E. Niforatos
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Visual Bypass
Reducing Token-Tax through Interface-Level Design
Every AI query passes through a system: a training corpus shapes a tokenizer’s vocabulary, that vocabulary is fixed inside a model, an API meters and prices access to it, a business layer wraps it in its own instructions, and only then does an interface let a user form their question. This thesis takes Donella Meadows’s framing of leverage points, which suggests places in a complex system where a small, well-chosen intervention produces disproportionate effects, as its lens, applied to one dysfunction in that stack: a tokenizer’s vocabulary, calibrated to whichever language dominates its training data, fragments non-English queries into more tokens than English ones for identical meaning. This token tax means two people asking the same health question pay a different price purely as a function of language. Every mitigation proposed so far, including expanding a tokenizer’s vocabulary, compressing an already-written prompt, and caching a repeated prefix, intervenes at the tokenizer or business layer; none touches the layer where a query is first formed. This thesis treats that interface layer as an unexamined leverage point and tests it directly, in the domain where the tax bites hardest: personal, multilingual consumer health questions.
The work proceeds in two movements. The first characterises the problem at its source: benchmarking real consumer health questions across English, Hindi, and Arabic, across three commercial models, confirms the tax is real, structural, and consistent in direction regardless of tokenizer, therefore a stable property of the model layer. The second tests whether the interface layer can counterweight it: MedQuery, a visual, non-verbal query interface built on a taxonomy of intents, open keywords, and ordinal parameters expressed through direct manipulation of a Kiviat diagram, replaces natural-language formulation with a compact, largely language-independent encoding, evaluated against free-text prompting across the same models and languages.
What this second study found is the clear demonstration of what a systems lens is for. The interface reduced token cost for some models, and reversed into a cost increase for another, therefore the largest effect observed anywhere in this analysis. Tracing that reversal upward through the stack shows it did not originate at the interface layer: it originated one layer above, in how differently each provider’s caching mechanism absorbed the structured system prompt. The interface behaved identically in every condition; what changed was a business-layer decision the designer cannot see or control without deliberately measuring for it. Response similarity between conditions stayed stable and moderate throughout, consistent with the interface reshaping emphasis rather than correctness; token savings, where they occurred, did not imply faster responses, suggesting that cost and speed are governed by separate mechanisms within the same stack.
The conclusion is therefore not simply that interface design is, or is not, an effective lever against the token tax. It is that leverage exercised at one layer of a multi-layer system cannot be evaluated, or trusted, from that layer alone—it must be verified against the layers it depends on, empirically and per provider, as standing practice rather than a one-time decision. That is both this thesis’s central finding and its methodological argument: the interface layer is real leverage, and knowing that required looking past the interface entirely.
Showcase:
https://youtu.be/0KlDJPVajj0 ...
The work proceeds in two movements. The first characterises the problem at its source: benchmarking real consumer health questions across English, Hindi, and Arabic, across three commercial models, confirms the tax is real, structural, and consistent in direction regardless of tokenizer, therefore a stable property of the model layer. The second tests whether the interface layer can counterweight it: MedQuery, a visual, non-verbal query interface built on a taxonomy of intents, open keywords, and ordinal parameters expressed through direct manipulation of a Kiviat diagram, replaces natural-language formulation with a compact, largely language-independent encoding, evaluated against free-text prompting across the same models and languages.
What this second study found is the clear demonstration of what a systems lens is for. The interface reduced token cost for some models, and reversed into a cost increase for another, therefore the largest effect observed anywhere in this analysis. Tracing that reversal upward through the stack shows it did not originate at the interface layer: it originated one layer above, in how differently each provider’s caching mechanism absorbed the structured system prompt. The interface behaved identically in every condition; what changed was a business-layer decision the designer cannot see or control without deliberately measuring for it. Response similarity between conditions stayed stable and moderate throughout, consistent with the interface reshaping emphasis rather than correctness; token savings, where they occurred, did not imply faster responses, suggesting that cost and speed are governed by separate mechanisms within the same stack.
The conclusion is therefore not simply that interface design is, or is not, an effective lever against the token tax. It is that leverage exercised at one layer of a multi-layer system cannot be evaluated, or trusted, from that layer alone—it must be verified against the layers it depends on, empirically and per provider, as standing practice rather than a one-time decision. That is both this thesis’s central finding and its methodological argument: the interface layer is real leverage, and knowing that required looking past the interface entirely.
Showcase:
https://youtu.be/0KlDJPVajj0 ...
Every AI query passes through a system: a training corpus shapes a tokenizer’s vocabulary, that vocabulary is fixed inside a model, an API meters and prices access to it, a business layer wraps it in its own instructions, and only then does an interface let a user form their question. This thesis takes Donella Meadows’s framing of leverage points, which suggests places in a complex system where a small, well-chosen intervention produces disproportionate effects, as its lens, applied to one dysfunction in that stack: a tokenizer’s vocabulary, calibrated to whichever language dominates its training data, fragments non-English queries into more tokens than English ones for identical meaning. This token tax means two people asking the same health question pay a different price purely as a function of language. Every mitigation proposed so far, including expanding a tokenizer’s vocabulary, compressing an already-written prompt, and caching a repeated prefix, intervenes at the tokenizer or business layer; none touches the layer where a query is first formed. This thesis treats that interface layer as an unexamined leverage point and tests it directly, in the domain where the tax bites hardest: personal, multilingual consumer health questions.
The work proceeds in two movements. The first characterises the problem at its source: benchmarking real consumer health questions across English, Hindi, and Arabic, across three commercial models, confirms the tax is real, structural, and consistent in direction regardless of tokenizer, therefore a stable property of the model layer. The second tests whether the interface layer can counterweight it: MedQuery, a visual, non-verbal query interface built on a taxonomy of intents, open keywords, and ordinal parameters expressed through direct manipulation of a Kiviat diagram, replaces natural-language formulation with a compact, largely language-independent encoding, evaluated against free-text prompting across the same models and languages.
What this second study found is the clear demonstration of what a systems lens is for. The interface reduced token cost for some models, and reversed into a cost increase for another, therefore the largest effect observed anywhere in this analysis. Tracing that reversal upward through the stack shows it did not originate at the interface layer: it originated one layer above, in how differently each provider’s caching mechanism absorbed the structured system prompt. The interface behaved identically in every condition; what changed was a business-layer decision the designer cannot see or control without deliberately measuring for it. Response similarity between conditions stayed stable and moderate throughout, consistent with the interface reshaping emphasis rather than correctness; token savings, where they occurred, did not imply faster responses, suggesting that cost and speed are governed by separate mechanisms within the same stack.
The conclusion is therefore not simply that interface design is, or is not, an effective lever against the token tax. It is that leverage exercised at one layer of a multi-layer system cannot be evaluated, or trusted, from that layer alone—it must be verified against the layers it depends on, empirically and per provider, as standing practice rather than a one-time decision. That is both this thesis’s central finding and its methodological argument: the interface layer is real leverage, and knowing that required looking past the interface entirely.
Showcase:
https://youtu.be/0KlDJPVajj0
The work proceeds in two movements. The first characterises the problem at its source: benchmarking real consumer health questions across English, Hindi, and Arabic, across three commercial models, confirms the tax is real, structural, and consistent in direction regardless of tokenizer, therefore a stable property of the model layer. The second tests whether the interface layer can counterweight it: MedQuery, a visual, non-verbal query interface built on a taxonomy of intents, open keywords, and ordinal parameters expressed through direct manipulation of a Kiviat diagram, replaces natural-language formulation with a compact, largely language-independent encoding, evaluated against free-text prompting across the same models and languages.
What this second study found is the clear demonstration of what a systems lens is for. The interface reduced token cost for some models, and reversed into a cost increase for another, therefore the largest effect observed anywhere in this analysis. Tracing that reversal upward through the stack shows it did not originate at the interface layer: it originated one layer above, in how differently each provider’s caching mechanism absorbed the structured system prompt. The interface behaved identically in every condition; what changed was a business-layer decision the designer cannot see or control without deliberately measuring for it. Response similarity between conditions stayed stable and moderate throughout, consistent with the interface reshaping emphasis rather than correctness; token savings, where they occurred, did not imply faster responses, suggesting that cost and speed are governed by separate mechanisms within the same stack.
The conclusion is therefore not simply that interface design is, or is not, an effective lever against the token tax. It is that leverage exercised at one layer of a multi-layer system cannot be evaluated, or trusted, from that layer alone—it must be verified against the layers it depends on, empirically and per provider, as standing practice rather than a one-time decision. That is both this thesis’s central finding and its methodological argument: the interface layer is real leverage, and knowing that required looking past the interface entirely.
Showcase:
https://youtu.be/0KlDJPVajj0
Type a prompt, wait a few seconds, and generative AI hands you a finished logo. A logo belongs to a brand’s identity, but so do its strategy, personality, and how it shows up across touchpoints. Brand identity is a network of connected decisions, where strategy shapes personality, personality shapes visual language, and visual language shapes every touchpoint a customer meets. Current AI tools work against this logic. The brand strategy defined in one tool is invisible to the image generator in another, since they are designed for single, disconnected, prompt-based outputs. At each stage, brand decisions must be manually re-entered. As a result, designer control is lost, brand consistency is threatened, and the creative process begins to represent what the tool can do rather than what the brand should be.
This thesis investigates how a node-based brand identity system can structure human-AI co-creation across the full brand identity workflow while maintaining the designer’s strategic and curatorial role. The work follows a Research through Design approach, structured by the Double Diamond. An exploratory phase, combining a literature review, a focus group with four agency brand designers, and a design hackathon, mapped how branding is practised and where AI currently fits. These findings, together with five concepts drawn from brand theory and human-AI interaction research, formed the theoretical framework for the design. Guided by this framework, a node-based system was built in Krea.ai across the six core branding phases, from research and discovery to guidelines and delivery, with around 90 nodes.
