Microbial fuel cell (MFC)-based biosensors have emerged as promising self-powered platforms for real-time monitoring by integrating bioelectrochemical sensing with sustainable energy generation. This review provides a comprehensive overview of next-generation MFC biosensors, highlighting recent advances in sensing mechanisms, system design, performance optimization, and intelligent integration. The fundamental principles of microbial electron transfer and bioelectrochemical signal generation are discussed, followed by strategies to enhance sensor performance through electrode engineering, biofilm optimization, and operational control. The integration of Internet of Things (IoT) technologies enables continuous, remote, and distributed monitoring, supporting the development of intelligent sensing networks for real-time data acquisition. Furthermore, the incorporation of artificial intelligence (AI) enhances signal processing, pattern recognition, predictive analytics, anomaly detection, and adaptive system control, significantly improving sensing accuracy and operational reliability. The synergistic convergence of self-powered sensing, IoT connectivity, and AI-driven analytics is further explored through emerging smart biosensing architectures capable of autonomous operation and decision-making. Key applications in environmental monitoring, industrial process control, wastewater management, food safety, and emerging biomedical diagnostics are comprehensively discussed. Current challenges, including limited power output, long-term stability, biofouling, selectivity, data security, and large-scale deployment, are critically examined. Finally, future research directions with machine learning-guided sensor design, and hybrid multimodal sensing platforms are presented to outline the pathway toward fully autonomous, sustainable, and intelligent biosensing systems. Finally, this review provides an integrated perspective on the evolution of MFC-based biosensors and highlights their significant potential to transform next-generation real-time monitoring technologies for environmental, industrial, and healthcare applications.
No takes yet. Share an insight, caveat, or question.
Thatikayala et al. (2026) studied this question.
Synapse has enriched 5 closely related papers on similar clinical questions. Consider them for comparative context: