Aravind S.
Chandini Sunil
Gokul M. S.
Soorya V.
Vinayak J.
Ajeesha S.
- U. G. Scholar Department of Electrical & Electronics Engineering, College of Engineering Perumon Kerala India
- U. G. Scholar Department of Electrical & Electronics Engineering, College of Engineering Perumon Kerala India
- U. G. Scholar Department of Electrical & Electronics Engineering, College of Engineering Perumon Kerala India
- U. G. Scholar Department of Electrical & Electronics Engineering, College of Engineering Perumon Kerala India
- U. G. Scholar Department of Electrical & Electronics Engineering, College of Engineering Perumon Kerala India
- Assistant Professor Department of Electrical & Electronics Engineering, College of Engineering Perumon Kerala India
Abstract
Autonomous Snake Detection and Catching Robot for household Safety after Calamities is a robot to protect house premises from the intrusion of snakes which is a major issue specially after calamities. During floods many incidents of snake encounters and bites were reported in numerous residential areas. According to disaster management experts, the possibility of flood in Kerala still remains and it can cause major impacts in future. Conventional methods for snake catching include tongs, hooks, hand capture and the limitations of these techniques are restrictions in the capability to reach the snake, potential injury and safety concerns. Autonomous Snake Detection and Catching Robot aims to address these limitations while prioritizing the safety of both humans and snakes. The proposal combines the procurement of series number of images and the detection of snake in the captured image with the machine learning concepts implemented through robotic technology, minimizing human intervention and ensuring a safer approach. The system uses the Raspberry Pi platform and YOLO to develop a cost-effective and efficient solution for the safe and autonomous capture of snakes. Real time monitoring is done with the help of cameras. The images obtained from the video captured by the camera module is compared with the trained database and if it matches, the alert system is triggered. Once the snake is detected it is caught by the robot with the help of a robotic arm. Unlike existing solutions the robot does not rely solely on human intervention minimizing human exposure to danger. Ultimately, the snake catching robot contributes to the overall resilience of communities in disaster-prone regions, safeguarding lives.
Keywords: Real-time monitoring, image processing, autonomous robot, rasberry Pi 4
[This article belongs to International Journal of Robotics and Automation in Mechanics(ijram)]
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| Volume | 02 |
| Issue | 01 |
| Received | May 29, 2024 |
| Accepted | June 5, 2024 |
| Published | July 6, 2024 |
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