The system was evaluated through a qualitative usability study with six professional designers, combining a guided walkthrough, a think-aloud assignment, semi-structured interviews, and a Likert-scale survey. Reflexive thematic analysis produced four themes. Designers found the phase-based logic sound and instantly recognisable, located the friction in the platform interface rather than the node-based architecture, and consistently reclaimed authorship by curating outputs, editing prompts, and uploading their own work. Every participant judged the designer’s role to be equally or more important when working with the system, not less.
The findings show that a node-based system shifts the designer from asset creator to system architect: someone who designs the structure that produces brand assets, not only the assets themselves. This shift is evidenced at two levels. Building the system was itself a design activity in which the decisive choices concerned architecture, which nodes to connect, which models to assign, and where to place human control points, rather than individual visual outputs. In the evaluation, designers who had not built the system took up curatorial, directive, and prompt-authoring control, added nodes themselves, and reasoned about its structure, showing this orientation is accessible to those who operate the system, not only the one who built it. This makes design expertise more decisive, not less, while raising the value of new skills such as turning creative intent into precise prompts. Because the framework structures any multi-phase creative process where strategic intent must be carried across stages, the same logic may extend beyond branding to other design domains. ...
This thesis investigates how a node-based brand identity system can structure human-AI co-creation across the full brand identity workflow while maintaining the designer’s strategic and curatorial role. The work follows a Research through Design approach, structured by the Double Diamond. An exploratory phase, combining a literature review, a focus group with four agency brand designers, and a design hackathon, mapped how branding is practised and where AI currently fits. These findings, together with five concepts drawn from brand theory and human-AI interaction research, formed the theoretical framework for the design. Guided by this framework, a node-based system was built in Krea.ai across the six core branding phases, from research and discovery to guidelines and delivery, with around 90 nodes.
The system was evaluated through a qualitative usability study with six professional designers, combining a guided walkthrough, a think-aloud assignment, semi-structured interviews, and a Likert-scale survey. Reflexive thematic analysis produced four themes. Designers found the phase-based logic sound and instantly recognisable, located the friction in the platform interface rather than the node-based architecture, and consistently reclaimed authorship by curating outputs, editing prompts, and uploading their own work. Every participant judged the designer’s role to be equally or more important when working with the system, not less.
The findings show that a node-based system shifts the designer from asset creator to system architect: someone who designs the structure that produces brand assets, not only the assets themselves. This shift is evidenced at two levels. Building the system was itself a design activity in which the decisive choices concerned architecture, which nodes to connect, which models to assign, and where to place human control points, rather than individual visual outputs. In the evaluation, designers who had not built the system took up curatorial, directive, and prompt-authoring control, added nodes themselves, and reasoned about its structure, showing this orientation is accessible to those who operate the system, not only the one who built it. This makes design expertise more decisive, not less, while raising the value of new skills such as turning creative intent into precise prompts. Because the framework structures any multi-phase creative process where strategic intent must be carried across stages, the same logic may extend beyond branding to other design domains. ...
Type a prompt, wait a few seconds, and generative AI hands you a finished logo. A logo belongs to a brand’s identity, but so do its strategy, personality, and how it shows up across touchpoints. Brand identity is a network of connected decisions, where strategy shapes personality, personality shapes visual language, and visual language shapes every touchpoint a customer meets. Current AI tools work against this logic. The brand strategy defined in one tool is invisible to the image generator in another, since they are designed for single, disconnected, prompt-based outputs. At each stage, brand decisions must be manually re-entered. As a result, designer control is lost, brand consistency is threatened, and the creative process begins to represent what the tool can do rather than what the brand should be.
This thesis investigates how a node-based brand identity system can structure human-AI co-creation across the full brand identity workflow while maintaining the designer’s strategic and curatorial role. The work follows a Research through Design approach, structured by the Double Diamond. An exploratory phase, combining a literature review, a focus group with four agency brand designers, and a design hackathon, mapped how branding is practised and where AI currently fits. These findings, together with five concepts drawn from brand theory and human-AI interaction research, formed the theoretical framework for the design. Guided by this framework, a node-based system was built in Krea.ai across the six core branding phases, from research and discovery to guidelines and delivery, with around 90 nodes.
The system was evaluated through a qualitative usability study with six professional designers, combining a guided walkthrough, a think-aloud assignment, semi-structured interviews, and a Likert-scale survey. Reflexive thematic analysis produced four themes. Designers found the phase-based logic sound and instantly recognisable, located the friction in the platform interface rather than the node-based architecture, and consistently reclaimed authorship by curating outputs, editing prompts, and uploading their own work. Every participant judged the designer’s role to be equally or more important when working with the system, not less.
The findings show that a node-based system shifts the designer from asset creator to system architect: someone who designs the structure that produces brand assets, not only the assets themselves. This shift is evidenced at two levels. Building the system was itself a design activity in which the decisive choices concerned architecture, which nodes to connect, which models to assign, and where to place human control points, rather than individual visual outputs. In the evaluation, designers who had not built the system took up curatorial, directive, and prompt-authoring control, added nodes themselves, and reasoned about its structure, showing this orientation is accessible to those who operate the system, not only the one who built it. This makes design expertise more decisive, not less, while raising the value of new skills such as turning creative intent into precise prompts. Because the framework structures any multi-phase creative process where strategic intent must be carried across stages, the same logic may extend beyond branding to other design domains.
This thesis investigates how a node-based brand identity system can structure human-AI co-creation across the full brand identity workflow while maintaining the designer’s strategic and curatorial role. The work follows a Research through Design approach, structured by the Double Diamond. An exploratory phase, combining a literature review, a focus group with four agency brand designers, and a design hackathon, mapped how branding is practised and where AI currently fits. These findings, together with five concepts drawn from brand theory and human-AI interaction research, formed the theoretical framework for the design. Guided by this framework, a node-based system was built in Krea.ai across the six core branding phases, from research and discovery to guidelines and delivery, with around 90 nodes.
The system was evaluated through a qualitative usability study with six professional designers, combining a guided walkthrough, a think-aloud assignment, semi-structured interviews, and a Likert-scale survey. Reflexive thematic analysis produced four themes. Designers found the phase-based logic sound and instantly recognisable, located the friction in the platform interface rather than the node-based architecture, and consistently reclaimed authorship by curating outputs, editing prompts, and uploading their own work. Every participant judged the designer’s role to be equally or more important when working with the system, not less.
The findings show that a node-based system shifts the designer from asset creator to system architect: someone who designs the structure that produces brand assets, not only the assets themselves. This shift is evidenced at two levels. Building the system was itself a design activity in which the decisive choices concerned architecture, which nodes to connect, which models to assign, and where to place human control points, rather than individual visual outputs. In the evaluation, designers who had not built the system took up curatorial, directive, and prompt-authoring control, added nodes themselves, and reasoned about its structure, showing this orientation is accessible to those who operate the system, not only the one who built it. This makes design expertise more decisive, not less, while raising the value of new skills such as turning creative intent into precise prompts. Because the framework structures any multi-phase creative process where strategic intent must be carried across stages, the same logic may extend beyond branding to other design domains.
Social engineering is a major threat in today's cybersecurity landscape. Unlike other types of cyberattacks, social engineering focuses on exploiting human psychology rather than technical vulnerabilities. By manipulating individuals into revealing sensitive information or taking actions against their own interests, malicious actors can cause significant harm, ranging from financial loss to compromised systems. As a socio-technical problem, it requires not only technical measures but also awareness on the human side to defend against these threats. With advancements in technology and, most recently, generative artificial intelligence, social engineering attacks are becoming increasingly sophisticated, highlighting the urgency to educate individuals about how to recognise and defend against them. While existing efforts in research and industry mostly focus on interventions for workplace settings, little attention has been given to approaches targeted at the general public or everyday life contexts. This thesis addresses this gap by designing and evaluating a serious game to raise awareness of social engineering, focusing on families as the target group. The resulting game, “Connected & Protected”, employs an asymmetric tabletop format in which one player takes on the role of a social engineer, while the others play as family members, trying to protect their personal data from the attacker. The aim of the game is to educate players about common influence principles used in social engineering, how to counter them, and the risks that come with sharing personal data. The project takes a human-centred approach and involves users in multiple phases, including feedback sessions and playtesting to support concept development and prototyping. The game was evaluated using a pre- and post-test study design with 15 participants across five family groups, including a delayed post-test two weeks later to measure knowledge retention. The evaluation focused on three main areas: social engineering awareness, self-perceptions, and game experience. Results indicated that the game had positive effects on social engineering awareness, with significant improvements after gameplay that were largely retained at the delayed post-test. Participants improved in their ability to recognise influence principles in social engineering scenarios and showed increased knowledge about defensive strategies and data-sharing risks. Self-efficacy and perceived preparedness to deal with social engineering attempts likewise increased significantly after gameplay, while perceived susceptibility did not change notably. The game experience was overall well-received, with particularly high scores for enjoyment and audiovisual appeal, along with a positively rated perceived learning effect and willingness to play the game again. With this project, we provide novel insights into designing serious games for social engineering education aimed at the general public, leveraging the family setting as a medium for shared learning and intergenerational knowledge exchange. The contributions can serve as a starting point for practitioners and policymakers to extend security awareness interventions beyond the workplace, making social engineering education more accessible by bringing it into people's homes.
...
