To track vehicle’s location, various schemes have been proposed. In , a vehicletracking application is developed. The data collected from GPS receiver is sent to the web server via GPRS cellular network. When the users need to monitor their vehicles, a request is sent from an application to the web server, that will process these request and responds back to the requesting application. Since the application is server dependent, therefore server failure will cause serious problems. In vehicletracking device (VTD) , a user must send a message to a sim- card installed on VTD hardware. The user will get a reply from the VTD in terms of coordinates i.e., latitude and longitudes. The user clicks on received coordinates in order to view the location of a vehicle on google maps. In VTD, the absence of user friendly application makes it inappropriate for many users.
Vehicletracking systems are generally used in urban areas as these areas are heavily populated and developed. Now-a-days, the security of a vehicle is important as they are used to prevent from stealing. In this project we designed the vehicle tracing circuit. Number of vehicle tracing technologies is already implemented. We here are using the GSM and GPS modules to locate the vehicle location. Present location of the vehicle can be traced/received by getting coordinates from the satellite using GPS technology and transmitted through GSM in form of a message to parental mobile/sim.
To address the solution of vehicletracking at intersections and roundabouts, the Monte Carlo Markov Chain (MCMC), discussed in Section 3.7, method is used. The stochastic method was shown to perform well in scenes containing false mea- surements and in scenes containing missing measurements, also known as occlu- sions. The method also performs well when multiple tracks are in proximity to one another. Figure 4.4 shows the performance of MCMC under various conditions, including (a) only the true object positions, (b) the addition of ten percent false alarms, (c) in the presence of ten percent missing measurements and (d) a combina- tion of (b) and (c). Target points in the figures are coloured the same if they belong to the same track. False alarms are indicated using white. There is no relationship between the colours selected for a given track in each of the four figures.
A vehicletracking system consists of an electronic device installed on a vehicle so that it could be track by its owner or a third-party for its position. Most of todays vehicletracking system uses Global Positioning System (GPS) to get an accurate reading of the vehicle position. Communication components such as cellular (GSM) and satellite transmitter will be combined to transmit the vehicle’s position to remote user. Vehicle’s information can be viewed by using a software on a computer.
There is considerably greater use of vehicletracking for vans, and to a lesser extent heavy goods vehicles, than cars according to the respondents utilising the technology. In fact, four fifths of respondents tracked vans compared to just a third for cars, perhaps reflecting a more established and proven business case for van operators. Elsewhere, there still remains a low level of uptake for unpowered assets such as trailers and plant. (Fig 1)
Vehicletracking using the canny edge detector algorithm is used for detecting the edges. A Dynamic Bayesian Network (DBN) is constructed for classification purpose. A well trained DBN can estimate the probability of a pixel belonging to a vehicle or not. It also relates among neighboring pixels in a region. There is a fast growth in computer technology and increasing needs in security and studies of target vehicle detection in aerial surveillance using image processing techniques and based IPs and Location also it will work effectively in vehicletracking using HMA VPN.
Remote Asset Management Ltd is an award winning provider of user friendly vehicletracking. Last year RAM attended some of the regional SPATA meetings to present their unique GPS solution… and several members are now using the system to control costs and improve the efficiency of their operations. In fact, Portrait Pools have written a case study that highlights some of the key benefits of using the RAM system -
The Global Positioning System (GPS)/Global System for Mobile communication (GSM)/General Packet Radio Service (GPRS) Technology is used to prevent from the theft of any vehicle which is connected with this technology and to track the level of movement of vehicle from any location at any time3. This system makes use of smartphone environment and microcontroller. The system is in-built with the vehicle uses GPS, GSM and GPRS technology for vehicletracking. GPS and GSM/ GPRS modules are controlled by the microcontroller. In this system, a mobile application is developed to maintain and periodically monitor the vehicle place. The concept of a multilayered vehicular data cloud set up by obtainable and utilizing cloud computing and IoT technologies4,5. To make use of vehicle warranty analysis they proposed a methodology called a vehicular data mining cloud service and an intelligent parking cloud service in the IoT environment. To strengthen the vehicular data mining cloud service, they proposed two modified models which make use of a Naïve Bayes model and a Logistic Regression model. The smart investigation systems taking up the vision of the system and pattern appreciation systems are organized to deliver intellectual video analysis and uncontrolled object finding, to increase public security. From the previous smart surveillance techniques, the methodologies that they have installed in the few places and here the methodologies are Automatic License Plate Recognition (ALPR). Few of techniques can provide big scale data retrieval across wide area, integration and data analysis to achieve intelligent urban surveillance. In6, used a novel system called Snake Eyes, which aspires to carry together automatic license plate recognition engines and to realize massive data analysis using cloud computing technology. The vehicle in a town or any place with a given license number targeted by enabled detection and tracking system which can grandly make things easier and gather speed the process of fetching security issues.
