IoT in Urban Traffic Prediction Development Case Studies and Future Trends
The problem of urban traffic has become quite serious in recent years. This problem seriously affects the daily travel of urban residents and urban safety and brings great challenges to the sustainable development of the transportation system. This paper first briefly summarizes the development proc...
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EDP Sciences
2025-01-01
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| Series: | ITM Web of Conferences |
| Online Access: | https://www.itm-conferences.org/articles/itmconf/pdf/2025/01/itmconf_dai2024_01007.pdf |
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| author | Wang Renhe |
| author_facet | Wang Renhe |
| author_sort | Wang Renhe |
| collection | DOAJ |
| description | The problem of urban traffic has become quite serious in recent years. This problem seriously affects the daily travel of urban residents and urban safety and brings great challenges to the sustainable development of the transportation system. This paper first briefly summarizes the development process of using the Internet of Things (IoT) to calculate future road traffic. As early as 1999, Kevin Ashton proposed to apply the Internet of Things to traffic, but the application in the traffic field is not mature, such as the early ETC (electronic road pricing system). With the rise of wireless communication technology, vehicle GPS navigation systems began to appear, which can provide real-time traffic information and route planning. Nowadays, various sensors, radio frequency identification devices (RFID), cameras, and other devices are widely used, making real-time data collection and analysis possible. Then it analyzes the current actual successful cases of using the IOT to calculate future road traffic, discusses in detail the promotion of traffic and the advantages of using the Internet of Things compared with the previous traffic, and gives the corresponding data. Finally, the future research direction and development trends are put forward. First, edge computing is introduced into the IOT, and edge computing is mixed with cloud computing to obtain a prediction system with better performance and lower robustness. The second is to optimize the existing network transport layer protocol. Finally, this paper makes a summary. |
| format | Article |
| id | doaj-art-c78433922c8547dba7018fcecb798e37 |
| institution | Kabale University |
| issn | 2271-2097 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | EDP Sciences |
| record_format | Article |
| series | ITM Web of Conferences |
| spelling | doaj-art-c78433922c8547dba7018fcecb798e372025-02-07T08:21:10ZengEDP SciencesITM Web of Conferences2271-20972025-01-01700100710.1051/itmconf/20257001007itmconf_dai2024_01007IoT in Urban Traffic Prediction Development Case Studies and Future TrendsWang Renhe0Pearl River College, Tianjin University of Finance and EconomicsThe problem of urban traffic has become quite serious in recent years. This problem seriously affects the daily travel of urban residents and urban safety and brings great challenges to the sustainable development of the transportation system. This paper first briefly summarizes the development process of using the Internet of Things (IoT) to calculate future road traffic. As early as 1999, Kevin Ashton proposed to apply the Internet of Things to traffic, but the application in the traffic field is not mature, such as the early ETC (electronic road pricing system). With the rise of wireless communication technology, vehicle GPS navigation systems began to appear, which can provide real-time traffic information and route planning. Nowadays, various sensors, radio frequency identification devices (RFID), cameras, and other devices are widely used, making real-time data collection and analysis possible. Then it analyzes the current actual successful cases of using the IOT to calculate future road traffic, discusses in detail the promotion of traffic and the advantages of using the Internet of Things compared with the previous traffic, and gives the corresponding data. Finally, the future research direction and development trends are put forward. First, edge computing is introduced into the IOT, and edge computing is mixed with cloud computing to obtain a prediction system with better performance and lower robustness. The second is to optimize the existing network transport layer protocol. Finally, this paper makes a summary.https://www.itm-conferences.org/articles/itmconf/pdf/2025/01/itmconf_dai2024_01007.pdf |
| spellingShingle | Wang Renhe IoT in Urban Traffic Prediction Development Case Studies and Future Trends ITM Web of Conferences |
| title | IoT in Urban Traffic Prediction Development Case Studies and Future Trends |
| title_full | IoT in Urban Traffic Prediction Development Case Studies and Future Trends |
| title_fullStr | IoT in Urban Traffic Prediction Development Case Studies and Future Trends |
| title_full_unstemmed | IoT in Urban Traffic Prediction Development Case Studies and Future Trends |
| title_short | IoT in Urban Traffic Prediction Development Case Studies and Future Trends |
| title_sort | iot in urban traffic prediction development case studies and future trends |
| url | https://www.itm-conferences.org/articles/itmconf/pdf/2025/01/itmconf_dai2024_01007.pdf |
| work_keys_str_mv | AT wangrenhe iotinurbantrafficpredictiondevelopmentcasestudiesandfuturetrends |