A Comprehensive Survey of Energy Harvesting Strategies for Wireless Sensor Networks: Methods, Challenges and Future Directions
Renewable energy technologies offer a sustainable and efficient solution to the power limitations of Wireless Sensor Networks (WSNs), enabling long-term operation across diverse applications. The comparative analysis in this study highlights that different energy harvesting mechanisms vary in efficiency, reliability, and suitability based on environmental conditions. Photovoltaic harvesting emerges as the most effective for outdoor environments, while electromechanical harvesting is well-suited for vibration-rich settings. RF energy harvesting, though cost-effective, has lower energy efficiency and is best utilized in combination with other methods. The radar chart underscores the importance of hybrid energy harvesting, integrating multiple sources to enhance power availability and stability. Despite advancements in energy harvesting techniques, integration strategies, and power management, challenges such as efficiency optimization, adaptability to dynamic environments, and smart energy allocation remain unresolved. Addressing these issues requires collaborative efforts among academia, industry, and policymakers to develop intelligent, hybrid energy harvesting systems for self-sustaining WSNs. Future research should focus on enhancing material efficiency, refining energy conversion techniques, and implementing adaptive power management strategies. Overcoming these challenges will pave the way for more resilient, autonomous, and sustainable wireless sensing and monitoring technologies.
Authors
- Vijay Kumar Garg (ORCID: https://orcid.org/0000-0001-9914-5266)
- Nikhil Marriwala (ORCID: https://orcid.org/0000-0002-1093-630X)
- Gautam Gupta (ORCID: https://orcid.org/0000-0001-7607-4055)
Institutions
- Kurukshetra University (IN)
Publication Details
- Published
- 2025-03-06
- DOI
- https://doi.org/10.1109/ispcc66872.2025.11039546
- Citations
- 1
- Primary Topic
- Energy Harvesting in Wireless Networks
- Type
- article
- Field-Weighted Citation Impact
- 0.73