Recent advances in machine learning inspire the development of deep neural network-based smart sensing applications for the Artificial Intelligence of Things (AIoT). However, due to the nature of the AIoT sensing data, the machine learning models are in ...

The autonomous space farming system could be used to grow self-pollinating crops in space exploration missions that require no human intervention. Our goal is to utilize hyper spectral imaging and traditional imaging to allow for machine learning models ...

Bio jet fuels derived from feedstock offer a sustainable alternative to meeting energy needs. Modeling supply chains that produce said fuels can lead to computationally prohibitive mixed integer linear programs (MILP) that consider optimal facility ...

Computer-Aided Dispatch (CAD) systems optimize the management of security incidents and facilitate the call for rescue. However, these systems are often heterogeneous and designed to meet the needs of a particular city or region in isolated ways, making ...

This paper introduces MegaFlow2D, a dataset of over 2 million snapshots of parameterized 2D fluid dynamics simulations of 3000 different external flow and internal flow configurations. It’s worth noting that, simulation results on both low and high mesh ...

Cyber-Physical Systems (CPS) require seamless integration of physical and computation components through communication networks. They often contain sub-systems from different physical domains (e.g., electrical, mechanical, and electronic) that must ...

Open-source software (OSS) is a critical element in the design and operation of complex cyber-physical systems. Contributions to OSS projects are typically the result of voluntary work and time allocation by researchers, software developers, hackers, and ...

Computer vision systems in sensor nodes of the Internet of Things (IoT) based on Deep Learning (DL) are demanding because the DL models are memory and computation hungry while the nodes often come with tight constraints on energy, latency, and memory. ...

The paper presents early work on LetSynchronise, an open-source framework that aims to facilitate research and collaboration on Logical Execution Time (LET) systems. It offers a web application for modelling, simulating, analysing, and optimising LET ...

Driver Behavior Modeling (DBM) aims to predict and model human driving behaviors, which is typically incorporated into the Advanced Driver Assistance System to enhance transportation safety and improve driving experience. Inverse reinforcement learning (...

Convenience is a strong driver for the evolution of technology. Such efforts have given rise to the Internet-of-Things (IoT), defined as the network of everyday devices (i.e., “things”) ranging from light bulbs to smart speakers, connected to the ...