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UNIVERSITY OF BUCHAREST
FACULTY OF PHYSICS Guest
2025-08-21 0:34 |
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Conference: Bucharest University Faculty of Physics 2025 Meeting
Section: Physics and Technology of Renewable and Alternative Energy Sources
Title:
Integrating Microbial Fuel Cells with Artificial Intelligence for Advanced Environmental Monitoring
Authors:
Matei-Tom IACOB(1,2),Bogdan Ciprian MITREA(1,2), Cornelia DIAC(1,2)
Affiliation:
1) University of Bucharest, Faculty of Physics, 3Nano-SAE, Research Centre, Măgurele,PO Box MG 38, 077125, Romania
2) University of Bucharest, Faculty of Physics, Măgurele, PO Box MG 38, 077125 Romania
E-mail
tom.iacob@3nanosae.org
Keywords:
Microbial Fuel Cells, Artificial Intelligence, Environmental Monitoring, Machine Learning, Neural Networks, Bio-sensors
Abstract:
Microbial Fuel Cells (MFCs) represent a technology suitable for environmental monitoring, leveraging the metabolic activity of microorganisms to generate electricity from organic matter. This electric behavior can be used not only for energy production but also as a means to sense and monitor environmental conditions in real-time. This study propose combining MFCs with Artificial Intelligence (AI) to create a monitoring system capable of detecting and analyzing environmental data. MFCs can be deployed in various ecosystems such as: soil, wastewater, and aquatic environments and capture electrochemical signals that can correlate with key environmental parameters, including organic matter concentration, pH levels, heavy metal presence, and biochemical oxygen demand (BOD). Microorganisms detectable signals could provide insights into environment health. By using AI, particularly machine learning algorithms, we aim to identify patterns, predict environmental changes, and detect anomalies such as the presence of contaminants or microbial altered activity. Current research is focused towards optimizing MFC designs to ensure consistent and reliable signal generation across diverse and dynamic environmental conditions. This approach seeks to develop a scalable, eco-friendly monitoring platform that can be applied to water quality management, soil health evaluation, and pollution control. This research underscores the potential of combining biological systems with computational intelligence to address environmental challenges.
References:
Kumar, S.S. et al. (2019) ‘Microbial fuel cells as a sustainable platform technology for Bioenergy, Biosensing, environmental monitoring, and other low power device applications’, Fuel, 255, p. 115682. doi:10.1016/j.fuel.2019.115682.
Liu, C., Cheng, L. and Jia, H. (2024) ‘Application of microbial fuel cell‐based biosensor in Environmental Monitoring – A Critical Review’, Electroanalysis, 36(10). doi:10.1002/elan.202400100.
Tsompanas MA, You J, Philamore H, Rossiter J, Ieropoulos I. Neural Networks Predicting Microbial Fuel Cells Output for Soft Robotics Applications. Front Robot AI. 2021 Mar 4;8:633414. doi: 10.3389/frobt.2021.633414. PMID: 33748191; PMCID: PMC7969642.
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