A Wireless Sensor Network-Based Portable Vehicle Detector Evaluation System
17 Jan 2013-Sensors (Multidisciplinary Digital Publishing Institute (MDPI))-Vol. 13, Iss: 1, pp 1160-1182
TL;DR: The architecture and design of a Portable Vehicle Detector Evaluation System and the implementation results, focusing on the wireless sensor networks and methods for traffic information measurement, show that it can evaluate a Vehicle Detection System conveniently and objectively.
Abstract: In an upcoming smart transportation environment, performance evaluations of existing Vehicle Detection Systems are crucial to maintain their accuracy. The existing evaluation method for Vehicle Detection Systems is based on a wired Vehicle Detection System reference and a video recorder, which must be operated and analyzed by capable traffic experts. However, this conventional evaluation system has many disadvantages. It is inconvenient to deploy, the evaluation takes a long time, and it lacks scalability and objectivity. To improve the evaluation procedure, this paper proposes a Portable Vehicle Detector Evaluation System based on wireless sensor networks. We describe both the architecture and design of a Vehicle Detector Evaluation System and the implementation results, focusing on the wireless sensor networks and methods for traffic information measurement. With the help of wireless sensor networks and automated analysis, our Vehicle Detector Evaluation System can evaluate a Vehicle Detection System conveniently and objectively. The extensive evaluations of our Vehicle Detector Evaluation System show that it can measure the traffic information such as volume counts and speed with over 98% accuracy.
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TL;DR: A comprehensive study of wireless sensor networks' deployment in urban areas and discusses the merits and demerits of WSN architectures in urban environments.
Abstract: As new wireless technologies become more and more advance so does their expanse of applications. Among other new and innovative wireless networks, Wireless Sensor Networks (WSNs) have emerged as highly flexible and dynamic facets that are being deployed in almost every type of environment whether it is rural, suburban or urban in nature. The most adaptive and innovative research avenues are being considered in an urban environment, where WSN deployment is especially demanding due to its harsh and perverse channel conditions. We have chosen WSN deployment in an urban environment as linchpin of our research. As each application scenario is different from the other, therefore WSN solution for each application has to be adaptive and innovative. We have discussed each application of WSNs in urban areas in detail with all the problems related to it and in the end, technical solution to those problems has been discussed. Graphical abstractDisplay Omitted HighlightsWe have performed a comprehensive study of wireless sensor networks' deployment in urban areas.We have discussed the merits and demerits of WSN architectures in urban environments.We have discussed the wireless sensor based solutions already deployed by researchers that are optimal for urban environments.
594 citations
25 Feb 2020
TL;DR: The purpose of this article is to provide an up-to-date presentation of both traditional and most recent applications of Wireless Sensor Networks to enable the comprehension of this scientific area and facilitate the perception of novel applications.
Abstract: Wireless Sensor Networks are considered to be among the most rapidly evolving technological domains thanks to the numerous benefits that their usage provides. As a result, from their first appearance until the present day, Wireless Sensor Networks have had a continuously growing range of applications. The purpose of this article is to provide an up-to-date presentation of both traditional and most recent applications of Wireless Sensor Networks and hopefully not only enable the comprehension of this scientific area but also facilitate the perception of novel applications. In order to achieve this goal, the main categories of applications of Wireless Sensor Networks are identified, and characteristic examples of them are studied. Their particular characteristics are explained, while their pros and cons are denoted. Next, a discussion on certain considerations that are related with each one of these specific categories takes place. Finally, concluding remarks are drawn.
282 citations
TL;DR: This paper presents a system based on WSN designed to characterize urban traffic, particularly traffic trend monitoring through the calculation of the origin-destination matrix in real time by using Bluetooth identification.
Abstract: Sustainable mobility requires a better management of the available infrastructure resources. To achieve this goal, it is necessary to obtain accurate data about road usage, in particular in urban areas. Although a variety of sensor alternates for urban traffic exist, they usually require extensive investments in the form of construction works for installation, processing means, etc. Wireless Sensor Networks (WSN) are an alternative to acquire urban traffic data, allowing for flexible, easy deployment. Together with the use of the appropriate sensors, like Bluetooth identification, and associate processing, WSN can provide the means to obtain in real time data like the origin-destination matrix, a key tool for trend monitoring which previously required weeks or months to be completed. This paper presents a system based on WSN designed to characterize urban traffic, particularly traffic trend monitoring through the calculation of the origin-destination matrix in real time by using Bluetooth identification. Additional sensors are also available integrated in different types of nodes. Experiments in real conditions have been performed, both for separate sensors (Bluetooth, ultrasound and laser), and for the whole system, showing the feasibility of this approach.
