A Smart Robotic Design to Identify and Diffuse Bombs in Defence Environments Using Sensors Assisted Internet of Things (IoT) Technology
Numerous news media outlets cover incidents in which trained personnel or combatants are injured or perish while defusing bombs. The military robot that conducts intelligence operations. While it has been beneficial to the Army, firefighters, and police officers in critical situations, many of the current systems are inefficient due to their lack of accuracy and technology. Our objective is to develop the most efficient robot possible in order to achieve accuracy and technology. Robotic limbs equipped with metal detectors are being installed to provide manual assistance. The wireless explosive disposal device will enhance our nation's defense against terrorists, suicide bombers, and other similar activities. Experts are required to operate the explosives detectors and disposal system. However, this method of analysis necessitates additional time and poses a risk to the lives of experts. A novel robot, the IoT Defense Robotic Model (IoTDRM), is developed in this paper with the assistance of Internet of Things (IoT) technology. The proposed model is cross-validated against the conventional logic of the Smart Bomb Diffusing Robot (SBDR) to assess its performance. The signals are transmitted from the sensor end to the IoT controller in this robot, and they are retransmitted to the server end via a wireless system. The user controls the automaton manually using a personal computer or mobile phone. When the sensor detects a metal, a buzzer alarm will sound. The metal is examined using a wireless camera to determine whether it is a weapon. Since the identified metal is a bomb, the user instructs the robot to detonate it via the computer.
Authors
- Maram Y. Al-Safarini
- M. Swarna (ORCID: https://orcid.org/0009-0008-1038-5772)
- P. Vijayakumari
- Alok Narkhede
- N. Deepa (ORCID: https://orcid.org/0000-0002-7483-568X)
- Sheji Mary
Institutions
- Albert Einstein College of Medicine (US)
- SRM Institute of Science and Technology (IN)
- Zarqa University (JO)
- Dr. M.G.R. Educational and Research Institute (IN)
Publication Details
- Published
- 2024-12-12
- DOI
- https://doi.org/10.1109/icses63760.2024.10910752
- Primary Topic
- Fire Detection and Safety Systems
- Type
- article
- Field-Weighted Citation Impact
- 0.00