Social engineering is a major threat in today's cybersecurity landscape. Unlike other types of cyberattacks, social engineering focuses on exploiting human psychology rather than technical vulnerabilities. By manipulating individuals into revealing sensitive information or taking actions against their own interests, malicious actors can cause significant harm, ranging from financial loss to compromised systems. As a socio-technical problem, it requires not only technical measures but also awareness on the human side to defend against these threats. With advancements in technology and, most recently, generative artificial intelligence, social engineering attacks are becoming increasingly sophisticated, highlighting the urgency to educate individuals about how to recognise and defend against them. While existing efforts in research and industry mostly focus on interventions for workplace settings, little attention has been given to approaches targeted at the general public or everyday life contexts. This thesis addresses this gap by designing and evaluating a serious game to raise awareness of social engineering, focusing on families as the target group. The resulting game, “Connected & Protected”, employs an asymmetric tabletop format in which one player takes on the role of a social engineer, while the others play as family members, trying to protect their personal data from the attacker. The aim of the game is to educate players about common influence principles used in social engineering, how to counter them, and the risks that come with sharing personal data. The project takes a human-centred approach and involves users in multiple phases, including feedback sessions and playtesting to support concept development and prototyping. The game was evaluated using a pre- and post-test study design with 15 participants across five family groups, including a delayed post-test two weeks later to measure knowledge retention. The evaluation focused on three main areas: social engineering awareness, self-perceptions, and game experience. Results indicated that the game had positive effects on social engineering awareness, with significant improvements after gameplay that were largely retained at the delayed post-test. Participants improved in their ability to recognise influence principles in social engineering scenarios and showed increased knowledge about defensive strategies and data-sharing risks. Self-efficacy and perceived preparedness to deal with social engineering attempts likewise increased significantly after gameplay, while perceived susceptibility did not change notably. The game experience was overall well-received, with particularly high scores for enjoyment and audiovisual appeal, along with a positively rated perceived learning effect and willingness to play the game again. With this project, we provide novel insights into designing serious games for social engineering education aimed at the general public, leveraging the family setting as a medium for shared learning and intergenerational knowledge exchange. The contributions can serve as a starting point for practitioners and policymakers to extend security awareness interventions beyond the workplace, making social engineering education more accessible by bringing it into people's homes.
Source code and project files, including models, mm-wave radar drivers, and Max/MSP file for music generation: https://github.com/Jerry744/halfmind-flow
Try out TOVA test online. All data are saved locally in the browser: https://www.halfmind.nl ...
Try out TOVA test online. All data are saved locally in the browser: https://www.halfmind.nl ...
Source code and project files, including models, mm-wave radar drivers, and Max/MSP file for music generation: https://github.com/Jerry744/halfmind-flow
Try out TOVA test online. All data are saved locally in the browser: https://www.halfmind.nl
Try out TOVA test online. All data are saved locally in the browser: https://www.halfmind.nl
Beyond Wrong Turns
The Impact of Lane-Level Guidance and Distraction on the Cognitive Mechanisms of Navigation Errors
Navigation errors (missed, wrong, and risky turns) reflect cognitive failures that remain insufficiently understood in in-vehicle navigation. This thesis examines how level of map guidance detail and cognitive distraction shape these errors through the lens of situation awareness. In a 2×2 within-subjects simulator study (N=40), drivers completed four urban routes under Road-level versus Lane-level Navigation (LLN) guidance, with and without an auditory 2-back task. Multimodal data were collected, including vehicle control, eye movements, secondary task performance, and subjective workload and user experience ratings. Observed navigation errors were mapped to perception, interpretation, or decision-making failures in cognitive processes.
LLN significantly reduced interpretation failures and wrong turns, contributing to a 40% reduction in total errors. It also reallocated attention toward the navigation display, as shown by more frequent and longer glances and broader scanning, without degrading vehicle control. Distraction robustly elevated workload and reduced road monitoring, but session-level error rates remained unchanged. Interaction analyses showed that distraction attenuated LLN’s attention-shift effects, while LLN mitigated some distraction costs in road monitoring; certain control benefits, however, reversed under load. Driver experience moderated outcomes: experienced drivers benefited consistently from LLN, with fewer errors and lower workload, while less experienced drivers reported higher workload and a tendency toward more missed turns.
Together, these findings demonstrate how navigation errors can be systematically mapped to underlying cognitive failures and reveal how level of map guidance detail and distraction influence these processes, providing a foundation for more context-aware navigation support. ...
LLN significantly reduced interpretation failures and wrong turns, contributing to a 40% reduction in total errors. It also reallocated attention toward the navigation display, as shown by more frequent and longer glances and broader scanning, without degrading vehicle control. Distraction robustly elevated workload and reduced road monitoring, but session-level error rates remained unchanged. Interaction analyses showed that distraction attenuated LLN’s attention-shift effects, while LLN mitigated some distraction costs in road monitoring; certain control benefits, however, reversed under load. Driver experience moderated outcomes: experienced drivers benefited consistently from LLN, with fewer errors and lower workload, while less experienced drivers reported higher workload and a tendency toward more missed turns.
Together, these findings demonstrate how navigation errors can be systematically mapped to underlying cognitive failures and reveal how level of map guidance detail and distraction influence these processes, providing a foundation for more context-aware navigation support. ...
Navigation errors (missed, wrong, and risky turns) reflect cognitive failures that remain insufficiently understood in in-vehicle navigation. This thesis examines how level of map guidance detail and cognitive distraction shape these errors through the lens of situation awareness. In a 2×2 within-subjects simulator study (N=40), drivers completed four urban routes under Road-level versus Lane-level Navigation (LLN) guidance, with and without an auditory 2-back task. Multimodal data were collected, including vehicle control, eye movements, secondary task performance, and subjective workload and user experience ratings. Observed navigation errors were mapped to perception, interpretation, or decision-making failures in cognitive processes.
LLN significantly reduced interpretation failures and wrong turns, contributing to a 40% reduction in total errors. It also reallocated attention toward the navigation display, as shown by more frequent and longer glances and broader scanning, without degrading vehicle control. Distraction robustly elevated workload and reduced road monitoring, but session-level error rates remained unchanged. Interaction analyses showed that distraction attenuated LLN’s attention-shift effects, while LLN mitigated some distraction costs in road monitoring; certain control benefits, however, reversed under load. Driver experience moderated outcomes: experienced drivers benefited consistently from LLN, with fewer errors and lower workload, while less experienced drivers reported higher workload and a tendency toward more missed turns.
Together, these findings demonstrate how navigation errors can be systematically mapped to underlying cognitive failures and reveal how level of map guidance detail and distraction influence these processes, providing a foundation for more context-aware navigation support.
LLN significantly reduced interpretation failures and wrong turns, contributing to a 40% reduction in total errors. It also reallocated attention toward the navigation display, as shown by more frequent and longer glances and broader scanning, without degrading vehicle control. Distraction robustly elevated workload and reduced road monitoring, but session-level error rates remained unchanged. Interaction analyses showed that distraction attenuated LLN’s attention-shift effects, while LLN mitigated some distraction costs in road monitoring; certain control benefits, however, reversed under load. Driver experience moderated outcomes: experienced drivers benefited consistently from LLN, with fewer errors and lower workload, while less experienced drivers reported higher workload and a tendency toward more missed turns.
Together, these findings demonstrate how navigation errors can be systematically mapped to underlying cognitive failures and reveal how level of map guidance detail and distraction influence these processes, providing a foundation for more context-aware navigation support.
Modern factories showlittle resemblance to the assembly lines froma century ago. Nowadays, a single human might be responsible for setting up, operating, and maintaining a complex chain of machines. This shift has made the work of factory operators more cognitively demanding, requiring constant monitoring and problem-solving. Key to tackling these challenges is the effective collaboration of human operators in exchanging ideas and knowledge, from high-level problem-solving strategies to solutions for emerging issues. Yet, the heightened productivity requirements and small shifts mean fewer opportunities to share this knowledge face-to-face and reporting practices are deprioritized. Thus, the manufacturing industry faces a knowledge management crisis.
This dissertation investigates the integration of conversational AI assistants into manufacturing settings to facilitate knowledge sharing among factory operators. Capitalizing on recent advancements in Natural Language Processing (NLP), particularly in Large Language Models (LLMs), this research investigates the designing and evaluation of conversational AI tools that efficiently capture and share human knowledge on the factory floor while addressing operator needs and concerns. The introduction of conversational AI assistants for knowledge sharing—referred to as cognitive assistants (CA) in this work—in factory environments promises significant benefits but comes with numerous challenges.... ...
This dissertation investigates the integration of conversational AI assistants into manufacturing settings to facilitate knowledge sharing among factory operators. Capitalizing on recent advancements in Natural Language Processing (NLP), particularly in Large Language Models (LLMs), this research investigates the designing and evaluation of conversational AI tools that efficiently capture and share human knowledge on the factory floor while addressing operator needs and concerns. The introduction of conversational AI assistants for knowledge sharing—referred to as cognitive assistants (CA) in this work—in factory environments promises significant benefits but comes with numerous challenges.... ...
Modern factories showlittle resemblance to the assembly lines froma century ago. Nowadays, a single human might be responsible for setting up, operating, and maintaining a complex chain of machines. This shift has made the work of factory operators more cognitively demanding, requiring constant monitoring and problem-solving. Key to tackling these challenges is the effective collaboration of human operators in exchanging ideas and knowledge, from high-level problem-solving strategies to solutions for emerging issues. Yet, the heightened productivity requirements and small shifts mean fewer opportunities to share this knowledge face-to-face and reporting practices are deprioritized. Thus, the manufacturing industry faces a knowledge management crisis.
