Opportunities for Applications Using 5G Networks: Requirements, Challenges, and Outlook

The increasing demand for mobile network capacity driven by Internet of Things (IoT) applications results in the need for understanding better the potential and limitations of 5G networks. Vertical application areas like smart mobility, energy networks, industrial IoT applications, and AR/VR enhanced services all pose different requirements on...

Ethical hacking for boosting IoT vulnerability management: A first look into bug bounty programs and responsible disclosure

The security of the Internet of Things (IoT) has attracted much attention due to the growing number of IoT-oriented security incidents. IoT hardware and software security vulnerabilities are exploited affecting many companies and persons. Since the causes of vulnerabilities go beyond pure technical measures, there is a pressing demand...

Will Algorithms Blind People? The Effect of Explainable AI and Decision-Makers’ Experience on AI-supported Decision-Making in Government

Computational artificial intelligence (AI) algorithms are increasingly used to support decision making by governments. Yet algorithms often remain opaque to the decision makers and devoid of clear explanations for the decisions made. In this study, we used an experimental approach to compare decision making in three situations: humans making...

Trustworthy and Sustainable Edge AI: A Research Agenda

As a fast evolving domain that merges edge computing, data analytics and AI/ML, commonly referred as Edge AI, the community of Edge AI is establishing and gradually finds its way to connect with mainstream research communities of distributed systems, IoT, and embedded machine learning. Meanwhile, despite of its well-claimed potential to...

Accountable AI for Healthcare IoT Systems

Various AI systems have taken a unique space in our daily lives, helping us in decision-making in critical as well as non-critical scenarios. Although these systems are widely adopted across different sectors, they have not been used to their full potential in critical domains such as the healthcare sector enabled by the Internet of Things (IoT)...

A Survey on Approximate Edge AI for Energy Efficient Autonomous Driving Services

Autonomous driving services depends on active sensing from modules such as camera, LiDAR, radar, and communication units. Traditionally, these modules process the sensed data on high-performance computing units inside the vehicle, which can deploy intelligent algorithms and AI models. The sensors mentioned above can produce large volumes of data...

Bias Detection and Generalization in AI Algorithms on Edge for Autonomous Driving

A machine learning model can often produce biased outputs for a familiar group or similar sets of classes during inference over an unknown dataset. The generalization of neural networks have been studied to resolve biases, which has also shown improvement in accuracy and performance metrics, such as precision and recall, and refining the dataset...