Engineering Living Biosensors: Integrating Bio-Computing Principles for Sustainable Environmental Monitoring

Abstract

Industrial and agricultural pollutants contribute a significant role in global environmental degradation. Traditional detection technologies often face high cost , non-biodegradable, and energy - intensive .  This study explores the development of living biosensors that utilise bio-computing principles for eco-friendly pollutant detection that is aligning with the goal of green chemistry and sustainable development to a greater extent .
The objective talks about a conceptual framework for microbial biosensors capable of performing complex biology computation to detect heavy metals and other organic toxins through gene circuit logic . Engineered microbial strains were modelled with synthetic promoters that triggers a visible response much like green fluorescence and colour change detections . The mechanism replicates digital computation within a biological context , enabling real-time , self-sustaining detection without heavy electronic components .

The proposed model demonstrates that bio-computing can be a game changer in the detection of unknown pollutants in more efficient ways , as they are biodegradable , self- replicating , and low-energy alternatives to traditional chemical and electronic detectors. They offer a scalable with addition of sustainable solution for environmental monitoring and industrial waste management