An Investigation of Garbage Disposal Electric Vehicles (GDEVs) Integrated with Deep Neural Networking (DNN) and Intelligent Transportation System (ITS) in Smart City Management System (SCMS)

2021 ◽  
Author(s):  
N. Yuvaraj ◽  
K. Praghash ◽  
R. Arshath Raja ◽  
T. Karthikeyan
Keyword(s):  
Electric Vehicles ◽  
Smart City ◽  
Management System ◽  
Intelligent Transportation System ◽  
Intelligent Transportation ◽  
Transportation System ◽  
City Management ◽  
Garbage Disposal

scholarly journals 5G Vehicular Network for Smart Vehicles in Smart City: A Review

2020 ◽  
Vol 1 (1) ◽  
Author(s):  
Hamzah U. Mustakim
Keyword(s):  
Smart City ◽  
Intelligent Transportation System ◽  
Data Communication ◽  
Intelligent Transportation ◽  
Vehicular Network ◽  
Transportation System ◽  
Maximum Speed ◽  
Multimedia Services ◽  
Communication Services ◽  
Smart Vehicles

Smart vehicles is one of the innovation that can be used to increase the effectiveness of traffic in smart city as urban area and in the highway. In its development, smart vehicles not only require mobile communication services to ensure safety but also multimedia services for the passengers. These services must be integrated on intelligent transportation system. 5G vehicular network technology provides data communication services for intelligent transportation system via macrocells and smallcells to support smart vehicles which can drive at a maximum speed of 500Km/hour with multimedia services for passengers with data rates reaching the Gbps level. This paper will review 5G network architecture and emerging technologies that enabling vehicular network for smart vehicles in smart city.

scholarly journals Сontrol of Intelligent Transport System in Minsk

2018 ◽  
Vol 17 (5) ◽  
pp. 401-412
Author(s):  
D. V. Kapskiy ◽  
D. V. Navoy ◽  
P. A. Pegin
Keyword(s):  
Traffic Flow ◽  
Traffic Management ◽  
Management System ◽  
Intelligent Transportation System ◽  
Road Traffic ◽  
Intelligent Transportation ◽  
Transportation System ◽  
Design System ◽  
Intelligent Transport System ◽  
Traffic Management System

The paper considers algorithms for searching a maximum traffic volume of road vehicles in a traffic light cycle with a distributed intensity pulse and optimization of shifts under coordinated traffic flow control. Modeling of traffic flows have been made while using a computer program developed by the authors and it has made it possible to improve efficiency of traffic management by taking into account the distributed pulse of transport intensity. The paper proposes a model for minimizing total losses in road traffic during the integration of an incident control sub-system and route guidance for and an automatic road traffic management system as part of Minsk intelligent transportation system which has been studied as a tool for modeling a computer-aided design system "Backbone management". The model that minimizes vehicle delays, uses an algorithm implementing traffic flow intensity parameters depending on the time of day, days of the week. As a result of the simulation it has been revealed that the most effective parameter is an indicator of vehicle delays which does not always satisfy drivers trying to choose routes of their traffic which are based on a minimum transportation speed. However, from the point of view of managing an intelligent transportation system, it is necessary to choose parameters based on the requirements for minimizing delays on the road traffic network of the largest city in our country. All the proposed algorithms and models are used in the automatic traffic management system of Minsk city and will be used while creating an integrated intellectual transportation system of the city.

Machine learning based accident prediction in secure IoT enable transportation system

2021 ◽  
pp. 1-13 ◽  
Author(s):  
Bhabendu Kumar Mohanta ◽  
Debasish Jena ◽  
Niva Mohapatra ◽  
Somula Ramasubbareddy ◽  
Bharat S. Rawal
Keyword(s):  
Machine Learning ◽  
Smart City ◽  
Information Exchange ◽  
Secure Communication ◽  
Intelligent Transportation System ◽  
Transportation System ◽  
Information And Communications Technology ◽  
Classification Models ◽  
Architecture Model ◽  
Accident Severity

Smart city has come a long way since the development of emerging technology like Information and communications technology (ICT), Internet of Things (IoT), Machine Learning (ML), Block chain and Artificial Intelligence. The Intelligent Transportation System (ITS) is an important application in a rapidly growing smart city. Prediction of the automotive accident severity plays a very crucial role in the smart transportation system. The main motive behind this research is to determine the specific features which could affect vehicle accident severity. In this paper, some of the classification models, specifically Logistic Regression, Artificial Neural network, Decision Tree, K-Nearest Neighbors, and Random Forest have been implemented for predicting the accident severity. All the models have been verified, and the experimental results prove that these classification models have attained considerable accuracy. The paper also explained a secure communication architecture model for secure information exchange among all the components associated with the ITS. Finally paper implemented web base Message alert system which will be used for alert the users through smart IoT devices.

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