A. Lakshna, K. Ramesh, B. Prabha, D. Sheema, K. Vijayakumar
{"title":"机器学习,智能交通预测和减少拥堵","authors":"A. Lakshna, K. Ramesh, B. Prabha, D. Sheema, K. Vijayakumar","doi":"10.1109/ICSES52305.2021.9633949","DOIUrl":null,"url":null,"abstract":"Smart traffic congestion reduction is useful for reducing the traffic in a highly congested area. To prevent heavy traffic Internet of things is implemented through a small device called a sensor, this technology is called smart traffic. A small device is placed near the roadside street post to detect the vehicle count. Smart traffic works by collecting the various signals like WiFi, Bluetooth, ZigBee from various electronic gadgets like a smartphone, smartwatch, smart band, tablet. The MAC address from each vehicle is collected as input information and stored in a cloud platform. Analyze and calculate the collected data set and performed it under machine learning prediction algorithms to get a better accuracy result to avoid traffic congestion. The logistic regression algorithm gives a 91% of accuracy level in traffic. It gives the shortest route to reach the destination without any hurdles. Results are reduced the traveling time, noise pollution, carbon dioxide emission, reach the destination on correct time and also save the fuel.","PeriodicalId":6777,"journal":{"name":"2021 International Conference on Innovative Computing, Intelligent Communication and Smart Electrical Systems (ICSES)","volume":"5 1","pages":"1-4"},"PeriodicalIF":0.0000,"publicationDate":"2021-09-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"Machine learning Smart Traffic Prediction and Congestion Reduction\",\"authors\":\"A. Lakshna, K. Ramesh, B. Prabha, D. Sheema, K. Vijayakumar\",\"doi\":\"10.1109/ICSES52305.2021.9633949\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Smart traffic congestion reduction is useful for reducing the traffic in a highly congested area. To prevent heavy traffic Internet of things is implemented through a small device called a sensor, this technology is called smart traffic. A small device is placed near the roadside street post to detect the vehicle count. Smart traffic works by collecting the various signals like WiFi, Bluetooth, ZigBee from various electronic gadgets like a smartphone, smartwatch, smart band, tablet. The MAC address from each vehicle is collected as input information and stored in a cloud platform. Analyze and calculate the collected data set and performed it under machine learning prediction algorithms to get a better accuracy result to avoid traffic congestion. The logistic regression algorithm gives a 91% of accuracy level in traffic. It gives the shortest route to reach the destination without any hurdles. Results are reduced the traveling time, noise pollution, carbon dioxide emission, reach the destination on correct time and also save the fuel.\",\"PeriodicalId\":6777,\"journal\":{\"name\":\"2021 International Conference on Innovative Computing, Intelligent Communication and Smart Electrical Systems (ICSES)\",\"volume\":\"5 1\",\"pages\":\"1-4\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2021-09-24\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2021 International Conference on Innovative Computing, Intelligent Communication and Smart Electrical Systems (ICSES)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICSES52305.2021.9633949\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2021 International Conference on Innovative Computing, Intelligent Communication and Smart Electrical Systems (ICSES)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICSES52305.2021.9633949","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Machine learning Smart Traffic Prediction and Congestion Reduction
Smart traffic congestion reduction is useful for reducing the traffic in a highly congested area. To prevent heavy traffic Internet of things is implemented through a small device called a sensor, this technology is called smart traffic. A small device is placed near the roadside street post to detect the vehicle count. Smart traffic works by collecting the various signals like WiFi, Bluetooth, ZigBee from various electronic gadgets like a smartphone, smartwatch, smart band, tablet. The MAC address from each vehicle is collected as input information and stored in a cloud platform. Analyze and calculate the collected data set and performed it under machine learning prediction algorithms to get a better accuracy result to avoid traffic congestion. The logistic regression algorithm gives a 91% of accuracy level in traffic. It gives the shortest route to reach the destination without any hurdles. Results are reduced the traveling time, noise pollution, carbon dioxide emission, reach the destination on correct time and also save the fuel.