IoT Sensor Network Powered by Sediment Microbial Fuel Cell

Niwa, Masato; Pan, Zhenni; Shimamoto, Shigeru

doi:10.1109/ccnc46108.2020.9045606

Cited by 4 publications

(1 citation statement)

References 14 publications

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“…MFC can operate at lower temperatures and can also be used to treat organic waste. A substrate is an important factor because it provides energy and a source of nutrients [94]. In MFCs, the ability of microorganisms to oxidize substrate present in the anodic chamber and transfer electrons is linked to current production; substrates influence the composition of the microorganism community in the anode electrode biofilm and performance parameters such as power density and Coulombic efficiency (CE) [95].…”

Section: Discussionmentioning

confidence: 99%

A Survey of Applications of MFC and Recent Progress of Artificial Intelligence and Machine Learning Techniques and Applications, with competing fuel cells

et al. 2022

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Tomorrow is a technology for Microbial fuel cells (MFC). It has attracted numerous studies for the continuous development of cell efficiency since the problem of the coming era can be resolved. Implementing artificial learning and machine learning is a change that can effectively achieve the goals. A microbial fuel cell constitutes a complex non-linear procedure that preferably needs a strategy that is not a linear control strategy for the most optimum result. Rather than making a computationally tedious and heavy non-linear control strategy, a superior single linear model or gain scheduling, or multiple models-based control techniques are the practical and feasible ways to tackle the non-linearity existing in the Microbial Fuel Cell. Machine learning and Artificial Intelligence help reduce computation and model costs. It saves time and is more efficient than previously used manual methods, which are now obsolete. In order to find the most accurate results, the study would compare all currently available research efforts and focus on implementing Artificial Intelligence and Machine learning concepts within the Microbial Fuel Cell and comparison with other fuel cells.

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Section: Discussionmentioning

confidence: 99%