45 citations
TL;DR: Piezoelectric acceleration sensors, based on the same measuring principle as MEMS accelerometers, are used with the objective to analyze in detail the amplitudes and frequency ranges in which vibrations occur, and the algorithms to determine the presence of vehicles, their travel direction, and speed are developed.
Abstract: The study of vehicular traffic is essential for modern cities to determine the efficiency of their current roads and to plan new infrastructure that keeps the mobility of its inhabitants. Technologies that provide detailed data of the current situation on the roads are needed to reduce journey times and pollution emissions and consequently improve the quality of life of the people. Smart streets featuring sensor networks offer the possibility to study with high accuracy the traffic conditions on every point of the road. Using sensor networks parameters like speed, travel direction, and type of vehicles can be precisely calculated. Furthermore, it is possible to determine in real time the peak hours and the site of accidents. Different sources such as sound, magnetism, or vibrations can be used to monitor the traffic flow. From them, road vibrations are of special interest because of their potential for energy harvesting by using piezoelectric films and thus reducing the dependence on external power sources. This paper presents a study that provides the bases to develop a 2-D sensor network using MEMS accelerometers placed on the width and length of the road surface to monitor continuously the traffic flow. In this paper, piezoelectric acceleration sensors, based on the same measuring principle as MEMS accelerometers, are used with the objective to analyze in detail the amplitudes and frequency ranges in which vibrations occur. From this information, the algorithms to determine the presence of vehicles, their travel direction, and speed are developed.
28 citations
Cites background from "A Wireless Sensor Network-Based Por..."
...Examples of studies that use sensor networks as traffic detectors are given in [6] and [7] in which the magnetic signature of vehicles is used to monitor the traffic conditions....
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...Magnetic sensors as proposed in [7] can provide up to 98%...
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TL;DR: Investigations indicate that the number of sensors needed in a non-uniform topology is much less than that in a uniform one, and compared with a random scheme, simulation results further verify the advantage of the deployment model.
Abstract: Sensor-deployment-based lifetime optimization is one of the most effective methods used to prolong the lifetime of Wireless Sensor Network (WSN) by reducing the distance-sensitive energy consumption. In this paper, data retransmission, a major consumption factor that is usually neglected in the previous work, is considered. For a homogeneous WSN, monitoring a circular target area with a centered base station, a sensor deployment model based on regular hexagonal grids is analyzed. To maximize the WSN lifetime, optimization models for both uniform and non-uniform deployment schemes are proposed by constraining on coverage, connectivity and success transmission rate. Based on the data transmission analysis in a data gathering cycle, the WSN lifetime in the model can be obtained through quantifying the energy consumption at each sensor location. The results of case studies show that it is meaningful to consider data retransmission in the lifetime optimization. In particular, our investigations indicate that, with the same lifetime requirement, the number of sensors needed in a non-uniform topology is much less than that in a uniform one. Finally, compared with a random scheme, simulation results further verify the advantage of our deployment model.
17 citations
References
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01 May 2005
TL;DR: In this paper, a survey and evaluation of clock synchronization protocols based on a palette of factors such as precision, accuracy, cost, and complexity is presented, which can help developers either in choosing an existing synchronization protocol or in defining a new protocol that is best suited to the specific needs of a sensor network application.
Abstract: Recent advances in micro-electromechanical (MEMS) technology have led to the development of small, low-cost, and low-power sensors Wireless sensor networks (WSNs) are large-scale networks of such sensors, dedicated to observing and monitoring various aspects of the physical world In such networks, data from each sensor is agglomerated using data fusion to form a single meaningful result, which makes time synchronization between sensors highly desirable This paper surveys and evaluates existing clock synchronization protocols based on a palette of factors like precision, accuracy, cost, and complexity The design considerations presented here can help developers either in choosing an existing synchronization protocol or in defining a new protocol that is best suited to the specific needs of a sensor-network application Finally, the survey provides a valuable framework by which designers can compare new and existing synchronization protocols
1,018 citations
01 Jul 2004
TL;DR: In this article, a medium access control scheme, called PEDAMACS, is proposed for a class of sensor networks with two special characteristics: the nodes periodically generate data for transfer to a distinguished node called the access point, and the nodes are (transmit) power and energy limited.
