Sensor Management

Sensor management focuses on optimizing the use of sensors to efficiently collect and process data, addressing challenges like data overload and limited resources. Current research emphasizes intelligent data selection and transmission, employing techniques like near-sensor machine learning and reinforcement learning algorithms such as Double Deep Q Networks, to improve efficiency and reduce computational costs. These advancements are crucial for applications ranging from robotics and the Internet of Things to space situational awareness, enabling more effective data acquisition and analysis in resource-constrained environments. Furthermore, research explores novel sensor architectures and the impact of sensor parameters on data quality, aiming to enhance control and understanding of sensor output.