This dissertation investigates the integration of conversational AI assistants into manufacturing settings to facilitate knowledge sharing among factory operators. Capitalizing on recent advancements in Natural Language Processing (NLP), particularly in Large Language Models (LLMs), this research investigates the designing and evaluation of conversational AI tools that efficiently capture and share human knowledge on the factory floor while addressing operator needs and concerns. The introduction of conversational AI assistants for knowledge sharing—referred to as cognitive assistants (CA) in this work—in factory environments promises significant benefits but comes with numerous challenges....
This dissertation investigates the integration of conversational AI assistants into manufacturing settings to facilitate knowledge sharing among factory operators. Capitalizing on recent advancements in Natural Language Processing (NLP), particularly in Large Language Models (LLMs), this research investigates the designing and evaluation of conversational AI tools that efficiently capture and share human knowledge on the factory floor while addressing operator needs and concerns. The introduction of conversational AI assistants for knowledge sharing—referred to as cognitive assistants (CA) in this work—in factory environments promises significant benefits but comes with numerous challenges....
Enabling Domain Expert Evaluation of Emerging AI Technologies in Healthcare Settings
Introduction of Dual-Core Evaluation Framework for Conversational AI in Healthcare
In the rapidly evolving healthcare landscape, integrating Artificial Intelligence (AI), particularly Large Language Models (LLMs), presents significant opportunities and complex challenges. This study examines the efficacy and implications of LLMs within healthcare systems, with a focus on enhancing user-centric evaluation methods for AI-generated healthcare advice. The research centres on three critical areas: Identifying the limitations of current evaluation methods, addressing the challenges related to the accuracy and reliability of LLM-generated advice, and proposing improvements to evaluation frameworks to enhance the practical application of these models in healthcare settings.
Our study utilizes a chatbot prototype trained specifically on healthcare datasets relevant to the Dutch context, exploring its application in real-world scenarios to validate and refine evaluation metrics. By involving healthcare professionals in interactions with the chatbot, we aim to ground our findings in practical, user-based experiences. The engagement with the prototype helps uncover vital insights into the AI’s performance, emphasizing the necessity for models that generate reliable and ethical responses and resonate with professional healthcare practices.
The proposed research contributes to the broader discourse on AI in healthcare by offering a novel framework for assessing AI-generated responses through a blend of empirical user studies and theoretical analysis. This framework aims to mitigate the subjective nature of current evaluations and provide a more robust, standardized approach to assessing the impact of AI technologies on healthcare outcomes. Through this research, we aim to forge a path toward more responsive, responsible, and user-centred AI tools in healthcare, ensuring that they align with both professional standards and patient needs.
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Our study utilizes a chatbot prototype trained specifically on healthcare datasets relevant to the Dutch context, exploring its application in real-world scenarios to validate and refine evaluation metrics. By involving healthcare professionals in interactions with the chatbot, we aim to ground our findings in practical, user-based experiences. The engagement with the prototype helps uncover vital insights into the AI’s performance, emphasizing the necessity for models that generate reliable and ethical responses and resonate with professional healthcare practices.
The proposed research contributes to the broader discourse on AI in healthcare by offering a novel framework for assessing AI-generated responses through a blend of empirical user studies and theoretical analysis. This framework aims to mitigate the subjective nature of current evaluations and provide a more robust, standardized approach to assessing the impact of AI technologies on healthcare outcomes. Through this research, we aim to forge a path toward more responsive, responsible, and user-centred AI tools in healthcare, ensuring that they align with both professional standards and patient needs.
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In the rapidly evolving healthcare landscape, integrating Artificial Intelligence (AI), particularly Large Language Models (LLMs), presents significant opportunities and complex challenges. This study examines the efficacy and implications of LLMs within healthcare systems, with a focus on enhancing user-centric evaluation methods for AI-generated healthcare advice. The research centres on three critical areas: Identifying the limitations of current evaluation methods, addressing the challenges related to the accuracy and reliability of LLM-generated advice, and proposing improvements to evaluation frameworks to enhance the practical application of these models in healthcare settings.
Our study utilizes a chatbot prototype trained specifically on healthcare datasets relevant to the Dutch context, exploring its application in real-world scenarios to validate and refine evaluation metrics. By involving healthcare professionals in interactions with the chatbot, we aim to ground our findings in practical, user-based experiences. The engagement with the prototype helps uncover vital insights into the AI’s performance, emphasizing the necessity for models that generate reliable and ethical responses and resonate with professional healthcare practices.
The proposed research contributes to the broader discourse on AI in healthcare by offering a novel framework for assessing AI-generated responses through a blend of empirical user studies and theoretical analysis. This framework aims to mitigate the subjective nature of current evaluations and provide a more robust, standardized approach to assessing the impact of AI technologies on healthcare outcomes. Through this research, we aim to forge a path toward more responsive, responsible, and user-centred AI tools in healthcare, ensuring that they align with both professional standards and patient needs.
Our study utilizes a chatbot prototype trained specifically on healthcare datasets relevant to the Dutch context, exploring its application in real-world scenarios to validate and refine evaluation metrics. By involving healthcare professionals in interactions with the chatbot, we aim to ground our findings in practical, user-based experiences. The engagement with the prototype helps uncover vital insights into the AI’s performance, emphasizing the necessity for models that generate reliable and ethical responses and resonate with professional healthcare practices.
The proposed research contributes to the broader discourse on AI in healthcare by offering a novel framework for assessing AI-generated responses through a blend of empirical user studies and theoretical analysis. This framework aims to mitigate the subjective nature of current evaluations and provide a more robust, standardized approach to assessing the impact of AI technologies on healthcare outcomes. Through this research, we aim to forge a path toward more responsive, responsible, and user-centred AI tools in healthcare, ensuring that they align with both professional standards and patient needs.
Designing with AI : Video to Mindmaps
“Exploring the Potential of Generating AI-Mindmaps from Videos to Enhance Video Analysis Workflows for Designers”
In today’s world, products are increasingly intertwined with our daily lives, becoming more intricate. To design these interactions effectively, designers need to comprehend both the people involved in the activities and the technical systems. As user-centered design spreads, the focus shifts from viewing design as problemsolving to recognizing it as the social creation of new possibilities. This shift highlights the importance of users and their everyday lives, as well as their interactions with the product in designing.
Videos serve as a powerful tool for learning about users, their behaviors, and interactions. Video Based Design (VBD) involves analyzing videos to interpret, infer, question actions, and understand the user’s thought process. However, this approach can extend the time and analytical rigor needed due to the extensive analysis required to draw valid conclusions from the video content. To streamline this process and enhance researchers’ workflow, we prototyped a tool that can produce mind maps from videos. These mind maps serve as a visual representation of the video’s key concepts in an organized manner. This tool utilizes Large Language Models (LLMs) to process multimodal video inputs and output the generated mind maps.
To assess the impact of mind maps on the video-based design process, an experimental study was conducted involving 28 designers. Participants were asked to watch two videos from different contexts and then engage in activities using mind maps generated by both the LLM and a human designer. Through quantitative and qualitative analysis of the study data, we gained valuable insights, identified strengths and weaknesses, and proposed design enhancements for the next version of the tool. ...
Videos serve as a powerful tool for learning about users, their behaviors, and interactions. Video Based Design (VBD) involves analyzing videos to interpret, infer, question actions, and understand the user’s thought process. However, this approach can extend the time and analytical rigor needed due to the extensive analysis required to draw valid conclusions from the video content. To streamline this process and enhance researchers’ workflow, we prototyped a tool that can produce mind maps from videos. These mind maps serve as a visual representation of the video’s key concepts in an organized manner. This tool utilizes Large Language Models (LLMs) to process multimodal video inputs and output the generated mind maps.
To assess the impact of mind maps on the video-based design process, an experimental study was conducted involving 28 designers. Participants were asked to watch two videos from different contexts and then engage in activities using mind maps generated by both the LLM and a human designer. Through quantitative and qualitative analysis of the study data, we gained valuable insights, identified strengths and weaknesses, and proposed design enhancements for the next version of the tool. ...
In today’s world, products are increasingly intertwined with our daily lives, becoming more intricate. To design these interactions effectively, designers need to comprehend both the people involved in the activities and the technical systems. As user-centered design spreads, the focus shifts from viewing design as problemsolving to recognizing it as the social creation of new possibilities. This shift highlights the importance of users and their everyday lives, as well as their interactions with the product in designing.
Videos serve as a powerful tool for learning about users, their behaviors, and interactions. Video Based Design (VBD) involves analyzing videos to interpret, infer, question actions, and understand the user’s thought process. However, this approach can extend the time and analytical rigor needed due to the extensive analysis required to draw valid conclusions from the video content. To streamline this process and enhance researchers’ workflow, we prototyped a tool that can produce mind maps from videos. These mind maps serve as a visual representation of the video’s key concepts in an organized manner. This tool utilizes Large Language Models (LLMs) to process multimodal video inputs and output the generated mind maps.
To assess the impact of mind maps on the video-based design process, an experimental study was conducted involving 28 designers. Participants were asked to watch two videos from different contexts and then engage in activities using mind maps generated by both the LLM and a human designer. Through quantitative and qualitative analysis of the study data, we gained valuable insights, identified strengths and weaknesses, and proposed design enhancements for the next version of the tool.
Videos serve as a powerful tool for learning about users, their behaviors, and interactions. Video Based Design (VBD) involves analyzing videos to interpret, infer, question actions, and understand the user’s thought process. However, this approach can extend the time and analytical rigor needed due to the extensive analysis required to draw valid conclusions from the video content. To streamline this process and enhance researchers’ workflow, we prototyped a tool that can produce mind maps from videos. These mind maps serve as a visual representation of the video’s key concepts in an organized manner. This tool utilizes Large Language Models (LLMs) to process multimodal video inputs and output the generated mind maps.
