CAPACITANCE BIOSENSORS FOR THE RAPID DETECTION OF ESCHERICHIA COLI IN WATER
Abstract
Ensuring the safety of drinking water and environmental water sources is a critical public health priority, with microbial contamination, particularly by fecal indicator bacteria like Escherichia coli (E. coli), posing significant risks. Traditional methods for detecting E. coli are often time-consuming, labor-intensive, and require specialized laboratory facilities, hindering rapid response to contamination events. This article explores the potential of capacitance biosensors as a rapid, label-free, and sensitive alternative for E. coli detection in water. The introduction highlights the importance of water quality monitoring and the limitations of current detection techniques. The methods section details the fundamental principles of impedance/capacitance microbiology and the design considerations for capacitance biosensors tailored for bacterial detection. The results synthesize current research demonstrating the efficacy of these biosensors in real-time monitoring of bacterial activity and specific pathogen identification. The discussion interprets the advantages and challenges of capacitance biosensors, emphasizing their potential for decentralized, on-site water quality assessment, and outlines future directions for research and development to achieve widespread adoption.
Keywords
References
Similar Articles
- Evan Richman, Advanced Evolutionary Optimization and Intelligent Sensor Integration for Electromagnetic Compatibility and Signal Integrity in Autonomous Vehicle Architectures , International Journal of Next-Generation Engineering and Technology: Vol. 3 No. 01 (2026): Volume 03 Issue 01
- Dr. Youssef El-Masry, Statistical Learning Driven Virtual Counterpart Systems Evaluating Healthcare Coverage Administration Analysis , International Journal of Next-Generation Engineering and Technology: Vol. 2 No. 10 (2025): Volume 02 Issue 10
- Simone Marquez-Rodriguez, Artificial Intelligence-Driven Predictive Risk Analytics and Automation in Construction Project Management: Integrating Machine Learning, Computer Vision, And Data Intelligence for Safer and More Efficient Infrastructure Development , International Journal of Next-Generation Engineering and Technology: Vol. 2 No. 12 (2025): Volume 02 Issue 12
- Valeria GonzΓ‘lez, AI-Augmented Neural Architecture for Remote Ledger Bookkeeping with Fraud Detection and Exposure Forecasting , International Journal of Next-Generation Engineering and Technology: Vol. 3 No. 04 (2026): Volume 03 Issue 04
- Prof. Claire Dubois, Remote computational finance analytics architecture deep learning enabled unlawful transaction screening exposure evaluation framework , International Journal of Next-Generation Engineering and Technology: Vol. 3 No. 04 (2026): Volume 03 Issue 04
- Dr. Aarav Mehta, Dr. Priya Nair, A Systematic Review of Scene Image Text Detection and Recognition: Advances in Deep Learning Models, Optimization Strategies, and Real-World Applications , International Journal of Next-Generation Engineering and Technology: Vol. 3 No. 08 (2026): Volume 03 Issue 08
- Arjun Sharma, Priya Verma, Graph Neural Network-Based Framework for Intelligent Cyber Threat Detection in Cloud Computing , International Journal of Next-Generation Engineering and Technology: Vol. 3 No. 08 (2026): Volume 03 Issue 08
- Dr. Elena Marovic, Human Exposure to Microplastics: Pathways, Internal Distribution, Analytical Detection, and Emerging Toxicological Implications , International Journal of Next-Generation Engineering and Technology: Vol. 2 No. 09 (2025): Volume 02 Issue 09
- Dr. Clara E. Whitmore, Artificial Intelligence for Resilient Decentralized Infrastructures: An Integrative Research Study on Hybrid Renewable Energy Management and Real-Time Digital Payment Fraud Detection , International Journal of Next-Generation Engineering and Technology: Vol. 3 No. 04 (2026): Volume 03 Issue 04
- Dr. Amira R. Hassan, Assessing Pakistan's Climatic Vulnerability: A Review of Evolving Impacts and Adaptive Strategies , International Journal of Next-Generation Engineering and Technology: Vol. 2 No. 10 (2025): Volume 02 Issue 10
You may also start an advanced similarity search for this article.