Adaptive Traffic Management System Using IoT and Machine Learning

Yadav, Abhishek; More, Vaishali; Shinde, Neha; Nerurkar, Manjiri; Sakhare, Nitin N.

doi:10.32628/ijsrset196146

Cited by 17 publications

(5 citation statements)

References 17 publications

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“…Smart algorithms are currently helping many organizations in the private and public sectors to improve their operating efficiencies [57]. In the public sector, for instance, city traffic management can be improved significantly by availing of an adaptive AI-based traffic management system [58]. Strategic placement of sensors closes to street lamps/ bulbs in public spaces facilitates data gathering.…”

Section: Artificial Intelligence In Smart Citiesmentioning

confidence: 99%

Blending Human Ware with Software and Hardware in the Design of Smart Cities

Almusaed¹,

Almssad²

2023

Sustainable Smart Cities - A Vision for Tomorrow

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Sustainable innovation entails realizing society-oriented value creation in an environment-friendly manner. A smart city can be viewed as a holistic paradigm that avails of state-of-the-art information and communication technologies (ICTs, in other words) to advance the so-called “Internet of Things.” This aids the management of urban processes and improves the quality of life for the citizens. Smart cities are bound to keep getting “smarter” as the ICTs keep developing. While the technological factor represented by the IoT, augmented and virtual reality, artificial intelligence, urban digital twinning, cloud computing, and mobile Internet is a driving factor unarguably, innovation in urban ecology is a vital socio-economic factor that will spur the transformation of urban areas in the world to smart cities. In this chapter, the authors answer the “what,” how, and “who,” so to say, of the paradigm—smart cities—with real-life examples and a case study. They emphasize the importance of human ware and remind readers that technology—the all-encompassing Internet of Things with its infantry of cameras, sensors, and electronic devices—though powerful, is a humble servant in the service of the inhabitants of a smart city.

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Section: Artificial Intelligence In Smart Citiesmentioning

confidence: 99%

Blending Human Ware with Software and Hardware in the Design of Smart Cities

Almusaed¹,

Almssad²

2023

Sustainable Smart Cities - A Vision for Tomorrow

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“…This work's follow-up research aims to more thoroughly analyze traffic monitoring video data and to offer helpful traffic travel advisory services [10]. With a software system, the circumstances of an accident can be determined by identifying overlapping images in real-time video streaming [129]. To create various condition-specific datasets for model testing, we advise a more thorough comparison of these two, employing field data for model calibration, simulation, DTW, and SVM.…”

Section: Recent Trends Research Directions and Lessons Learnedmentioning

confidence: 99%

A Review of Artificial Intelligence and Machine Learning for Incident Detectors in Road Transport Systems

Olugbade

Ojo²,

Imoize

et al. 2022

MCA

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Road transport is the most prone to accidents, resulting in significant fatalities and injuries. It also faces a plethora of never-ending problems, such as the frequent loss of lives and valuables during an accident. Appropriate actions need to be taken to address these problems, such as the establishment of an automatic incident detection system using artificial intelligence and machine learning. This article explores the overview of artificial intelligence and machine learning in facilitating automatic incident detector systems to decrease road accidents. The study examines the critical problems and potential remedies for reducing road traffic accidents and the application of artificial intelligence and machine learning in road transportation systems. More, new, and emerging trends that reduce frequent accidents in the transportation sector are discussed extensively. Specifically, the study organized the following sub-topics: an incident detector with machine learning and artificial intelligence and road management with machine learning and artificial intelligence. Additionally, safety is the primary concern of road transport; the internet of vehicles and vehicle ad hoc networks, including the use of wireless communication technologies such as 5G wireless networks and the use of machine learning and artificial intelligence for road transportation systems planning, are elaborated. Key findings from the review indicate that route optimization, cargo volume forecasting, predictive fleet maintenance, real-time vehicle tracking, and traffic management are critical to safeguarding road transportation systems. Finally, the paper summarizes the challenges facing the application of artificial intelligence in road transport systems, highlights the research trends, identifies the unresolved questions, and highlights the essential research takeaways. The work can serve as reference material for road transport system planning and management.

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“…Throughout any trip, there is a chance for accident happening at any moments [2]. Manual control of traffic, by traffic officers or using predefined timers has been confirmed that it's not an real solution to all the earlier cited problems caused by traffic accidents [3]. So we need to design better traffic management system can detect the accident and decreased the severity of injures after an accident by reducing the period gap between the accident happening and the therapeutic response.…”

Section: Introductionmentioning

confidence: 99%

A Review of Vehicle Accident Detection and Notification Systems Based on Machine Learning Techniques

Hadi Nassar,

Mustafa Al-Tuwaijari

2024

Acad. Sci. J.

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The rabid growth of the vehicles accidents on our roads are increasing as well as the number of human lives lost and the costs of repairing damages due to these accidents in order to reduce the dangers associated with accidents. A lot of researchers and specialists turn to electronic systems based on machine learning, deep learning techniques algorithms or any other artificial intelligence methods to detect and generate an emergency signal can reduce the time gap between the accident happening and the arrival of medical help. The main purpose of this review article was to identify and collect all the studies that have been done previously to detect roads traffics based on using machine learning techniques particularly deep learning. This paper will present all the methods that have been used and the experimental results of these studies and the research gabs they contain. We are following a systematic search plan passed on selected the papers that have the most similar keyword to make sure that all paper are exactly matching this paper subject so we apply this plan by using Springer, Elsevier, Electrical and Electronics Engineers (IEEE) xplore ,Google scholar, Arxiv, Sciencedirect and Researchgate datasets. From the all previous mentioned datasets we found 37 papers only 26 of these papers are corresponded with the review subject.

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Adaptive Traffic Management System Using IoT and Machine Learning

Cited by 17 publications

References 17 publications

Blending Human Ware with Software and Hardware in the Design of Smart Cities

Blending Human Ware with Software and Hardware in the Design of Smart Cities

A Review of Artificial Intelligence and Machine Learning for Incident Detectors in Road Transport Systems

A Review of Vehicle Accident Detection and Notification Systems Based on Machine Learning Techniques

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