Enhancing Coverage and Efficiency in Wireless Sensor Networks: A Review of Optimization Techniques

Wireless Sensor Networks (WSNs) are vital for applications such as environmental monitoring, surveillance, and healthcare, where comprehensive network coverage is essential for accurate data collection. However, achieving full coverage in WSNs presents significant challenges due to resource constraints, such as limited battery life, processing capabilities, and environmental factors like terrain and obstacles. To address these issues, coverage optimization techniques are employed to maximize spatial coverage while minimizing energy consumption and deployment costs. This paper provides a thorough overview of these coverage optimization techniques, categorizing them based on different deployment strategies, including static and dynamic sensor placement. It explores their respective advantages, limitations, and application scenarios, offering valuable insights for researchers and practitioners. The study is motivated by the need to better understand how to improve WSN coverage efficiency and ensure reliable data collection in diverse environments. The research aims to synthesize existing knowledge on WSN coverage optimization, identify gaps in current strategies, and guide future studies in this field. Key findings emphasize the effectiveness of various techniques in enhancing coverage, such as mobility-based approaches and energy-aware algorithms, while also addressing practical challenges like sensor redundancy and environmental unpredictability. Ultimately, this paper contributes to the ongoing efforts to develop more adaptive, scalable, and energy-efficient solutions for WSN coverage optimization.