An Overview of Sensor Fusion and Data Analytics in WSNs

Wireless sensor networks (WSNs) have emerged as a powerful technology for a wide range of applications, including environmental monitoring, industrial automation, and healthcare. One of the key challenges in WSNs is effectively leveraging the vast amounts of data collected by the sensor nodes to extract meaningful insights and support informed decision-making. This research paper explores the concept of sensor fusion and data analytics in the context of wireless sensor networks. We discuss the benefits and challenges of integrating data from multiple sensors, and present various techniques and algorithms for fusing sensor data and conducting advanced analytics. The paper also examines the role of machine learning and artificial intelligence in enhancing the capabilities of sensor fusion and data analytics in WSNs. Finally, we provide a discussion of the practical considerations and future research directions in this field.