I. Imran, R. Ramesh, S. S. Abineshwar, V. Pandyaraj
{"title":"Intelligent Fire-Fighting Robot with Deep Learning","authors":"I. Imran, R. Ramesh, S. S. Abineshwar, V. Pandyaraj","doi":"10.1109/IC3IOT53935.2022.9767869","DOIUrl":null,"url":null,"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.","PeriodicalId":430809,"journal":{"name":"2022 International Conference on Communication, Computing and Internet of Things (IC3IoT)","volume":"13 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-03-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2022 International Conference on Communication, Computing and Internet of Things (IC3IoT)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/IC3IOT53935.2022.9767869","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
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.