AN ENERGY-EFFICIENT IOT SENSOR NETWORK FRAMEWORK USING INTELLIGENT ENERGY HARVESTING AND ADAPTIVE ROUTING
AUTHORS:
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P Kavitha
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Department Of ECE, SVS Group of Institutions, Hanmakonda, Telangana
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Abstract
The rapid growth of Internet of Things (IoT) applications has led to the deployment of large-scale sensor networks in smart cities, healthcare, agriculture, industrial automation, and environmental monitoring systems. However, the limited battery capacity of sensor nodes remains a major challenge affecting network lifetime and reliability. Frequent battery replacement increases maintenance costs and limits scalability, particularly in remote and inaccessible locations. This paper proposes an Energy-Efficient IoT Sensor Network Framework that integrates intelligent energy harvesting techniques, adaptive sleep scheduling, edge computing, and Artificial Intelligence (AI)-based routing algorithms to optimize power consumption and extend network longevity. The proposed system continuously monitors residual node energy, communication quality, and environmental conditions to dynamically select optimal routing paths and operational states. Machine learning algorithms predict energy consumption patterns and network traffic conditions, enabling proactive resource management. Experimental analysis demonstrates significant improvements in network lifetime, packet delivery ratio, energy utilization efficiency, and communication reliability compared to conventional routing approaches. The proposed framework offers a sustainable and scalable solution for next-generation IoT sensor networks operating in energy-constrained environments.
Keywords
Internet of Things Energy Efficiency Wireless Sensor Networks Energy Harvesting AI-Based Routing Edge Computing Smart Environment Sustainable IoT.
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PUBLICATION DETAILS
Review Type:
Double-Blind Peer Review
License:
CC BY-NC 4.0
Volume/Issue:
Volume 02, Issue 7
Review Rounds:
2
Article Type:
Research Article
Publication Date:
Jul 10 2026
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Vijaya, H. & Ganapathi, D. (2026). An Energy-Efficient IoT Sensor Network Framework Using Intelligent Energy Harvesting and Adaptive Routing. International Journal of Science, Strategic Management and Technology, 02(7). https://doi.org/10.55041/ijsmt.v2i7.025
Vijaya, Halavath, and Dabbeta Ganapathi. "An Energy-Efficient IoT Sensor Network Framework Using Intelligent Energy Harvesting and Adaptive Routing." International Journal of Science, Strategic Management and Technology, vol. 02, no. 7, 2026, pp. . doi:https://doi.org/10.55041/ijsmt.v2i7.025.
Vijaya, Halavath, and Dabbeta Ganapathi. "An Energy-Efficient IoT Sensor Network Framework Using Intelligent Energy Harvesting and Adaptive Routing." International Journal of Science, Strategic Management and Technology 02, no. 7 (2026). https://doi.org/https://doi.org/10.55041/ijsmt.v2i7.025.
References
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[2] S. Lindsey and C. S. Raghavendra, “PEGASIS: Power-Efficient Gathering in Sensor Information Systems,” IEEE Aerospace Conference, vol. 3, pp. 1125–1130, 2002.
[3] I. F. Akyildiz, W. Su, Y. Sankarasubramaniam, and E. Cayirci, “Wireless Sensor Networks: A Survey,” Computer Networks, vol. 38, no. 4, pp. 393–422, 2002.
[4] K. Akkaya and M. Younis, “A Survey on Routing Protocols for Wireless Sensor Networks,” Ad Hoc Networks, vol. 3, no. 3, pp. 325–349, 2005.
[5] J. Yick, B. Mukherjee, and D. Ghosal, “Wireless Sensor Network Survey,” Computer Networks, vol. 52, no. 12, pp. 2292–2330, 2008.
[6] A. S. Weddell and N. M. White, “Energy Harvesting for Autonomous Sensor Systems,” Artech House, 2010.
[7] M. Chen, Y. Hao, K. Hwang, L. Wang, and L. Wang, “Disease Prediction by Machine Learning Over Big Data From Healthcare Communities,” IEEE Access, vol. 5, pp. 8869–8879, 2017.
[8] X. Sun, J. Wan, and M. Imran, “Machine Learning-Based Energy Optimization in IoT Sensor Networks,” IEEE Internet of Things Journal, vol. 8, no. 9, pp. 7232–7245, 2021.
[9] H. Gupta, A. Vahid Dastjerdi, S. K. Ghosh, and R. Buyya, “Edge Computing in IoT Networks: Architecture and Energy Optimization,” Future Generation Computer Systems, vol. 123, pp. 1–14, 2021.
[10] Y. Li and Z. Wang, “AI-Driven Energy Management for Sustainable IoT Systems,” Sensors, vol. 23, no. 6, pp. 3125–3142, 2023.
[2] S. Lindsey and C. S. Raghavendra, “PEGASIS: Power-Efficient Gathering in Sensor Information Systems,” IEEE Aerospace Conference, vol. 3, pp. 1125–1130, 2002.
[3] I. F. Akyildiz, W. Su, Y. Sankarasubramaniam, and E. Cayirci, “Wireless Sensor Networks: A Survey,” Computer Networks, vol. 38, no. 4, pp. 393–422, 2002.
[4] K. Akkaya and M. Younis, “A Survey on Routing Protocols for Wireless Sensor Networks,” Ad Hoc Networks, vol. 3, no. 3, pp. 325–349, 2005.
[5] J. Yick, B. Mukherjee, and D. Ghosal, “Wireless Sensor Network Survey,” Computer Networks, vol. 52, no. 12, pp. 2292–2330, 2008.
[6] A. S. Weddell and N. M. White, “Energy Harvesting for Autonomous Sensor Systems,” Artech House, 2010.
[7] M. Chen, Y. Hao, K. Hwang, L. Wang, and L. Wang, “Disease Prediction by Machine Learning Over Big Data From Healthcare Communities,” IEEE Access, vol. 5, pp. 8869–8879, 2017.
[8] X. Sun, J. Wan, and M. Imran, “Machine Learning-Based Energy Optimization in IoT Sensor Networks,” IEEE Internet of Things Journal, vol. 8, no. 9, pp. 7232–7245, 2021.
[9] H. Gupta, A. Vahid Dastjerdi, S. K. Ghosh, and R. Buyya, “Edge Computing in IoT Networks: Architecture and Energy Optimization,” Future Generation Computer Systems, vol. 123, pp. 1–14, 2021.
[10] Y. Li and Z. Wang, “AI-Driven Energy Management for Sustainable IoT Systems,” Sensors, vol. 23, no. 6, pp. 3125–3142, 2023.
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