To assess the impact of mind maps on the video-based design process, an experimental study was conducted involving 28 designers. Participants were asked to watch two videos from different contexts and then engage in activities using mind maps generated by both the LLM and a human designer. Through quantitative and qualitative analysis of the study data, we gained valuable insights, identified strengths and weaknesses, and proposed design enhancements for the next version of the tool.
Introduction: Individuals with burnout often experience cognitive challenges in general performance or the excessive effort to perform certain tasks. With the increasing work pace over the years, on average, over 10% of workers in Europe and over 17% in non-European countries had experienced burnout up until 2018 (Schaufeli, 2018). Personal solutions like websites and guided meditation applications have emerged to help alleviate burnout symptoms. Governments have passed legislation to prevent burnout from occurring.
The advancing cognitive personal informatics (CPI) technology has made it possible to monitor psychophysiological data and quantify human cognition and cognitive activities. The quantified human cognition-related data could be of great value to people who wish to be more aware of their condition or needs and refer to this information in reflective activities to become a better version of themselves.
Methodology: Three main research questions were generated to inquire about the role of cognitive data in burnout solutions. This project follows the principles of participatory design and the double diamond framework with minor adaptations to answer the research questions. Background research was conducted to gather theoretical and practical information on topics related to burnout solutions, measures of cognitive data, and state-of-the-art CPI technology. Semi-structured interviews with people with burnout experience were conducted as a user study. Creative sessions with target users were conducted to guide the design direction.
Results: The background research clarified the basic burnout profile as well as the cognitive burnout correlates that can be measured by CPI systems. This part of the research elaborated on 7 key correlates that can later be applied in the design phase. The participatory design research activities revealed different perspectives from potential users on burnout that complemented the background research. The participatory design activities also proposed key features that shaped the initial concept.
Conclusion: A design guideline was proposed to help users make good use of CPI technology and self-reflection to search for burnout solutions independently based on the research findings. Some of the key stages in the guideline were conceptualized into wireframes. The guideline suggests users should have full control and support over the entire burnout recovery process, with resources for community support when needed. ...
The advancing cognitive personal informatics (CPI) technology has made it possible to monitor psychophysiological data and quantify human cognition and cognitive activities. The quantified human cognition-related data could be of great value to people who wish to be more aware of their condition or needs and refer to this information in reflective activities to become a better version of themselves.
Methodology: Three main research questions were generated to inquire about the role of cognitive data in burnout solutions. This project follows the principles of participatory design and the double diamond framework with minor adaptations to answer the research questions. Background research was conducted to gather theoretical and practical information on topics related to burnout solutions, measures of cognitive data, and state-of-the-art CPI technology. Semi-structured interviews with people with burnout experience were conducted as a user study. Creative sessions with target users were conducted to guide the design direction.
Results: The background research clarified the basic burnout profile as well as the cognitive burnout correlates that can be measured by CPI systems. This part of the research elaborated on 7 key correlates that can later be applied in the design phase. The participatory design research activities revealed different perspectives from potential users on burnout that complemented the background research. The participatory design activities also proposed key features that shaped the initial concept.
Conclusion: A design guideline was proposed to help users make good use of CPI technology and self-reflection to search for burnout solutions independently based on the research findings. Some of the key stages in the guideline were conceptualized into wireframes. The guideline suggests users should have full control and support over the entire burnout recovery process, with resources for community support when needed. ...
Introduction: Individuals with burnout often experience cognitive challenges in general performance or the excessive effort to perform certain tasks. With the increasing work pace over the years, on average, over 10% of workers in Europe and over 17% in non-European countries had experienced burnout up until 2018 (Schaufeli, 2018). Personal solutions like websites and guided meditation applications have emerged to help alleviate burnout symptoms. Governments have passed legislation to prevent burnout from occurring.
The advancing cognitive personal informatics (CPI) technology has made it possible to monitor psychophysiological data and quantify human cognition and cognitive activities. The quantified human cognition-related data could be of great value to people who wish to be more aware of their condition or needs and refer to this information in reflective activities to become a better version of themselves.
Methodology: Three main research questions were generated to inquire about the role of cognitive data in burnout solutions. This project follows the principles of participatory design and the double diamond framework with minor adaptations to answer the research questions. Background research was conducted to gather theoretical and practical information on topics related to burnout solutions, measures of cognitive data, and state-of-the-art CPI technology. Semi-structured interviews with people with burnout experience were conducted as a user study. Creative sessions with target users were conducted to guide the design direction.
Results: The background research clarified the basic burnout profile as well as the cognitive burnout correlates that can be measured by CPI systems. This part of the research elaborated on 7 key correlates that can later be applied in the design phase. The participatory design research activities revealed different perspectives from potential users on burnout that complemented the background research. The participatory design activities also proposed key features that shaped the initial concept.
Conclusion: A design guideline was proposed to help users make good use of CPI technology and self-reflection to search for burnout solutions independently based on the research findings. Some of the key stages in the guideline were conceptualized into wireframes. The guideline suggests users should have full control and support over the entire burnout recovery process, with resources for community support when needed.
The advancing cognitive personal informatics (CPI) technology has made it possible to monitor psychophysiological data and quantify human cognition and cognitive activities. The quantified human cognition-related data could be of great value to people who wish to be more aware of their condition or needs and refer to this information in reflective activities to become a better version of themselves.
Methodology: Three main research questions were generated to inquire about the role of cognitive data in burnout solutions. This project follows the principles of participatory design and the double diamond framework with minor adaptations to answer the research questions. Background research was conducted to gather theoretical and practical information on topics related to burnout solutions, measures of cognitive data, and state-of-the-art CPI technology. Semi-structured interviews with people with burnout experience were conducted as a user study. Creative sessions with target users were conducted to guide the design direction.
Results: The background research clarified the basic burnout profile as well as the cognitive burnout correlates that can be measured by CPI systems. This part of the research elaborated on 7 key correlates that can later be applied in the design phase. The participatory design research activities revealed different perspectives from potential users on burnout that complemented the background research. The participatory design activities also proposed key features that shaped the initial concept.
Conclusion: A design guideline was proposed to help users make good use of CPI technology and self-reflection to search for burnout solutions independently based on the research findings. Some of the key stages in the guideline were conceptualized into wireframes. The guideline suggests users should have full control and support over the entire burnout recovery process, with resources for community support when needed.
Surgeon-friendly 3D Navigation
Bridging the Gap between Conventional Medical Imaging and Holographic Technology
Hepatopancreato-biliary (HPB) surgeons, when planning complex cases of pancreatic cancer, lose precious time because of difficulties in visualising the interaction between tumour and blood vessels and identifying patient-specific anatomy. To tackle this issue, the Integrated Imaging Workstation (IIW) was prototyped by e/MTIC and Philips. This prototype encompasses a conventional medical viewer and a holographic display to visualise the same medical data, providing a functional basis and showing promise. However, it lacks a human-centred interaction design, particularly in integrating it into a surgeon’s established interaction flows with conventional medical imaging, as a study with 13 expert surgeons highlights. The literature review and empirical research show that surgeons iteratively scroll through scans to build a mental 3D reconstruction of the anatomy, and have two personal approaches to finding anatomical landmarks and interactions, “vertical scan” and “zoom in and out”. Also, it unveils 3 key design opportunities: minimising workflow disruption, visualising both overview and detail and balancing speed and control in the interaction.
These findings were translated into multiple design concepts, such as one with different modes of visualisation depending on anatomical landmarks. The most desirable concepts were combined into a navigation system, which in turn went through one expert feedback iteration. The final design comprises a system for surgeons to easily select anatomical landmarks through 2D medical imaging. This enables reaching and controlling desired points of view, which then can be orbited around. A high-fidelity prototype was implemented with Unity3D and evaluated. The mixed-method evaluation study with 3 expert HPB surgeons shows promise towards the overall usability of the navigation system and its clinical application. However, some aspects of the interaction, such as the selection of minor vessel branches and missing visual feedback for point-of-view changes, need refinement. These results illustrate a solid human-centred design direction for supporting surgeons in finding crucial landmarks and vascular interactions, as well as an approach to integrate 3D medical visualisation into established workflow with 2D imaging of HPB surgeons.
This thesis hopes to be a starting point for future iterations of the IIW. For example, using metaphors to help the surgeons establish a mental model of the 3D camera system could be tested, or scoping the main user focus to novice surgeons could be helpful to refine the design. Furthermore, this project could be relevant for other research and design endeavours that aim to inject 3D medical visualisation technology into existing workflows in a surgeon-friendly manner.
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These findings were translated into multiple design concepts, such as one with different modes of visualisation depending on anatomical landmarks. The most desirable concepts were combined into a navigation system, which in turn went through one expert feedback iteration. The final design comprises a system for surgeons to easily select anatomical landmarks through 2D medical imaging. This enables reaching and controlling desired points of view, which then can be orbited around. A high-fidelity prototype was implemented with Unity3D and evaluated. The mixed-method evaluation study with 3 expert HPB surgeons shows promise towards the overall usability of the navigation system and its clinical application. However, some aspects of the interaction, such as the selection of minor vessel branches and missing visual feedback for point-of-view changes, need refinement. These results illustrate a solid human-centred design direction for supporting surgeons in finding crucial landmarks and vascular interactions, as well as an approach to integrate 3D medical visualisation into established workflow with 2D imaging of HPB surgeons.
This thesis hopes to be a starting point for future iterations of the IIW. For example, using metaphors to help the surgeons establish a mental model of the 3D camera system could be tested, or scoping the main user focus to novice surgeons could be helpful to refine the design. Furthermore, this project could be relevant for other research and design endeavours that aim to inject 3D medical visualisation technology into existing workflows in a surgeon-friendly manner.
