Harnessing Smart Biosensors for Detecting and Degrading Environmental Pollutants

The increasing presence of hazardous pollutants in air, water, and soil ecosystems has underscored the urgent need for advanced monitoring and remediation technologies. Smart biosensors-analytic devices that combine biological components with physicochemical detectors-offer a promising solution for real-time detection and even degradation of environmental contaminants. This paper explores recent innovations in biosensor technology, focusing on their dual function as both monitoring tools and active agents for pollutant breakdown. We review key categories of smart biosensors, including enzymatic, microbial, DNA-based, and cell-free system, and highlight how they are engineered to detect a wide range of pollutants such as heavy metals, pesticides, microplastics, and organic toxins. Particular attention is given to the integration of these biosensors with internet of thing (IoT) platforms, allowing remote data acquisition and cloud-based environmental diagnostics. Furthermore, emerging hybrid systems that combine biosensing with biodegradation mechanisms are evaluated for their potential in mitigating localized pollution in aquatic and terrestrial ecosystem. Through selected case studies and pilot projects, we demonstrate how smart biosensors are transforming traditional environmental surveillance by enabling early warning systems, adaptive management strategies, and cost-effective pollutant removal. The paper concludes by addressing current challenges-such as stability, selectivity, and environmental compatibility-and proposes a roadmap for future research, including scalable production methods and the incorporation of synthetic biology. Ultimately, smart biosensors represent a transformation approach to environmental protection, offering a convergence of biology, engineering, and data science to detect, understand, and neutralize pollution in a sustainable manner.

کلیدواژه ها:

Artificial Intelligence ، Biodegradation ، Environmental Monitoring