Parameswaran Ramesh, Vidhya N, Panjavarnam B, Shabana Parveen M, Deepak Athipan A M B, B. P. T. V
{"title":"I-CVSSDM: IoT Enabled Computer Vision Safety System for Disaster Management","authors":"Parameswaran Ramesh, Vidhya N, Panjavarnam B, Shabana Parveen M, Deepak Athipan A M B, B. P. T. V","doi":"10.4108/eetiot.5046","DOIUrl":null,"url":null,"abstract":"INTRODUCTION: Around the world, individuals experience flooding more frequently than any other natural calamity. \nOBJECTIVES: The motivation behind this research is to provide an Internet of Things (IoT)-based early warning assistive system to enable monitoring of water logging levels in flood-affected areas. Further, the SSD-MobiNET V2 model is used in the developed system to detect and classify the objects that prevail in the flood zone. \nMETHODS: The developed research is validated in a real-time scenario. To enable this, a customized embedded module is designed and developed using the Raspberry Pi 4 model B processor. The module uses (i) a pi-camera to capture the objects and (ii) an ultrasonic sensor to measure the water level in the flood area. \nRESULTS: The measured data and detected objects are periodically ported to the cloud and stored in the cloud database to enable remote monitoring and further processing. \nCONCLUSION: Also, whenever the level of waterlogged exceeds the threshold, an alert is sent to the concerned authorities in the form of an SMS, a phone call, or an email.","PeriodicalId":506477,"journal":{"name":"EAI Endorsed Transactions on Internet of Things","volume":"71 2","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2024-02-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"EAI Endorsed Transactions on Internet of Things","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.4108/eetiot.5046","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
INTRODUCTION: Around the world, individuals experience flooding more frequently than any other natural calamity.
OBJECTIVES: The motivation behind this research is to provide an Internet of Things (IoT)-based early warning assistive system to enable monitoring of water logging levels in flood-affected areas. Further, the SSD-MobiNET V2 model is used in the developed system to detect and classify the objects that prevail in the flood zone.
METHODS: The developed research is validated in a real-time scenario. To enable this, a customized embedded module is designed and developed using the Raspberry Pi 4 model B processor. The module uses (i) a pi-camera to capture the objects and (ii) an ultrasonic sensor to measure the water level in the flood area.
RESULTS: The measured data and detected objects are periodically ported to the cloud and stored in the cloud database to enable remote monitoring and further processing.
CONCLUSION: Also, whenever the level of waterlogged exceeds the threshold, an alert is sent to the concerned authorities in the form of an SMS, a phone call, or an email.
引言:在世界各地,人们遭遇洪灾的频率高于其他自然灾害。目标:这项研究的动机是提供一个基于物联网(IoT)的预警辅助系统,以监测受洪水影响地区的积水程度。此外,开发的系统还使用了 SSD-MobiNET V2 模型来检测洪水区域内的物体并对其进行分类。方法:所开发的研究在实时场景中进行了验证。为此,使用 Raspberry Pi 4 B 型处理器设计和开发了一个定制的嵌入式模块。该模块使用(i) pi 摄像头捕捉物体,(ii) 超声波传感器测量洪水区域的水位。结果:测量到的数据和检测到的物体会定期移植到云端,并存储在云数据库中,以便进行远程监控和进一步处理。结论:此外,只要内涝水位超过阈值,就会以短信、电话或电子邮件的形式向有关部门发出警报。