Microbial fuel cell–based self‐powered biosensor for environment monitoring in IoT cloud framework
K. Saravanakumar, R. Rajeswari
AI summary
70% confidenceA microbial fuel cell-based self-powered biosensor is proposed for environment monitoring in an IoT cloud framework, utilizing Oryza Sativa plants with bacteria as catalysts to extract energy.
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- MFC
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Abstract
Summary Renewable energy sources are useful for sustainable monitoring, but still very limited today due to various implementation constraints. Microbial fuel cells (MFCs) are considered a promising renewable power source for remote monitoring applications. They are used as wireless temperature sensors and biosensors due to their ability in powering environmental sensors. MFCs can provide ultralow and dynamic power, and hence, energy improvement is crucial for self‐powered biosensors. Cloud computing–based IoT framework is proposed for environment monitoring using MFC‐based biosensors. This paper presents the electric energy harvesting from Oryza Sativa plants with bacteria as the catalyst. It adopts the technology of MFC in the plants to extract the maximum energy. An effective power management with IoT cloud framework is presented in this work to independently operate multiple MFCs to generate maximum power. Independently operated MFCs with electrically isolated electrodes have been utilized in the design of a suitable power management system. Cloud computing is utilized in this work to process the data generated in continuous monitoring of environment. Experimental results show that the proposed framework can achieve sustainable power for sensor nodes and achieves maximum performance in environment monitoring using cloud‐based IoT platform.
Key findings
- MFCs can provide ultralow and dynamic power, making them suitable for remote monitoring applications.
- An effective power management system is presented to independently operate multiple MFCs and generate maximum power.
- Cloud computing is utilized to process data generated in continuous environmental monitoring.
Keywords
Identifiers
- Journal
- Concurrency and Computation: Practice and Experience
- Year
- 2019