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Hepatopancreato-biliary (HPB) surgeons, when planning complex cases of pancreatic cancer, lose precious time because of difficulties in visualising the interaction between tumour and blood vessels and identifying patient-specific anatomy. To tackle this issue, the Integrated Imaging Workstation (IIW) was prototyped by e/MTIC and Philips. This prototype encompasses a conventional medical viewer and a holographic display to visualise the same medical data, providing a functional basis and showing promise. However, it lacks a human-centred interaction design, particularly in integrating it into a surgeon’s established interaction flows with conventional medical imaging, as a study with 13 expert surgeons highlights. The literature review and empirical research show that surgeons iteratively scroll through scans to build a mental 3D reconstruction of the anatomy, and have two personal approaches to finding anatomical landmarks and interactions, “vertical scan” and “zoom in and out”. Also, it unveils 3 key design opportunities: minimising workflow disruption, visualising both overview and detail and balancing speed and control in the interaction.
These findings were translated into multiple design concepts, such as one with different modes of visualisation depending on anatomical landmarks. The most desirable concepts were combined into a navigation system, which in turn went through one expert feedback iteration. The final design comprises a system for surgeons to easily select anatomical landmarks through 2D medical imaging. This enables reaching and controlling desired points of view, which then can be orbited around. A high-fidelity prototype was implemented with Unity3D and evaluated. The mixed-method evaluation study with 3 expert HPB surgeons shows promise towards the overall usability of the navigation system and its clinical application. However, some aspects of the interaction, such as the selection of minor vessel branches and missing visual feedback for point-of-view changes, need refinement. These results illustrate a solid human-centred design direction for supporting surgeons in finding crucial landmarks and vascular interactions, as well as an approach to integrate 3D medical visualisation into established workflow with 2D imaging of HPB surgeons.
This thesis hopes to be a starting point for future iterations of the IIW. For example, using metaphors to help the surgeons establish a mental model of the 3D camera system could be tested, or scoping the main user focus to novice surgeons could be helpful to refine the design. Furthermore, this project could be relevant for other research and design endeavours that aim to inject 3D medical visualisation technology into existing workflows in a surgeon-friendly manner.
These findings were translated into multiple design concepts, such as one with different modes of visualisation depending on anatomical landmarks. The most desirable concepts were combined into a navigation system, which in turn went through one expert feedback iteration. The final design comprises a system for surgeons to easily select anatomical landmarks through 2D medical imaging. This enables reaching and controlling desired points of view, which then can be orbited around. A high-fidelity prototype was implemented with Unity3D and evaluated. The mixed-method evaluation study with 3 expert HPB surgeons shows promise towards the overall usability of the navigation system and its clinical application. However, some aspects of the interaction, such as the selection of minor vessel branches and missing visual feedback for point-of-view changes, need refinement. These results illustrate a solid human-centred design direction for supporting surgeons in finding crucial landmarks and vascular interactions, as well as an approach to integrate 3D medical visualisation into established workflow with 2D imaging of HPB surgeons.
This thesis hopes to be a starting point for future iterations of the IIW. For example, using metaphors to help the surgeons establish a mental model of the 3D camera system could be tested, or scoping the main user focus to novice surgeons could be helpful to refine the design. Furthermore, this project could be relevant for other research and design endeavours that aim to inject 3D medical visualisation technology into existing workflows in a surgeon-friendly manner.
An Emotion-Adaptive VR Experience for Recreational Use with People Living with Dementia
A study that leverages the technology of electromyography
Dementia is an umbrella term for progressive loss of cognitive abilities, which mainly affects elderly- affecting relationships, feelings and behaviour. A person living with dementia (PLWD) might forget the names of their grandchildren, the face of their loved ones, important places and life events. Due to the rising population growth with more than 55 million people living with dementia (8.1 % of women and 5.4% of men over 65 years) and increasing life expectancies, dementia is already recognized by the WHO (World Health Organization) as a public health priority, and it is now the 7th leading cause of death (WHO, 2021).
The population pressure that care homes are currently under cannot be easily remedied without significant monetary investment into the manpower of the industry. Therefore it would be more fruitful to enable PLWD to function more independently from the help of their carers.
VR technology has seen immense growth in the last 10 years especially within the field of child and elderly care. Although dementia has been understood since 700BCE, the decrease in stigma has allowed the current era of dementia care to flourish using music, art and drama therapy- amongst other person-centred care techniques. Combining these reminiscence therapy techniques with the booming technology of VR is therefore the next logical step in improving immersion. To this end, VR offers control and consistency in testing virtual environments that guarantee safety. However, a key obstacle in the uptake of VR for PLWD is the risk of behavioural and psychological symptoms of dementia- negative behaviours. To reduce these behaviours, a balance must be struck between stimulation and overload- namely stress.
Emotion classification models were established using the valence-arousal circumplex model before identifying the physiological embodiments of such emotion. Of the stress sensing technology surveyed, electromyography was the only technology reviewed that showed evidence of accurate, low-latency, sensation of arousal and valence by way of measuring contractions in the trapezius and zygomaticus muscles respectively.
To design a conducive VR environment, overarching goals for reminiscence in VR were identified as presence, occupation, comfort, inclusion and novelty. The method of reminiscence therapy was broken down into three forms- place, object and interaction based. The parameters of brightness, volume and non-player character movement were established to be adapted in VR for stress reduction over the course of a 10 minute exploration test.
Results of the study showed a 26% decrease in average stress experienced during the three modulation stages over the control stage. Volume modulation was identified as the most effective parameter showing a 32% stress reduction.
Participants reported that the presentation of familiar environments in VR did in fact promote feelings of nostalgia and reported moments of reminiscence. Future work opportunities call for more studies with PLWD, multi-modal & multi-channel stress sensing and concurrent parameter modulation.
Technology improvements such as integrating all peripherals into a standalone system as well as utilising more convenient and ergonomic sensors that could be applied semi-permanently to form a more holistic data overview for PLWD outside experimental conditions.
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The population pressure that care homes are currently under cannot be easily remedied without significant monetary investment into the manpower of the industry. Therefore it would be more fruitful to enable PLWD to function more independently from the help of their carers.
VR technology has seen immense growth in the last 10 years especially within the field of child and elderly care. Although dementia has been understood since 700BCE, the decrease in stigma has allowed the current era of dementia care to flourish using music, art and drama therapy- amongst other person-centred care techniques. Combining these reminiscence therapy techniques with the booming technology of VR is therefore the next logical step in improving immersion. To this end, VR offers control and consistency in testing virtual environments that guarantee safety. However, a key obstacle in the uptake of VR for PLWD is the risk of behavioural and psychological symptoms of dementia- negative behaviours. To reduce these behaviours, a balance must be struck between stimulation and overload- namely stress.
Emotion classification models were established using the valence-arousal circumplex model before identifying the physiological embodiments of such emotion. Of the stress sensing technology surveyed, electromyography was the only technology reviewed that showed evidence of accurate, low-latency, sensation of arousal and valence by way of measuring contractions in the trapezius and zygomaticus muscles respectively.
To design a conducive VR environment, overarching goals for reminiscence in VR were identified as presence, occupation, comfort, inclusion and novelty. The method of reminiscence therapy was broken down into three forms- place, object and interaction based. The parameters of brightness, volume and non-player character movement were established to be adapted in VR for stress reduction over the course of a 10 minute exploration test.
Results of the study showed a 26% decrease in average stress experienced during the three modulation stages over the control stage. Volume modulation was identified as the most effective parameter showing a 32% stress reduction.
Participants reported that the presentation of familiar environments in VR did in fact promote feelings of nostalgia and reported moments of reminiscence. Future work opportunities call for more studies with PLWD, multi-modal & multi-channel stress sensing and concurrent parameter modulation.
Technology improvements such as integrating all peripherals into a standalone system as well as utilising more convenient and ergonomic sensors that could be applied semi-permanently to form a more holistic data overview for PLWD outside experimental conditions.
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Dementia is an umbrella term for progressive loss of cognitive abilities, which mainly affects elderly- affecting relationships, feelings and behaviour. A person living with dementia (PLWD) might forget the names of their grandchildren, the face of their loved ones, important places and life events. Due to the rising population growth with more than 55 million people living with dementia (8.1 % of women and 5.4% of men over 65 years) and increasing life expectancies, dementia is already recognized by the WHO (World Health Organization) as a public health priority, and it is now the 7th leading cause of death (WHO, 2021).
The population pressure that care homes are currently under cannot be easily remedied without significant monetary investment into the manpower of the industry. Therefore it would be more fruitful to enable PLWD to function more independently from the help of their carers.
VR technology has seen immense growth in the last 10 years especially within the field of child and elderly care. Although dementia has been understood since 700BCE, the decrease in stigma has allowed the current era of dementia care to flourish using music, art and drama therapy- amongst other person-centred care techniques. Combining these reminiscence therapy techniques with the booming technology of VR is therefore the next logical step in improving immersion. To this end, VR offers control and consistency in testing virtual environments that guarantee safety. However, a key obstacle in the uptake of VR for PLWD is the risk of behavioural and psychological symptoms of dementia- negative behaviours. To reduce these behaviours, a balance must be struck between stimulation and overload- namely stress.
Emotion classification models were established using the valence-arousal circumplex model before identifying the physiological embodiments of such emotion. Of the stress sensing technology surveyed, electromyography was the only technology reviewed that showed evidence of accurate, low-latency, sensation of arousal and valence by way of measuring contractions in the trapezius and zygomaticus muscles respectively.
