Energy Harvesting Integrated Sensor Node Architecture for Sustainable IoT Networks

Gopikrishnan, S.; Kokila, M.; Rivera, Marco; Wheeler, Patrick

Abstract

Internet of Things (IoT) is a life changing technology which is build on various devices which are connected to the Internet. Wireless sensor nodes (WSN) is one of such devices which plays a major role in deploying IoT in large scale of real-time even monitoring applications. But the energy limitations of those sensor nodes limits the features of IoT networks. Hence improving the energy limitations in WSN plays a vital role in last decade. This chapter presents the possibilities of enhance the energy limitations of sensor nodes with renewable energy resources. The proposed integrated architecture of this proposed model discusses the implementation of sensor node with flexible solar energy harvester module, multi mode communication capability and multi sensor data module. The special contribution in this chapter includes the hardware specification with budget analysis, sleep-awake strategy to effective use of energy and maximum possible data collection from the environment. The novelty and improvement of the proposed model has been proved with mathematical model as well as the real-time measurements from the prototype.

Citation

Gopikrishnan, S., Kokila, M., Rivera, M., & Wheeler, P. (2024, January). Energy Harvesting Integrated Sensor Node Architecture for Sustainable IoT Networks. Presented at 5th International Conference on Advances in Distributed Computing and Machine Learning (ICADCML)-2024, VIT-AP University, India

• Presentation Conference Type: Edited Proceedings
• Conference Name: 5th International Conference on Advances in Distributed Computing and Machine Learning (ICADCML)-2024
• Start Date: Jan 5, 2024
• End Date: Jan 6, 2024
• Acceptance Date: Jan 1, 2024
• Online Publication Date: Aug 2, 2024
• Publication Date: Aug 3, 2024
• Deposit Date: Aug 26, 2024
• Print ISSN: 2367-3370
• Peer Reviewed: Peer Reviewed
• Pages: 57-70
• Series Title: Lecture Notes in Networks and Systems
• Series Number: 1015
• Series ISSN: 2367-3389
• Book Title: Advances in Distributed Computing and Machine Learning Proceedings of ICADCML 2024, Volume 2
• ISBN: 978-981-97-3522-8
• DOI: https://doi.org/10.1007/978-981-97-3523-5_5
• Public URL: https://nottingham-repository.worktribe.com/output/38649323
• Publisher URL: https://link.springer.com/chapter/10.1007/978-981-97-3523-5_5