International Journal For Multidisciplinary Research

E-ISSN: 2582-2160     Impact Factor: 9.24

A Widely Indexed Open Access Peer Reviewed Multidisciplinary Bi-monthly Scholarly International Journal

Call for Paper Volume 8, Issue 2 (March-April 2026) Submit your research before last 3 days of April to publish your research paper in the issue of March-April.

Smart Robot for Detection and Diffusion of Explosives and Hazardous Gas Sensing

Author(s) Ms. Vaishnavi Devi, Ms. Yogitha Kovalan
Country India
Abstract This study describes the development of an intelligent robotic system designed to detect and neutralize explosive threats while enabling remote monitoring and automated hazard analysis. The proposed system combines embedded hardware components with machine learning techniques to improve operational safety in high-risk environments. The robotic platform integrates multiple functional units, including a toxic gas sensor for monitoring harmful atmospheric conditions, a GPS module for accurate location identification, and an RF-based communication system that allows wireless control from a safe distance. An onboard buzzer provides instant alerts whenever a threat is detected. For physical handling of suspected explosive objects, a mechanically controlled robotic gripper is incorporated to ensure careful and secure manipulation. Visual surveillance is achieved using an ESP32-CAM module, which streams live video to the operator. The captured images are processed using a custom-trained machine learning model capable of identifying weapons or suspicious objects in real time. In addition, a gas classification model developed in Python is integrated with a cloud-based platform to analyze environmental readings. The system categorizes detected gases into three levels—safe, warning, and dangerous—and presents the results through graphical visualization for easier interpretation. Whenever a potential threat is identified, automated email notifications are generated, including the exact GPS coordinates and the corresponding risk level. By combining real-time sensing, intelligent classification, and remote accessibility, the proposed semi-autonomous robotic solution enhances operational safety and is particularly suitable for military operations, disaster management scenarios, and hazardous area surveillance.
Keywords Explosive detection, toxic gas sensing, ESP32- CAM, RF control, GPS alert system, robotic gripper, machine learning, Cloud platform, Remote Surveillance.
Field Engineering
Published In Volume 8, Issue 2, March-April 2026
Published On 2026-03-16

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