Real-time IoT Urban Road Traffic Data Monitoring using LoRaWAN

Aneiba, Adel and Hayes, John and Albaarini, Mohammad and Brett, Nangle (2019) Real-time IoT Urban Road Traffic Data Monitoring using LoRaWAN. In: The 9th International Conference on the Internet of Things (IoT 2019), 22-25 October, Bilbao Spain. (In Press)

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Abstract

Inductive loop detection (ILD) systems have been used extensively within cities as an effective and reliable method of monitoring road traffic conditions through the detection and counting of vehicles. However, the existing ILDs systems suffer from numerous issues, including the complexity of integration with other technologies, high equipment cost and tedious management and maintenance processes.

Next-generation traffic monitoring systems need to be future proof and flexible, capable of adapting to any surface or road condition, in addition to maintaining the accuracy offered by existing solutions. Improving upon the concept of standard inductive loop technology used in existing traffic
detection and monitoring will be a significant step forward in achieving smarter uncongested cities. This paper presents an innovative, effective and reliable end-to-end inductive loop monitoring solution using a low-cost dual-loop detection board integrated with low power wide area network
(LPWAN) connectivity technology. The proposed solution has proven its robustness, accuracy and simplicity over the existing solution in initial experimentation, providing a realtime view of road conditions at low operational and capital expense, and comparatively trivial management.

Item Type: Conference or Workshop Item (Paper)
Uncontrolled Keywords: Urban Traffic Monitoring ,Inductive loop, intelligent traffic system, LPWAN ,LoRaWAN
Subjects: G400 Computer Science
Divisions: Faculty of Computing, Engineering and the Built Environment
Faculty of Computing, Engineering and the Built Environment > School of Computing and Digital Technology
Faculty of Computing, Engineering and the Built Environment > School of Computing and Digital Technology > Cloud Computing
Depositing User: Adel Aneiba
Date Deposited: 10 Sep 2019 12:47
Last Modified: 10 Sep 2019 12:47
URI: http://www.open-access.bcu.ac.uk/id/eprint/7968

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