Sensory Data Gathering for Road Traffic Monitoring: Energy Efficiency, Reliability, and Fault Tolerance
01 Jan 2015-pp 89-112
TL;DR: In this Chapter, a novel tree-based data gathering scheme has been proposed, exploiting the strip-like structure of the road network, and an efficient scheduling mechanism is implemented to assure both the coverage and the critical power savings of the sensor nodes.
Abstract: Vehicular traffic monitoring and control using through road sensor network is challenging due to a continuous data streaming over the resource constrained sensor devices. The delay sensitivity and reliability of the large volume of application data as well as the scarcity of sensor resources demand efficient designing of data collection protocol. In this Chapter, a novel tree-based data gathering scheme has been proposed, exploiting the strip-like structure of the road network. An efficient scheduling mechanism is implemented to assure both the coverage and the critical power savings of the sensor nodes. The network connectivity is guaranteed throughout by the proposed tree maintenance module that handles the dynamics of the network as a result of sensor node joining and leaving events. An application message controller has been designed that works cooperatively with the tree management module, and handles continuous streaming of the application data to ensure no loss or redundancy in data delivery. The performance of the proposed scheme is evaluated using the simulation results and compared with other approaches for large data collection in sensor network.
Citations
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16 Dec 2022
TL;DR: In this article , the authors proposed an efficient traffic monitoring system, which can detect the vehicle flow on the roads in real time, which has three made components including evaluating vehicle density that is based on background subtraction procedures.
Abstract: Traffic analysis true video monitoring is quite a complex job. The reason for the same include different appearances, light changes, and variation in speeds. This paper proposed an efficient traffic monitoring system, which can detect the vehicle flow on the roads in real time. This system has three made components including evaluating vehicle density that is based on background subtraction procedures. the second component evaluate the speed of the traffic flow using optical flow mechanism first up the third component includes evaluating the number of vehicles using improved differential approach. From the fundamental information extracted, our system can predict events such as high traffic zones, vehicles over speeding and many more. The simulation is conducted by using the traffic data set derived from Kaggle.
References
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23 Nov 2015
TL;DR: The most representative technologies and research results achieved by some of the most relevant research groups working on ITS are combined to show the chances of generating industrial solutions to be deployed in real transportation environments.
Abstract: The book provides a systematicoverview of Intelligent Transportation Systems (ITS). First, it includes aninsight into thereference architectures developed within the main EU research projects. Then, it delves into each of the layers of such architectures, from physical to application layer, describing the technological issues which are being currently faced by some of the most important ITS research groups. The bookconcludes with some end user services and applications deployed by industrial partners. This book is a well-balanced combination of academic contributions and industrial applications in the field of Intelligent Transportation Systems. The most representative technologies and research results achieved by some of the most relevant research groups working on ITS,collated to show the chances of generating industrial solutions to be deployed in real transportation environments.
142 citations
Dissertation•
01 Jan 2000
TL;DR: A wireless sensor package to instrument roadways for Intelligent Transportation Systems counts passing vehicles, measures the average roadway speed, and detects ice and water on the road, and includes a custom-designed, compact, broadband, inexpensive printed circuit microstrip antenna for the 915 MHz ISM band.
Abstract: We have developed a wireless sensor package to instrument roadways for Intelligent Transportation Systems. The sensor package counts passing vehicles, measures the average roadway speed, and detects ice and water on the road. Clusters of sensors can transmit this information in near real-time to wired base stations for use controlling and predicting traffic, and in clearing road hazards. The sensor package draws a maximum time-averaged current of 17 tA from an internal lithium battery, allowing it to operate in the roadbed for at least 10 years without maintenance. The nodes cost well under $30 to manufacture, and can be installed without running wires under the road, facilitating wide deployment. Unlike many other types of traffic sensors, these sensors count vehicles in bumper-to-bumper traffic just as well as in widely separated traffic. The devices detect vehicles by detecting the perturbations in the Earth's magnetic field caused by the vehicles. They measure this perturbation using an anisotropic magnetoresistive magnetic field sensor. The radio transmitters in the sensor are frequency-agile, and the sensors use a randomized sparse TDMA protocol, which allows several transmit-only devices to share a channel. The sensor package includes a custom-designed, compact, broadband, inexpensive printed circuit microstrip antenna for the 915 MHz U.S. ISM band. We built a prototype sensor package, and installed it in a pothole in a city street. We used the sensor to monitor the traffic flow rate during free-flowing traffic and a traffic jam. Thesis Supervisor: Joseph Paradiso Title: Principal Research Scientist, MIT Media Lab
122 citations
Proceedings Article•
12 Apr 2011TL;DR: The paper describes the hw/sw architecture devised by focusing on the WSN component, and analyzes its performance through experiments in a real, operational tunnel.
Abstract: Existing deployments of wireless sensor networks (WSNs) are often conceived as stand-alone monitoring tools. In this paper, we report instead on a deployment where the WSN is a key component of a closed-loop control system for adaptive lighting in operational road tunnels. WSN nodes along the tunnel walls report light readings to a control station, which closes the loop by setting the intensity of lamps to match a legislated curve. The ability to match dynamically the lighting levels to the actual environmental conditions improves the tunnel safety and reduces its power consumption. The use of WSNs in a closed-loop system, combined with the real-world, harsh setting of operational road tunnels, induces tighter requirements on the quality and timeliness of sensed data, as well as on the reliability and lifetime of the network. In this work, we test to what extent mainstream WSN technology meets these challenges, using a dedicated design that however relies on well-established techniques. The paper describes the hw/sw architecture we devised by focusing on the WSN component, and analyzes its performance through experiments in a real, operational tunnel.
120 citations
TL;DR: An experimental data analysis reported in this study shows how the high spatial resolution of WSN-based traffic monitoring can enhance the reliability of traffic modelling as well as the accuracy of short-term traffic state prediction.
Abstract: Wireless sensor networks (WSN) employ self-powered sensing devices that are mutually interconnected through wireless ad-hoc
technologies. This study illustrates the basics of WSN-based traffic monitoring and summarises the possible benefits in Intelligent Transport Systems (ITS) applications for the improvement of quality and safety of mobility. Compared with conventional infrastructure-based monitoring systems, this technology facilitates a denser deployment of sensors along the road, resulting in a higher spatial resolution of traffic parameter sampling. An experimental data analysis reported in this study shows how the high spatial resolution can enhance the reliability of traffic modelling as well as the accuracy of short-term traffic state prediction. The analysis uses the data published by the freeway performance measurement system of the University of California-Berkeley and the California Department of Transportation. A microscopic cellular automata model is used to estimate traffic flow and occupancy over time on a road segment in which a relevant traffic-flow anomaly is detected. The analysis shows that the estimate accuracy improves for increasing number of active sensors, as feasible in the case of WSN-based monitoring systems.
115 citations
Proceedings Article•
01 Jan 2011
108 citations