The aim of this project is to design & develop a vehicletracking system using GPRS which can be easily controlled by arduino uno. In this modern, fast moving and insecure world, it is became a basic necessity to be aware of one’s safety. The number of vehicles also increases on roads and highways. The proposed system is a GPS based real time vehicletracking system, is used for security applications as well as any organization that maintains a large fleet and wants accurate real-time information about vehicle position.
Many companies find that installing GPS vehicletracking on their fleet vehicles provides one sure way to improve safety. GPS tracking offers a wide variety of features and benefits that businesses with vehicle fleets can utilize to significantly improve their safety records and protect their business from undue costs.
The software algorithm of real time vehicletracking system is described here the ID for every individual. The variables are initialized and the serial port is connected for transmitting the data. The baud for serial transmission is 9600. The Google map is displayed in the official domain name website created. The GSM will send the information message to the remote domain. Encryption and decryption algorithms are used to transmitting the data to the domain securely.
ABSTRACT: Vehicle accidents are one of the most leading causes of fatality. The time between an accident occurrence and the emergency medical personnel are dispatched to the accident location is the important factor in the survival rates after an accident. By eliminating that time between an accident occurrence and the first responders are dispatched to the scene decreases mortality rates so that we can save lives. One approach to eliminate that delay between accident occurrence and first responder dispatch is to use An Accident Alert and VehicleTracking System, which sense when a traffic accident is likely to occur and immediately notify emergency occurred. In this paper, that system is described the main application of which is early accident detection. In this system, initially the GPS continuously takes input data from the satellite and stores the latitude and longitude values in ATmega16 microcontroller's buffer. If we have to track the vehicle, we need to send a message to GSM device, by which it gets activated. It also gets activated by detecting accident on the shock sensor connected to Raspberry Pi. Parallely deactivates GPS with the help of relay .Once GSM gets activated it takes the last received latitude and longitude positions values from the buffer and sends a message to a central emergency dispatch server which is predefined in the program. This system uses the things i.e. Raspberry Pi, Vibration Sensors, GPS and GSM modules to detect traffic accidents.
ecurity in general is a major concern in our society today. Every day, people purchase vehicles for different purposes, but for which ever reason, a lot of money is spent in the transaction which demands that adequate provision should be provided for its security and safety (Bajaja et al. 2012). Auto theft is a serious crime which is getting rampant day after day. It is then necessary for car users everywhere to have a way to track down their cars in case it is ever stolen. Real Time VehicleTracking System is one of the measures of securing vehicles. The word tracking means to find or follow something, therefore, Real time vehicletracking is a method used to track and monitor any remote vehicle equipped with a hardware unit that receives and transfers signals through global positioning system (GPS) satellite. It makes use of GPS to provide actual geographic real time position of each vehicle.
In recent years, vehicletracking has been applied in traffic surveillance with the intention of gaining traffic flow information, capturing traffic violations, and classifying vehicles. Vehicletracking is an undertaking that can open up possibilities for countless other applications. For example, a traffic surveillance camera attached to a traffic light could detect and track vehicles and not be affected by pedestrians. However, we could also configure the image processing system to detect pedestrians and ignore vehicles. It’s this versatility that makes image processing a preferred alternative to other detecting methods.
