Traffic Violation Tracker and Controller
S. P. Maniraj (),
Tadepalli Sarada Kiranmayee,
Aakanksha Thakur,
M. Bhagyashree and
Richa Gupta
Additional contact information
S. P. Maniraj: SRM Institute of Science and Technology
Tadepalli Sarada Kiranmayee: SRM Institute of Science and Technology
Aakanksha Thakur: SRM Institute of Science and Technology
M. Bhagyashree: SRM Institute of Science and Technology
Richa Gupta: SRM Institute of Science and Technology
A chapter in New Trends in Computational Vision and Bio-inspired Computing, 2020, pp 335-343 from Springer
Abstract:
Abstract It has always been noticed that the excuse given for any work delay are traffic. Urbanites face a lot of trouble due to traffic congestion. These congestions are caused by multiple reasons like traffic violators, traffic collision, inadequate green time, obstacles and many other reasons. Sometimes this can be due to traffic signal going out of sync due to system malfunctioning. Various interesting and engrossing advancements in this sector can be made using the field of IoT. It can bring many visions true to the real world. This paper focuses on reducing the reasons for traffic congestion by tackling them and providing the traffic handlers a technological relief, by giving them a centrally tracking system controlled via a network. For the gathering and processing of the real-time data, IoT is used. This processed information is sent to Cloud for further processes. This stratagem is generalized and can be deployed anywhere efficiently without much manual efforts.
Keywords: Urbanites; Traffic violators; Traffic handlers; IoT (search for similar items in EconPapers)
Date: 2020
References: Add references at CitEc
Citations:
There are no downloads for this item, see the EconPapers FAQ for hints about obtaining it.
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:spr:sprchp:978-3-030-41862-5_31
Ordering information: This item can be ordered from
http://www.springer.com/9783030418625
DOI: 10.1007/978-3-030-41862-5_31
Access Statistics for this chapter
More chapters in Springer Books from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().