The usefulness of artificial intelligence for safety assessment of different transport modes

Recent research in transport safety focuses on the processing of large amounts of available data by means of intelligent systems, in order to decrease the number of accidents for transportation users. Several Machine Learning (ML) and Artificial Intelligence (AI) applications have been developed to address safety problems and improve efficiency...

Learning Technologies & AI: Who are we designing for?

Focused on children and the learning context, we argue for the importance of designing artificial intelligence (AI) technologies that take a holistic view of their target users. Rather than prioritize system performance, these smart technologies can be tuned to assist users throughout the task completion process. We argue that considering...

Driver Profile and Driving Pattern Recognition for Road Safety Assessment: Main Challenges and Future Directions

This study reviews the Artificial Intelligence and Machine Learning approaches developed thus far for driver profile and driving pattern recognition, representing a set of macroscopic and microscopic behaviors respectively, to enhance the understanding of human factors in road safety, and therefore reduce the number of crashes. It provides a...

Attack Graph Model for Cyber-Physical Power Systems Using Hybrid Deep Learning

Electrical power grids are vulnerable to cyber attacks, as seen in Ukraine in 2015 and 2016. However, existing attack detection methods are limited. Most of them are based on power system measurement anomalies that occur when an attack is successfully executed at the later stages of the cyber kill chain. In contrast, the attacks on the Ukrainian...

Trustworthy AI Governance - Panel Discussion

As AI technology becomes more powerful, the impact on governance and the governance of AI becomes more important. The purpose of this panel is to bring together experts on Trustworthy AI and E-Governance to discuss the lessons learned so far and the challenges ahead. The goal is to provide a comprehensive review of challenges and potential...

Bio-Cyber-Physical ‘Planetoids’ for Repopulating Residual Spaces

Minimal interventions that provide various microclimates can stimulate both biodiversity and social accessibility of leftover spaces. New habitats are often developed for different animal and plant species based on studies of the microclimates typical of such residual spaces. By introducing interventions of 0.5-1.0 m diameter ‘planetoids’ placed...

Obstacle Avoidance and Trajectory Optimization for an Autonomous Vessel Utilizing MILP Path Planning, Computer Vision based Perception and Feedback Control

The framework of an autonomous vessel is typically composed of three distinct and independent blocks known as the Guidance, Navigation and Control (GNC) system. Whilst independent in their focus, the subsystems are nonetheless reliant on one another for a vessel to competently operate. This paper investigates the potential of using a combination...

Artificial Intelligence Based Short-Term Motions Forecasting for Autonomous Marine Vehicles Control

The development of fast and accurate intelligent vessel control systems is a necessary milestone on the path toward operating autonomous marine vehicles effectively in harsh environments and complex mission settings. One of the main problems of existing control systems is the disparity between the forecasted behaviour and how the vessel actually...

Computer Says I Don’t Know: An Empirical Approach to Capture Moral Uncertainty in Artificial Intelligence

As AI Systems become increasingly autonomous, they are expected to engage in decision-making processes that have moral implications. In this research we integrate theoretical and empirical lines of thought to address the matters of moral reasoning and moral uncertainty in AI Systems. We reconceptualize the metanormative framework for decision...

Technology and More-Than-Human Design

Are we reaching the limits of what human-centered and user-centered design can cope with? Developing new design methodologies and tools to unlock the potentials of data technologies such as the Internet of Things, Machine Learning and Artificial Intelligence for the everyday job of design is necessary but not sufficient. There is now a need to...

Ambient UX for Cyber-Physical Spaces

Ambient User Experience (Ambient UX) is a conceptual framework providing a strategy for design processes that target cyber-physical spaces. Such design processes interface Wireless Sensor-Actuator Networks (WSAN), Artificial Intelligence (AI), and physically built environments. For managing the complexity of such design processes and ensuring...

Automatic modular design of robot swarms using behavior trees as a control architecture

We investigate the possibilities, challenges, and limitations that arise from the use of behavior trees in the context of the automatic modular design of collective behaviors in swarm robotics. To do so, we introduce Maple, an automatic design method that combines predefined modules—low-level behaviors and conditions— into a behavior tree that...

Data governance: Organizing data for trustworthy Artificial Intelligence

The rise of Big, Open and Linked Data (BOLD) enables Big Data Algorithmic Systems (BDAS) which are often based on machine learning, neural networks and other forms of Artificial Intelligence (AI). As such systems are increasingly requested to make decisions that are consequential to individuals, communities and society at large, their...

Developing a Cyber Operations Computational Ontology

Cyber operations lack models, methodologies, and mechanisms to describe relevant data and knowledge. This problem is directly reflected when cyber operations are conducted and their effects assessed, and it can produce dissonance and disturbance in corresponding decision-making processes and communication between different military actors. To...