Smart Transportation Tracking Systems Based on the Internet of Things Vision

Fernando, Wiliam; Samarakkody, Ruwani M.; Halgamuge, Malka N.

doi:10.1007/978-3-030-36167-9_7

Cited by 7 publications

(5 citation statements)

References 37 publications

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“…Actuators are autonomous software agents that have been created as a low-cost option for tackling complicated issues across a wide range of application fields [30,31]. Actuators in the proposed architecture operate as message agents to improve traffic flow by learning a traffic management policy that determines when to show signal status, which measures the number of cars at a specific signal 4…”

Section: Actuatorsmentioning

confidence: 99%

Smart Traffic Management System for Metropolitan Cities of Kingdom Using Cutting Edge Technologies

Humayun

Afsar

Almufareh

et al. 2022

Journal of Advanced Transportation

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The expansion of technology in metropolitan centers draws people to cities, which causes excessive traffic on the roadways during peak hours. This exacerbated the traffic situation, resulting in a delay, a loss of resources, and a waste of time. Like any other metropolitan metropolis, Riyadh, Saudi Arabia, has everyday traffic congestion during business hours. The current traffic management has made many attempts to ease traffic congestion in cities; despite these measures, the problem has not been solved adequately. To handle this road congestion, there is a need to appropriately store the big data collected by traffic sensors and utilize it for efficient traffic management employing cutting-edge technology. This study provides an architecture for a smart traffic management system that uses modern technologies such as the Internet of Things (IoT), cloud computing, 5G, and big data to aid conventional traffic management systems and efficiently handle the stated problem. The proposed technique has the potential to reduce traffic congestion significantly. Our proposed solution encourages mobility by using roadside messaging agents to offer real-time traffic information on traffic congestion and unexpected traffic incidents. Citizens will save time by getting these early warning messages, particularly during peak hours. As part of the suggested method, each signal dashboard gets traffic information. A case study is used in the research to evaluate alternative solutions to traffic congestion. The case study results show that the proposed strategy outperforms the present options.

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Section: Actuatorsmentioning

confidence: 99%

Smart Traffic Management System for Metropolitan Cities of Kingdom Using Cutting Edge Technologies

Humayun

Afsar

Almufareh

et al. 2022

Journal of Advanced Transportation

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“…The sliding side of the mechanism is that the vehicular body becomes hidden from tracing view, if the GPS device is switched off. Fernando et al (2020) established the monitoring schema with satellite based navigation and to describe the protocols for second generation tracking device, but this system flips with the remote sensing ability as it does not encompass IoT technology for the ease of connectivity.…”

Section: Literature Surveymentioning

confidence: 99%

434 MHz Environmentally Safe Monitoring Schema for Vehicular Network by AI-ML-IoT Technologies

Kumar

Jayasingh

2021

Journal of Cases on Information Technology

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Connected vehicular tracking schema operated in environmentally safe radio frequency of 434 MHz, artificial intelligence, and machine learning and IoT technology (CVT-AIML-IoT) is cost effective and secured tracking or device monitoring system. The prime benefit of the proposed CVT-AIML-IoT system is that it utilizes cloud internet of things (IoT) technology and active radio frequency identification over global positioning system (GPS), which is prone to attackers due to self-defenseless network architecture. The sliding side of GPS is observed; when the GPS module is switched-off, it can be hidden without any authorization. Hence, an uninterrupted observing secured system like CVT-AIML-IoT is a promising solution with dynamic vehicular PIN generation by AI-ML concept. CVT-AIML-IoT grids the traceable area based on the topographical dependency. Detection range gateway coupled with IoT transceiver module captures data from each tracking zone to the cloud for monitoring over Web UI support and mapped with time stamp. Hence, CVT-AIML-IoT assures vehicular monitoring in a lucrative approach.

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“…Hence, organizations started experimenting, involved an indepth literature review of several parameters. Fernando et al (2020) studied the measurement of attributes of the moving vehicle and on how sensors can be used for data retrieval in tracking devices. Qiu et al (2018) assessed how various data are transferring methods for transmission, networks, and protocols utilized for communication.…”

Section: Literature Reviewmentioning

confidence: 99%

An IoT Based Model for a Trucking Transport System Using Predictive Analytics

Mahajan¹

2020

SJKFU

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The Internet of Things (IoT) has enormous potential to revolutionize the transport industry. IoT can be used to optimize the mobility of goods and people, adding transparency, updating information, and providing convenience while reducing the cost. The speed drives the requirements of the trucking industry with sustainability, safety and stresslessness. After reviewing the current challenges of supply chain networks, this paper proposes a new smart solution for booking freight in a new way, integrating data from multiple sources using smart cloud-based solutions. This paper provides a solution using two modules. Module 1 is the development of a mobile application for order updates and lives to monitor vehicles. Module 2 is an IoT device, which works as an intelligent device by using sensors and microcontrollers. This results in 'organizations' transparency on the live monitoring of the status of their entire supply chain network, anticipating problems in advance, and immediate response to the problem. This paper has implications for organizations that are driven by increased customer requirements pertaining to lead time delivery services, product availability, and reliability.

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Smart Transportation Tracking Systems Based on the Internet of Things Vision

Cited by 7 publications

References 37 publications

Smart Traffic Management System for Metropolitan Cities of Kingdom Using Cutting Edge Technologies

Smart Traffic Management System for Metropolitan Cities of Kingdom Using Cutting Edge Technologies

434 MHz Environmentally Safe Monitoring Schema for Vehicular Network by AI-ML-IoT Technologies

An IoT Based Model for a Trucking Transport System Using Predictive Analytics

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