Abstract: We consider a class of sensor networks with two special characteristics. First, the nodes periodically generate data for transfer to a distinguished node called the access point. Second, the nodes are (transmit) power and energy limited, but the access point, which communicates with the 'outside world', is not so limited. Such networks might be used for instance when a geographically distributed physical process, such as traffic on a freeway or at an urban street intersection, is periodically sensed for purposes of process control. We propose a medium access control scheme, called PEDAMACS, for this special class of networks. PEDAMACS uses the high-powered access point to synchronize the nodes and to schedule their transmissions and receptions in a TDMA manner. The protocol first enables the access point to gather topology (connectivity) information. A scheduling algorithm then determines when each node should transmit its data, and the access point announces the transmission schedule to the other nodes. The scheduling algorithm ideally should minimize the delay-the time needed for data from all nodes to reach the access point. However, this optimization problem is NP-complete. PEDAMACS instead uses a polynomial-time scheduling algorithm which guarantees a delay proportional to the number of nodes in the sensor network. Because PEDAMACS schedules node transmissions, its performance is much better than that of protocols designed for more general contention (or random access) networks in terms of power consumption, delay, fairness, and congestion control. The comparison is based on simulations in TOSSIM, a simulation environment for TinyOS, the operating system for the Berkeley sensor nodes. For the traffic application we consider, the PEDAMACS network provides a lifetime of several years compared to several months and days based on random access schemes with and without sleep cycles respectively, making sensor network technology economically viable.
344 citations
TL;DR: For the traffic application the authors consider, the PEDAMACS network provides a lifetime of several years compared to several months and days based on random access schemes with and without sleep cycles, respectively, making sensor network technology economically viable.
Abstract: PEDAMACS is a Time Division Multiple Access (TDMA) scheme that extends the common single hop TDMA to a multihop sensor network, using a high-powered access point to synchronize the nodes and to schedule their transmissions and receptions. The protocol first enables the access point to gather topology (connectivity) information. A scheduling algorithm then determines when each node should transmit and receive data, and the access point announces the transmission schedule to the other nodes. The performance of PEDAMACS is compared to existing protocols based on simulations in TOSSIM, a simulation environment for TinyOS, the operating system for the Berkeley sensor nodes. For the traffic application we consider, the PEDAMACS network provides a lifetime of several years compared to several months and days based on random access schemes with and without sleep cycles, respectively, making sensor network technology economically viable.
289 citations
01 Sep 2004
TL;DR: In this paper, the authors used magnetic sensor networks for traffic measurement in freeways and intersections, and reported that the vehicle detection rate was better than 99 percent (100 percent for vehicles other than motorcycles).
Abstract: Wireless magnetic sensor networks offer a very attractive, low-cost alternative to inductive loops for traffic measurement in freeways and at intersections. In addition to vehicle count, occupancy and speed, the sensors yield traffic information (such as vehicle classification) that cannot be obtained from loop data. Because such networks can be deployed in a very short time, they can also be used (and reused) for temporary traffic measurement. This paper reports the detection capabilities of magnetic sensors, based on two field experiments. The first experiment collected a two-hour trace of measurements on Hearst Avenue in Berkeley. The vehicle detection rate is better than 99 percent (100 percent for vehicles other than motorcycles); and estimates of vehicle length and speed appear to be better than 90 percent. Moreover, the measurements also give inter-vehicle spacing or headways, which reveal such interesting phenomena as platoon formation downstream of a traffic signal. Results of the second experiment are preliminary. Sensor data from 37 passing vehicles at the same site are processed and classified into 6 types. Sixty percent of the vehicles are classified correctly, when length is not used as a feature. The classification algorithm can be implemented in real time by the sensor node itself, in contrast to other methods based on high scan-rate inductive loop signals, which require extensive offline computation. We believe that when length is used as a feature, 80-90 percent of vehicles will be correctly classified.
247 citations