Sensor Network

Sensor networks comprise spatially distributed devices that collaboratively collect and process data, aiming to achieve efficient and reliable information gathering for various applications. Current research emphasizes developing robust and efficient algorithms for distributed data processing and inference under communication and resource constraints, employing techniques like Gaussian processes, variational inference, and deep learning architectures (e.g., graph neural networks, autoencoders). These advancements are crucial for improving the accuracy, reliability, and scalability of sensor networks across diverse fields, including environmental monitoring, autonomous systems, and industrial control.