Duty of care… corporate manslaughter… the Working Time Directive… with a wide range of new legislation already in place or on the horizon, businesses are increasingly looking to the latest vehicletracking technology to help them fulfil their legal obligations, as well as manage their fleet more effectively. But how do you overcome initial objections from staff over privacy and human rights? The following guide outlines the most important steps to take when introducing a telematics system to your fleet and arms you with 10 key reasons why tracking is good news for drivers, as well as management.
Recently, the lower costs and the increasing capabilities of the RFID technique attract attention in keeping track and monitoring the containers in the terminal (Hsu, Shih & Wang, 2009; Park, Dragovic & Kim, 2009; Ngai et al., 2010). Woo, Choi, Kwak and Kim (2009) proposed an activity product state tracking system architecture which is able to track products even when they are in a box or a container. Abad et al. (2009) developed an RFID-based system for traceability and cold chain monitoring of food. Wang et al. (2009) proposed a RFID-based decision support system to monitor, trace and track products in containers. Chao and Lin (2009) analyzed critical factors affecting the adoption of a container security service, which is composed of auto-detection and RFID technologies, from the shippers’ perspective. Cao and Xiao (2011) analyzed a propagation prediction model and the performance of a container RFID system under metallic container production circumstances. These applications encourage study of RFID to realize vehicletracking in container terminals. However, although numerous studies involving the installation of RFID have demonstrated the benefits of better container handling efficiency, a relative lack of research concerning tracking and monitoring vehicle movement in the container terminal environment is appearance.
Due to lack of research about Electrical Vehicletracking system, research about vehicletracking system that similar to Electrical Vehicletracking system wan done. In order to understand more about the vehicletracking system technology, research about current vehicle system was done. The vehicle include of bus, van, car and others. In April 2009, two University of Washington (UW) graduate students, Brian Ferris and Kari Watkins have developed a tool named OneBusAway that allow King Country Metro Transit riders to track the bus. To use this service, one must send the bus stop number to the server, later the server will reply with real-time arrival data of the bus.
This vehicletracking system is warranted to the original purchaser, to be free from defects in material and workmanship. The manufacturer will repair or replace at its option, and free of charge for the first twelve (12) months, any part that proves defective in material or workmanship under normal installation, use, and service, provided the product is returned to the manufacturer freight prepaid. After the first 12 month warranty period there will be a maximum service charge of $100.00 per calendar year (if required) for repair and/or replacement of any defective parts. A copy of the original purchase and installation receipt must accompany any products returned for warranty service. Warranty is limited to defective parts and/or replacement parts only and excludes any incidental, and consequential damages connected therewith.
Abstract: Multicamera vehicletracking is a necessary part of any video-based intelligent transportation system for extracting different traffic parameters; such as link travel times and origin/destination counts. In many applications, it is needed to locate traffic cameras disjoint from each other to cover a wide area. This paper presents a method for tracking moving vehicles in such camera networks. The proposed method introduces a new method for handling inter-object occlusions; as the most challenging part of the single camera tracking phase. This approach is based on coding the silhouette of moving objects before and after occlusion and separating occluded vehicles by computing the longest common substring of the related chain codes. In addition, to improve the accuracy of the tracking method, in the multicamera phase, a new feature based on the relationships among surrounding vehicles is introduced. The proposed feature is modeled by an exponential distribution and can efficiently improve the efficiency of the appearance (space-time) features when they cannot discriminate between correspondent and non-correspondent vehicles; due to noise or dynamic condition of traffic scenes. A graph-based approach is then used to track vehicles in the camera network. Experimental results show the efficiency of the proposed method.
A new variation to the RLS algorithm is presented. In the clipped RLS algorithm (CRLS), proposed in updating the filter weights and computation of the inverse correlation matrix, the input signal is quantized into three levels. The convergence of the CRLS algorithm to the optimum Wiener weights is proved. The computational complexity and signal estimation error is lower than that of the RLS algorithm. The CRLS algorithm is used in the estimation of a noisy chirp signal and in vehicles tracking. Simulation results in chirp signal detection shows that this algorithm yields considerable error reduction and less computation time in com- parison to the conventional RLS algorithm. In the presence of strong noise, also using the proposed algorithm in tracking of 59 vehicles shows an average of 3.06% reduction in prediction error variance relative to conventional RLS algorithm.