Integration of Biosensors in Robotic Systems for Enhanced Environmental Monitoring

Year : 2024 | Volume : 11 | Issue : 03 | Page : 38 49
    By

    S. Anand,

  1. Professor, Department of Computer Science and Engineering, Infant Jesus College of Engineering, Kilavallanadu, Tamil Nadu, India

Abstract

Biosensors are analytical devices that use biological components, such as enzymes, antibodies, or nucleic acids, to detect specific chemical or biological substances. They have shown great potential in various fields, particularly in environmental monitoring, due to their sensitivity, specificity, and ability to provide real-time data. Integrating biosensors with robotic systems combines the strengths of both technologies, allowing for efficient data collection in remote, hard-to-reach, or hazardous environments. This integration enables continuous monitoring, minimizes human intervention, and improves the accuracy and reliability of data. This study explores the design and implementation of biosensors within robotic platforms, addressing key factors such as sensor calibration, data collection protocols, and real-time data processing. Applications in diverse environmental scenarios, including water quality analysis, air pollution detection, and soil contamination assessment, are examined. The findings highlight the enhanced capabilities of biosensors when used in conjunction with robotic systems, underscoring their potential to revolutionize environmental monitoring and pave the way for future innovations in automated, real-time ecological assessments.

Keywords: Biosensors, robotics, environmental monitoring, drones, real-time data collection

[This article belongs to Journal of Advancements in Robotics ]

How to cite this article:
S. Anand. Integration of Biosensors in Robotic Systems for Enhanced Environmental Monitoring. Journal of Advancements in Robotics. 2024; 11(03):38-49.
How to cite this URL:
S. Anand. Integration of Biosensors in Robotic Systems for Enhanced Environmental Monitoring. Journal of Advancements in Robotics. 2024; 11(03):38-49. Available from: https://journals.stmjournals.com/joarb/article=2024/view=180741


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Regular Issue Subscription Review Article
Volume 11
Issue 03
Received 23/10/2024
Accepted 25/10/2024
Published 04/11/2024
317

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