Level-6 Automated IoT integrated with Artificial Intelligence Based Big Data-Driven Dynamic Vehicular Traffic Control System

Visuwasam L, Maria and Balakrishna, Ashwin and S R, Nikitha and V, Kowsalyaa (2020) Level-6 Automated IoT integrated with Artificial Intelligence Based Big Data-Driven Dynamic Vehicular Traffic Control System. EAI Endorsed Transactions on Energy Web, 7 (29): e9. ISSN 2032-944X

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Abstract

The current traffic control system (TCS) is not the most efficient system present for regulating traffic. Hoping to solve this we come up with dynamic data recording systems which encompasses of RFID tag and reader. The traffic density at each lane is calculated based on count of RFID’s apprehended. Depending on the density, the TCS is assigned a value of 15 to 70 seconds in round robin method for control of vehicular congestion. This proposed model also uses image processing for the detection of ambulances and also an active RFID for tracking the real-time location of these assets or in high-speed environments such as that of tolling. This allows the passage of ambulances through dense traffic. This system hopes to achieve to reduce the needless wait of crowded side, to reduce the long traffic chains, and to allow emergencies (medical/ vigilante) quickly through the traffic. The major merits of the system are it prevents unnecessary waiting time when no cars are present at the opposite route, gives the commuting passengers a better and more comfortable driving experience through their journey.

Item Type: Article
Uncontrolled Keywords: RFID, Energy Efficient Device-to-Device (D2D) Communications, active, Energy Efficient Routing Protocols, round robin
Subjects: Q Science > QA Mathematics > QA75 Electronic computers. Computer science
QA75 Electronic computers. Computer science
Depositing User: EAI Editor II.
Date Deposited: 16 Sep 2020 14:00
Last Modified: 16 Sep 2020 14:00
URI: https://eprints.eudl.eu/id/eprint/377

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