Adaptive Traffic Density Management System

2018 ◽  
Vol 06 (03) ◽  
pp. 173-176
Author(s):  
A Keerthi Infanta Francy ◽  
S Visalachi ◽  
R Deepa
Keyword(s):  
Management System ◽  
Traffic Density

scholarly journals Advanced Traffic Management System using A Fuzzy Logic Controller to Differentiate Parking Vehicle and Moving Vehicle

2020 ◽  
Vol 9 (5) ◽  
pp. 488-494
Keyword(s):  
Fuzzy Logic ◽  
Internet Of Things ◽  
Traffic Management ◽  
Management System ◽  
Fuzzy Logic Controller ◽  
Fuzzy Controller ◽  
Smart Cities ◽  
Traffic Density ◽  
Moving Vehicle ◽  
Traffic Management System

In smart cities, traffic congestion is one of the significant problems for citizens. Traffic management is an essential one for the quick development of populace and urban movement in metropolitan areas, and traffic blockage is often seeming on streets. To handle different issues for managing traffic on the streets and to help experts in inappropriate arrangement, a smart traffic management system with the IoT (Internet of Things) is proposed in this paper. Mechanisms to utilize IR sensors to distinguish traffic density isn't easy as smooth a solo vehicle recognized at the last sensor so that it can suggest traffic density in high in any event, even if there is free space before it. A technique to be proposed to solve the previously mentioned issues efficiently is by utilizing the Internet of things for traffic management systems. This paper aims to propose a Fuzzy controller to deal with traffics in smart cities. Fuzzy induction used to compute exact traffic, which separates the parking vehicle and moving vehicle. There is an issue of separating parking and un-parking vehicles in the existing systems. So, we planned to solve this using fuzzy logic.

scholarly journals Efficient Traffic Management System

2018 ◽  
Vol 7 (3.12) ◽  
pp. 926
Author(s):  
Suraj Kumar G Shukla ◽  
Aadithya Kandeth ◽  
D Sai Santhiya ◽  
Kayalvizhi Jayavel
Keyword(s):  
Image Processing ◽  
Traffic Congestion ◽  
Traffic Management ◽  
Management System ◽  
Large Scale ◽  
Traffic Signals ◽  
Input Image ◽  
Traffic Density ◽  
Use Of Technology ◽  
Traffic Management System

Traffic Management is a big issue which impacts us almost daily. Use of technology such as IoT and image processing can lead to a smooth traffic management system. The common reason for traffic congestion is due to the lack of an efficient traffic prioritization system. The internet of things is a network of devices. The embedded systems includes sensors, actuators, and electronics.With software and connectivity locally or over internet  helps in  transfer of data. Each of these devices is uniquely identifiable in the network and are highly interoperable. Image processing using OpenCV is a technique that is used to process an input image and obtain the traffic densities along various lanes in a junction. Existing traffic management solutions include using RFID tags on vehicles to obtain a vehicle count. This can also be done using ultrasonic sensors. The problem with these methods is that when implemented in a large scale, the cost of the entire system can be exponentially higher than an image processing approach as each vehicle will have to be fitted with an RFID tag. Hence, implementing this model at a largescale level, for example in a metropolitan city will be time consuming and expensive. This has led to the development of our algorithm, which uses image processing and IoT along with CCTV cameras. This system is efficient, as it uses CCTV cameras that are already present in traffic signals of most major metropolitan cities. Hence implementing the system at a largescale level is feasible. This algorithm also takes care of corner cases like heavy utility vehicles and motorbikes. It can also be used at night and during unfavorable weather conditions.The algorithm used detects the density of traffic as opposed to the count of vehicles by taking input images from a CCTV camera, comparing it with a sample image of an empty road and obtaining a match percentage. The traffic density can be found easily using this since it has a disproportionate relation with the match percentage. The traffic signals can be altered accordingly using the traffic density. The output is then sent to the ThingSpeak cloud where it can be analyzed.

scholarly journals Simulation Study on an ICT-Based Maritime Management and Safety Framework for Movable Bridges

2021 ◽  
Vol 11 (16) ◽  
pp. 7198
Author(s):  
Md Mostafizur Rahman Komol ◽  
Md Samiul Islam Sagar ◽  
Naeem Mohammad ◽  
Jack Pinnow ◽  
Mohammed Elhenawy ◽  
...  
Keyword(s):  
Control System ◽  
Traffic Management ◽  
Management System ◽  
Transportation Policy ◽  
Transportation Safety ◽  
Traffic Density ◽  
Simulation Platform ◽  
Vehicle Traffic ◽  
Vehicle Management ◽  
Movable Bridge

Maritime management is a crucial concern for movable bridge safety. Irregular management of water vehicles near movable bridges may lead to collision among ships and bridge infrastructures, causing massive losses of life and property. The paper presents a theoretical framework and simulation of an intelligent water vehicle management system for movable bridges corresponding to vehicle traffic responses. The water regime around the bridge is considered in virtually separated domains to estimate the desired safety actions based on the position of the approaching ships. An emergency clash avoidance control system is represented to prevent ship-infrastructure collision and ensure transportation safety. In addition, a simulation platform is developed specifically adaptable for movable bridge maritime and dynamic traffic management. The proposed theory is experimented using the simulation platform for different ship speeds and bridge-vehicle traffic volumes. Based on analyzing the velocity profile of approaching ships at different incidents, the bridge is found incapable of evacuating vehicles and unable to open promptly in case of speeding ships and high traffic density of vehicles on the bridge. Computational results show that the emergency control system is effective in reducing ship speed and prevent certain collisions. Lastly, the transportation policy for the newly proposed maritime management system is validated by real-world implementation in movable bridges across the world.

scholarly journals IoT based Road Traffic Management System for Metropolitan Cities

2020 ◽  
Vol 8 (12s3) ◽  
pp. 75-79
Keyword(s):  
Traffic Congestion ◽  
Traffic Management ◽  
Management System ◽  
Road Traffic ◽  
Traffic Density ◽  
The Road ◽  
Metropolitan Cities ◽  
Traffic Management System ◽  
Road Traffic Congestion ◽  
Jamming Problems

Many cities in the world face jamming problems in road traffic, particularly in metropolitan cities. At present the traffic controlling systems aresemiautomatic in nature. With the introduction of IoT in road traffic management systems, it revolutionizes the field of road traffic management system and improves the road traffic congestion problem.This paper proposes an IoT-based road traffic management system for metropolitan cities. The proposed system provides the hassle free movement of the vehicles to avoid inconvenience and reroute the higher priority vehicles. Experimental results show that the proposed system gives higher success rate for the low traffic density in the lane.

Abstract #1228: E-Glycemic Management System Provides Safe and Effective Meal Coverage for Critical Care and Surgery Patients Managed with IV Insulin in the Hospital

2015 ◽  
Vol 21 ◽  
pp. 288-289
Author(s):  
Joseph Aloi ◽  
Jagdeesh Ullal ◽  
Paul Chidester ◽  
Raymie McFarland ◽  
Robby Booth
Keyword(s):  
Critical Care ◽  
Management System ◽  
Glycemic Management

Abstract #1306: Improved Inpatient Hypoglycemia Rates with Electronic Glycemic Management System

2016 ◽  
Vol 22 ◽  
pp. 328
Author(s):  
Joseph Aloi ◽  
Jagdeesh Ullal ◽  
Paul Chidester ◽  
Amy Henderson ◽  
Robby Booth ◽  
...  
Keyword(s):  
Management System ◽  
Glycemic Management
Sign in / Sign up

Export Citation Format

Share Document