To design a conducive VR environment, overarching goals for reminiscence in VR were identified as presence, occupation, comfort, inclusion and novelty. The method of reminiscence therapy was broken down into three forms- place, object and interaction based. The parameters of brightness, volume and non-player character movement were established to be adapted in VR for stress reduction over the course of a 10 minute exploration test.
Results of the study showed a 26% decrease in average stress experienced during the three modulation stages over the control stage. Volume modulation was identified as the most effective parameter showing a 32% stress reduction.
Participants reported that the presentation of familiar environments in VR did in fact promote feelings of nostalgia and reported moments of reminiscence. Future work opportunities call for more studies with PLWD, multi-modal & multi-channel stress sensing and concurrent parameter modulation.
Technology improvements such as integrating all peripherals into a standalone system as well as utilising more convenient and ergonomic sensors that could be applied semi-permanently to form a more holistic data overview for PLWD outside experimental conditions.
The population pressure that care homes are currently under cannot be easily remedied without significant monetary investment into the manpower of the industry. Therefore it would be more fruitful to enable PLWD to function more independently from the help of their carers.
VR technology has seen immense growth in the last 10 years especially within the field of child and elderly care. Although dementia has been understood since 700BCE, the decrease in stigma has allowed the current era of dementia care to flourish using music, art and drama therapy- amongst other person-centred care techniques. Combining these reminiscence therapy techniques with the booming technology of VR is therefore the next logical step in improving immersion. To this end, VR offers control and consistency in testing virtual environments that guarantee safety. However, a key obstacle in the uptake of VR for PLWD is the risk of behavioural and psychological symptoms of dementia- negative behaviours. To reduce these behaviours, a balance must be struck between stimulation and overload- namely stress.
Emotion classification models were established using the valence-arousal circumplex model before identifying the physiological embodiments of such emotion. Of the stress sensing technology surveyed, electromyography was the only technology reviewed that showed evidence of accurate, low-latency, sensation of arousal and valence by way of measuring contractions in the trapezius and zygomaticus muscles respectively.
To design a conducive VR environment, overarching goals for reminiscence in VR were identified as presence, occupation, comfort, inclusion and novelty. The method of reminiscence therapy was broken down into three forms- place, object and interaction based. The parameters of brightness, volume and non-player character movement were established to be adapted in VR for stress reduction over the course of a 10 minute exploration test.
Results of the study showed a 26% decrease in average stress experienced during the three modulation stages over the control stage. Volume modulation was identified as the most effective parameter showing a 32% stress reduction.
Participants reported that the presentation of familiar environments in VR did in fact promote feelings of nostalgia and reported moments of reminiscence. Future work opportunities call for more studies with PLWD, multi-modal & multi-channel stress sensing and concurrent parameter modulation.
Technology improvements such as integrating all peripherals into a standalone system as well as utilising more convenient and ergonomic sensors that could be applied semi-permanently to form a more holistic data overview for PLWD outside experimental conditions.
The Use Of Smart Glasses In The Elderly Wound Care
A research project and design proposal on the contribution of Smart Glasses to the elderly wound care
With an ageing society and fewer people willing to work in healthcare, the pressure on the healthcare sector is growing. And next to that, the high workload increased even more with the COVID-19 pandemic. Next to these factors increase, caregivers need to make numerous decisions each day, is their work emotionally demanding and though to be done. When continuing to work in this way, the quality of care provision will decrease. Therefore technical solutions, like Smart Glasses, can be a way to reduce these high pressures and maintain or even improve the quality of care.
The company 1Minuut already offers an option with Smart Glasses to make knowledge easily, safely and everywhere available to the care provider. Two different Smart Glasses, the VuzixM400 and Google Enterprise 2, and their software Genzõ are already used in several elderly care organisations. Smart Glasses are mainly used to let an expert, like a wound specialist, remotely watch clients from another location. A nurse wears the Smart Glasses, and when video calling with the device, the expert can remotely watch along.
This project focused on two parts. First, the current use and experiences of Smart
Glasses (mainly of 1Minuut) are explored and researched. The second part of the research consisted of developing a design proposal of how Smart Glasses can contribute to supporting caregivers in elderly wound care.
The first part started with explorative activities in the context of Smart Glasses. A better understanding was created of how the Smart Glasses and Genzõ of 1Minuut are
working, are used, and by whom. Then literature research was performed to obtain more information on the experiences of other Smart Glasses users and researchers.
Furthermore, two questionnaires and interviews were conducted by seven participants (clients of 1Minuut) who had all experiences with using Smart Glasses in the actual context of elderly care. A content analysis method was used to analyse the interviews. The project also concentrated partly on what is happening in the elderly (wound) care sector. So when coming up with a proposed design, in the end, this design would contribute to something that can improve or make the work of the elderly care staff easier.
The main results of the study were that Smart Glasses do offer many advantages,
especially for the person watching along and the clients. Less effort needs to be made when experts can see an elderly client remotely, and time will be saved. Nurses receive
expertise on distance and can act faster, which improves the provision of care for the
elderly.
However, Smart Glasses are not yet fully used. This is mainly because there are not yet that many opportunities with and features for the Smart Glasses. In addition, nurses do not yet experience what is really in it for them. Some, especially elderly nurses, find it challenging to control. In conclusion, it takes them more time than it benefits them. Therefore nurses do not use the Smart Glasses much and choose the old manner.
Furthermore, current users mainly use the Smart Glasses when a call is scheduled. They mention that good communication between the nurse and the expert at a distance is essential, as is the reason for use. Therefore an implementation plan is necessary.
The second part of the study focused on proposing a design for how Smart Glasses can support caregivers in elderly wound care. In a short 5-step design sprint, a reporting tool for the Smart Glasses was proposed. This feature helps nurses report wounds with the Smart Glasses by voice. Smart Glasses wearers will be guided through different steps of the report. Closed questions are presented about the wounds, and commonly used answers are shown, which can be selected by saying the answer out loud. There is always an option to add another answer or report at another moment. Reporting can happen now directly in the client’s room after the nurse has finished the tasks. When finished reporting, it will be automatically uploaded to the client’s information file. This makes reporting more accessible, faster and more consistent. ...
The company 1Minuut already offers an option with Smart Glasses to make knowledge easily, safely and everywhere available to the care provider. Two different Smart Glasses, the VuzixM400 and Google Enterprise 2, and their software Genzõ are already used in several elderly care organisations. Smart Glasses are mainly used to let an expert, like a wound specialist, remotely watch clients from another location. A nurse wears the Smart Glasses, and when video calling with the device, the expert can remotely watch along.
This project focused on two parts. First, the current use and experiences of Smart
Glasses (mainly of 1Minuut) are explored and researched. The second part of the research consisted of developing a design proposal of how Smart Glasses can contribute to supporting caregivers in elderly wound care.
The first part started with explorative activities in the context of Smart Glasses. A better understanding was created of how the Smart Glasses and Genzõ of 1Minuut are
working, are used, and by whom. Then literature research was performed to obtain more information on the experiences of other Smart Glasses users and researchers.
Furthermore, two questionnaires and interviews were conducted by seven participants (clients of 1Minuut) who had all experiences with using Smart Glasses in the actual context of elderly care. A content analysis method was used to analyse the interviews. The project also concentrated partly on what is happening in the elderly (wound) care sector. So when coming up with a proposed design, in the end, this design would contribute to something that can improve or make the work of the elderly care staff easier.
The main results of the study were that Smart Glasses do offer many advantages,
especially for the person watching along and the clients. Less effort needs to be made when experts can see an elderly client remotely, and time will be saved. Nurses receive
expertise on distance and can act faster, which improves the provision of care for the
elderly.
However, Smart Glasses are not yet fully used. This is mainly because there are not yet that many opportunities with and features for the Smart Glasses. In addition, nurses do not yet experience what is really in it for them. Some, especially elderly nurses, find it challenging to control. In conclusion, it takes them more time than it benefits them. Therefore nurses do not use the Smart Glasses much and choose the old manner.
Furthermore, current users mainly use the Smart Glasses when a call is scheduled. They mention that good communication between the nurse and the expert at a distance is essential, as is the reason for use. Therefore an implementation plan is necessary.
The second part of the study focused on proposing a design for how Smart Glasses can support caregivers in elderly wound care. In a short 5-step design sprint, a reporting tool for the Smart Glasses was proposed. This feature helps nurses report wounds with the Smart Glasses by voice. Smart Glasses wearers will be guided through different steps of the report. Closed questions are presented about the wounds, and commonly used answers are shown, which can be selected by saying the answer out loud. There is always an option to add another answer or report at another moment. Reporting can happen now directly in the client’s room after the nurse has finished the tasks. When finished reporting, it will be automatically uploaded to the client’s information file. This makes reporting more accessible, faster and more consistent. ...
With an ageing society and fewer people willing to work in healthcare, the pressure on the healthcare sector is growing. And next to that, the high workload increased even more with the COVID-19 pandemic. Next to these factors increase, caregivers need to make numerous decisions each day, is their work emotionally demanding and though to be done. When continuing to work in this way, the quality of care provision will decrease. Therefore technical solutions, like Smart Glasses, can be a way to reduce these high pressures and maintain or even improve the quality of care.
The company 1Minuut already offers an option with Smart Glasses to make knowledge easily, safely and everywhere available to the care provider. Two different Smart Glasses, the VuzixM400 and Google Enterprise 2, and their software Genzõ are already used in several elderly care organisations. Smart Glasses are mainly used to let an expert, like a wound specialist, remotely watch clients from another location. A nurse wears the Smart Glasses, and when video calling with the device, the expert can remotely watch along.
