Multi-sensor data fusion is a research area that focuses on combining information from multiple sensors to improve the accuracy and reliability of the data being collected. This can include data from various types of sensors such as cameras, radar, lidar, and other sensors that capture different types of information. The goal of multi-sensor data fusion is to integrate and interpret data from different sources to provide a more comprehensive understanding of a situation or environment. By combining data from multiple sensors, researchers can improve the overall performance of systems such as surveillance, navigation, and monitoring applications. This field of research involves developing algorithms and techniques to effectively integrate and process data from multiple sensors, as well as addressing challenges such as data inconsistency, uncertainty, and sensor imperfections. Multi-sensor data fusion has applications in various fields including defense, autonomous systems, healthcare, and environmental monitoring.