Intelligent Fire-Fighting Robot with Deep Learning

I. Imran, R. Ramesh, S. S. Abineshwar, V. Pandyaraj
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Abstract

An accidental fire is a mishap that could be happen man-made or natural. Accidental fire occurs frequently and can be controlled but sometimes result in severe loss of life and property. To prevent these deadly activities, an autonomous fire-fighting robot is introduced. The bot will be activated as soon as the information of the fire accident reaches the bot. Once the location is fixed with google API, waypoints can be marked through the mission planner with the help of the GPS module. The bot will autonomously reach the destination using computer vision technologies. Lane, obstacle, and traffic light detections are executed to enable the autonomous drive. Yolov5 architecture plays a major role in detection methodologies. As soon as it reaches the destination, the fire and heat sensors will detect and spray water to douse the fire through the nozzle that can rotate about 180°. Initially, only one bot will be sent for rescue purposes, if it can't satisfy the needs and requirements, then the GSM module will send the message of inefficiency. So that more bots will reach the destination and can resolve the problem. To protect the electronic components the bot is thermally insulated with a special alloy of stainless steel. The proposed system will help reduce the burden of firefighters as well as manual errors caused during firefighting thus, it can own by private companies as well government.
具有深度学习的智能消防机器人
意外火灾是一种可能是人为或自然发生的事故。意外火灾发生频繁,可以控制,但有时会造成严重的生命财产损失。为了防止这些致命的活动,引入了一种自主消防机器人。一旦火灾事故的信息到达机器人,机器人将立即启动。一旦使用google API确定了位置,就可以在GPS模块的帮助下通过任务规划器标记航路点。机器人将利用计算机视觉技术自动到达目的地。车道、障碍物和交通灯检测被执行,以实现自动驾驶。Yolov5体系结构在检测方法中起着重要作用。一旦到达目的地,火灾和热传感器将检测并通过可旋转约180°的喷嘴喷水灭火。最初,只会派出一个机器人进行救援,如果不能满足需要和要求,GSM模块就会发送无效的消息。这样就会有更多的机器人到达目的地并解决问题。为了保护电子元件,机器人采用特殊的不锈钢合金隔热。该系统不仅可以由政府拥有,还可以由民间企业拥有,不仅可以减少消防员的负担,还可以减少消防过程中出现的人为失误。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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