This project focused on two parts. First, the current use and experiences of Smart
Glasses (mainly of 1Minuut) are explored and researched. The second part of the research consisted of developing a design proposal of how Smart Glasses can contribute to supporting caregivers in elderly wound care.
The first part started with explorative activities in the context of Smart Glasses. A better understanding was created of how the Smart Glasses and Genzõ of 1Minuut are
working, are used, and by whom. Then literature research was performed to obtain more information on the experiences of other Smart Glasses users and researchers.
Furthermore, two questionnaires and interviews were conducted by seven participants (clients of 1Minuut) who had all experiences with using Smart Glasses in the actual context of elderly care. A content analysis method was used to analyse the interviews. The project also concentrated partly on what is happening in the elderly (wound) care sector. So when coming up with a proposed design, in the end, this design would contribute to something that can improve or make the work of the elderly care staff easier.
The main results of the study were that Smart Glasses do offer many advantages,
especially for the person watching along and the clients. Less effort needs to be made when experts can see an elderly client remotely, and time will be saved. Nurses receive
expertise on distance and can act faster, which improves the provision of care for the
elderly.
However, Smart Glasses are not yet fully used. This is mainly because there are not yet that many opportunities with and features for the Smart Glasses. In addition, nurses do not yet experience what is really in it for them. Some, especially elderly nurses, find it challenging to control. In conclusion, it takes them more time than it benefits them. Therefore nurses do not use the Smart Glasses much and choose the old manner.
Furthermore, current users mainly use the Smart Glasses when a call is scheduled. They mention that good communication between the nurse and the expert at a distance is essential, as is the reason for use. Therefore an implementation plan is necessary.
The second part of the study focused on proposing a design for how Smart Glasses can support caregivers in elderly wound care. In a short 5-step design sprint, a reporting tool for the Smart Glasses was proposed. This feature helps nurses report wounds with the Smart Glasses by voice. Smart Glasses wearers will be guided through different steps of the report. Closed questions are presented about the wounds, and commonly used answers are shown, which can be selected by saying the answer out loud. There is always an option to add another answer or report at another moment. Reporting can happen now directly in the client’s room after the nurse has finished the tasks. When finished reporting, it will be automatically uploaded to the client’s information file. This makes reporting more accessible, faster and more consistent.
The company 1Minuut already offers an option with Smart Glasses to make knowledge easily, safely and everywhere available to the care provider. Two different Smart Glasses, the VuzixM400 and Google Enterprise 2, and their software Genzõ are already used in several elderly care organisations. Smart Glasses are mainly used to let an expert, like a wound specialist, remotely watch clients from another location. A nurse wears the Smart Glasses, and when video calling with the device, the expert can remotely watch along.
This project focused on two parts. First, the current use and experiences of Smart
Glasses (mainly of 1Minuut) are explored and researched. The second part of the research consisted of developing a design proposal of how Smart Glasses can contribute to supporting caregivers in elderly wound care.
The first part started with explorative activities in the context of Smart Glasses. A better understanding was created of how the Smart Glasses and Genzõ of 1Minuut are
working, are used, and by whom. Then literature research was performed to obtain more information on the experiences of other Smart Glasses users and researchers.
Furthermore, two questionnaires and interviews were conducted by seven participants (clients of 1Minuut) who had all experiences with using Smart Glasses in the actual context of elderly care. A content analysis method was used to analyse the interviews. The project also concentrated partly on what is happening in the elderly (wound) care sector. So when coming up with a proposed design, in the end, this design would contribute to something that can improve or make the work of the elderly care staff easier.
The main results of the study were that Smart Glasses do offer many advantages,
especially for the person watching along and the clients. Less effort needs to be made when experts can see an elderly client remotely, and time will be saved. Nurses receive
expertise on distance and can act faster, which improves the provision of care for the
elderly.
However, Smart Glasses are not yet fully used. This is mainly because there are not yet that many opportunities with and features for the Smart Glasses. In addition, nurses do not yet experience what is really in it for them. Some, especially elderly nurses, find it challenging to control. In conclusion, it takes them more time than it benefits them. Therefore nurses do not use the Smart Glasses much and choose the old manner.
Furthermore, current users mainly use the Smart Glasses when a call is scheduled. They mention that good communication between the nurse and the expert at a distance is essential, as is the reason for use. Therefore an implementation plan is necessary.
The second part of the study focused on proposing a design for how Smart Glasses can support caregivers in elderly wound care. In a short 5-step design sprint, a reporting tool for the Smart Glasses was proposed. This feature helps nurses report wounds with the Smart Glasses by voice. Smart Glasses wearers will be guided through different steps of the report. Closed questions are presented about the wounds, and commonly used answers are shown, which can be selected by saying the answer out loud. There is always an option to add another answer or report at another moment. Reporting can happen now directly in the client’s room after the nurse has finished the tasks. When finished reporting, it will be automatically uploaded to the client’s information file. This makes reporting more accessible, faster and more consistent.
This thesis project aims at improving inventory management and awareness of craftsmen in their light commercial vehicles, specifically in the trunk area. The term commercial vehicle is used to identify a vehicle which main purpose is to transport goods or materials. The light commercial vehicle market, comprising vans and trucks, in Europe is growing rapidly every year and craftsmen are one of the important customers of them. They see their vans as trustworthy colleagues that help them to bring their materials everywhere. However the current state of their vans with different storage solutions do not contribute for solving the issues that they face during intense work days. Those built storage solutions are only focusing on providing space for carried materials and does not contribute to craftsmen’s work performance in any way. In fact this approach reveals major user and context related issues that downgrades the productivity due to the lack of practicality. This status quo is questioned and a smarter solutions to improve inventory awareness and accessibility developed with this graduation thesis. The particular topic is analysed with a human-centric approach. Interviews were conducted with multiple craftsmen to define the problems that they face with, understand their actual needs and observe their van’s trunk area with carried materials. Deficiency in inventory management which is a symptom of several major difficulties faced within the trunk, results as disruptions to the workflow. Having a low-stock of a certain material, travelling additionally to the supplier to cover the deficiency and physically effortful routine controls for the inventory are some of the aspects that causes the disruptions and impracticalities.
The project’s outcome is a product and service design that offers automated control system dedicated for consumables which are small sized materials with high frequency of use. Screws, bolts, fasteners, elbows are some of them that are always carried in the trunk area. The concept utilises accessible sensor technologies integrated to a tangible unit in order to provide momentarily and accurate informations regarding the state of consumables. It enables the connectivity between the inventory, the van and the craftsman by enabling continuous monitoring. The flexibility of the system results as an adaptation to craftsman’s way of work by offering personal settings and configuration in order to be able to procure relevant and suggestive feedbacks, to ultimately improve their inventory management and work efficiency. ...
The project’s outcome is a product and service design that offers automated control system dedicated for consumables which are small sized materials with high frequency of use. Screws, bolts, fasteners, elbows are some of them that are always carried in the trunk area. The concept utilises accessible sensor technologies integrated to a tangible unit in order to provide momentarily and accurate informations regarding the state of consumables. It enables the connectivity between the inventory, the van and the craftsman by enabling continuous monitoring. The flexibility of the system results as an adaptation to craftsman’s way of work by offering personal settings and configuration in order to be able to procure relevant and suggestive feedbacks, to ultimately improve their inventory management and work efficiency. ...
This thesis project aims at improving inventory management and awareness of craftsmen in their light commercial vehicles, specifically in the trunk area. The term commercial vehicle is used to identify a vehicle which main purpose is to transport goods or materials. The light commercial vehicle market, comprising vans and trucks, in Europe is growing rapidly every year and craftsmen are one of the important customers of them. They see their vans as trustworthy colleagues that help them to bring their materials everywhere. However the current state of their vans with different storage solutions do not contribute for solving the issues that they face during intense work days. Those built storage solutions are only focusing on providing space for carried materials and does not contribute to craftsmen’s work performance in any way. In fact this approach reveals major user and context related issues that downgrades the productivity due to the lack of practicality. This status quo is questioned and a smarter solutions to improve inventory awareness and accessibility developed with this graduation thesis. The particular topic is analysed with a human-centric approach. Interviews were conducted with multiple craftsmen to define the problems that they face with, understand their actual needs and observe their van’s trunk area with carried materials. Deficiency in inventory management which is a symptom of several major difficulties faced within the trunk, results as disruptions to the workflow. Having a low-stock of a certain material, travelling additionally to the supplier to cover the deficiency and physically effortful routine controls for the inventory are some of the aspects that causes the disruptions and impracticalities.
The project’s outcome is a product and service design that offers automated control system dedicated for consumables which are small sized materials with high frequency of use. Screws, bolts, fasteners, elbows are some of them that are always carried in the trunk area. The concept utilises accessible sensor technologies integrated to a tangible unit in order to provide momentarily and accurate informations regarding the state of consumables. It enables the connectivity between the inventory, the van and the craftsman by enabling continuous monitoring. The flexibility of the system results as an adaptation to craftsman’s way of work by offering personal settings and configuration in order to be able to procure relevant and suggestive feedbacks, to ultimately improve their inventory management and work efficiency.
The project’s outcome is a product and service design that offers automated control system dedicated for consumables which are small sized materials with high frequency of use. Screws, bolts, fasteners, elbows are some of them that are always carried in the trunk area. The concept utilises accessible sensor technologies integrated to a tangible unit in order to provide momentarily and accurate informations regarding the state of consumables. It enables the connectivity between the inventory, the van and the craftsman by enabling continuous monitoring. The flexibility of the system results as an adaptation to craftsman’s way of work by offering personal settings and configuration in order to be able to procure relevant and suggestive feedbacks, to ultimately improve their inventory management and work efficiency.