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Indoor PM2.5 forecasting and the association with outdoor air pollution: a modelling study based on sensor data in Australia
Exposure to poor indoor air quality poses significant health risks, necessitating thorough assessment to mitigate associated dangers.
Predicting Next Useful Location With Context-Awareness: The State-Of-The-Art
Predicting the future location of mobile objects reinforces location-aware services with proactive intelligence and helps businesses and decision-makers with better planning and near real-time scheduling in different applications such as traffic congestion control, location-aware advertisements, and monitoring public health and well-being.
Energy-Efficient UAV-Assisted IoT Data Collection via TSP-Based Solution Space Reduction
This paper presents a wireless data collection framework that employs an unmanned aerial vehicle (UAV) to efficiently gather data from distributed IoT sensors deployed in a large area.
Deakin RF-Sensing: Experiments on Correlated Knowledge Distillation for Monitoring Human Postures with Radios
The proposed CKD framework transfers and fuses pose knowledge from a robust "Teacher" model to a parameterized "Student" model, which can be a promising technique for obtaining accurate yet lightweight pose estimates.
Poisoning Attacks and Defenses in Federated Learning: A Survey
Federated learning (FL) enables the training of models among distributed clients without compromising the privacy of training datasets, while the invisibility of clients datasets and the training process poses a variety of security threats.
Reinforcement Learning Based Approaches to Adaptive Context Caching in Distributed Context Management Systems
This paper proposes a reinforcement learning based approach to adaptively cache context with the objective of minimizing the cost incurred by context management systems in responding to context queries.
From Traditional Adaptive Data Caching to Adaptive Context Caching: A Survey
This paper presents a critical survey of the state-of-the-art in adaptive data caching with the objective of developing a body of knowledge in cost- and performance-efficient adaptive caching strategies.
Designed to Cooperate: A Kant-Inspired Ethic of Machine-to-Machine Cooperation
It is argued that being cooperative is not only important for their improved functioning, especially, when they use shared resources (e. g., parking spaces, public roads, curbside space and walkways), but also as a favourable requirement analogous to how humans cooperating with other humans can be advantageous and often viewed favourably.
Robot-Friendly Cities
Robots are increasingly tested in public spaces, towards a future where urban environments are not only for humans but for autonomous systems.
Cooperative Automated Vehicles: a Review of Opportunities and Challenges in Socially Intelligent Vehicles Beyond Networking
The connected automated vehicle has been often touted as a technology that will become pervasive in society in the near future.
