TRUCK TRACKING AND ALERTS MONITORING SYSTEM

Transcription

1 International Journal of Civil Engineering and Technology (IJCIET) Volume 9, Issue 11, November 2018, pp , Article ID: IJCIET_09_11_011 Available online at ISSN Print: and ISSN Online: IAEME Publication Scopus Indexed TRUCK TRACKING AND ALERTS MONITORING SYSTEM V. Kanchana Devi School of Computer Science and Engineering, VIT University Chennai, India A. David Maxim Gururaj* Mathematics Division, School of Advanced Sciences, VIT University Chennai, India A. Kavya School of Computer Science and Engineering, VIT University Chennai, India E. Umamaheswari School of Computer Science and Engineering, VIT University Chennai, India *Corresponding Author ABSTRACT Tracking vehicles is becoming more essential in the present world of logistics market, as delay in delivery and pick-up of goods is costing more especially for startups. Keeping track of the vehicles help in managing resources in a more efficient way, and increasing profit. The tracking must be done in a more efficient way with less latency. This work proposes an online GPS vehicle tracking framework which tracks vehicles continuously. This work outputs vehicles status, position and also includes features like driver well-being by observing the level of vehicle control, weariness anticipation utilizing the EYE-BLINK and MEMS sensor. The proposed system stores the complete details about the travel of a vehicle like the route, distance travelled, driver control over the vehicle, and the cautions happened. This work will help in understanding the condition of the vehicle and the driver efficiency also. Key words: Vehicle Tracking, Vehicle Condition Monitoring, Sensors, GSM - Global System for Mobile, GPS - Global Positioning System, Location Monitoring. Cite this Article: V. Kanchana Devi, A. David Maxim Gururaj, A. Kavya, E. Umamaheswari, Truck Tracking and Alerts Monitoring System, International Journal of Civil Engineering and Technology (IJCIET) 9(11), 2018, pp INTRODUCTION The proposed methodology is about the truck administration and alerts monitoring, in which a web application is developed for an organization to track the location of their vehicles. In this, the proprietor or the person in-charge for tracking vehicles will be able to view the location of editor@iaeme.com

2 Truck Tracking and Alerts Monitoring System a vehicle on multiple devices like mobile, desktop and tablet. The owner of a vehicle can also view the cautions given to the driver of a particular vehicle. With quick increment in the vehicles it is necessary to automate the tracking process, this will also help in tracking theft and hijacking of vehicles. This will also help in finding out the efficiency of the driver in maintaining the time and skills in handling the vehicle. This will also help in finding out if the driver has exercised any non-business related works which has in-term delayed the trip. This will help the vehicle owners in tracking a device from a remote location anywhere anytime. This work also observes the driver well-being by observing the level of vehicle control, weariness anticipation by using EYE-BLINK and MEMS sensor [1]. By using these sensors, alerts will be given to the drivers when there is a possibility of disaster. These entire data of will be saved in cloud for processing in finding out ways to improve the vehicle and driver efficiency [2] [3]. The condition of vehicles can also be assessed using the cloud [4] data and special training can be given to drivers if their driving patterns are delaying the trips. 2. ARCHITECTURE Figure 1 System Architecture 3. VEHICLE TRACKING The most important module in the proposed system is to track the truck and monitor in web application using IoT devices. The vehicle direction is observed using accelerometer sensor or MEMS sensor [5][6]. The following framework gives the position of vehicles in a more accurately. The objective of this module is to track vehicles and screen the location details using the programming unit that gets the data and exchanges motion through GPS satellite[7] [8]. Programmed vehicle area framework utilized online, portable correspondence and Web based stage for correspondence. This framework empowers to gather and examine the data about area of vehicle progressively. It is equipped for following an extensive number of transports at the same time and distinguishes the stationary truck naturally. Tilt sensor is also used to check the condition of the vehicle, thereby alerting the system in case of any emergencies [9] [10]. A neural system obtains the satellite related data to get a yield flag illustrative of recipient related route data, where in the neural system involves one of the versatile learning for the blunder decrease and ideal count[11] [12]. This system enhances the normal precision of GPS flag gathering at the transport station. The constant vehicle monitoring framework includes GPS module deployed in the vehicles, which transmits the ongoing area of vehicle to the collector sheets deployed in the vehicle stops [13] [14]. The editor@iaeme.com

3 V. Kanchana Devi, A. David Maxim Gururaj, A. Kavya, E. Umamaheswari GPS information of the vehicle areas is send to servers and the same is updated same in the web application for the organization to monitor. Fig 1: shows the entire proposed system architecture and Fig 2: shows the tracking map saved in the server for future data processing. Figure 2 Tracking Vehicle Map 4. SENSORS INTERFACING The framework is appropriate for screening transport vehicles movement in desktop, mobile, tablet devices inside open transport stations and can advise directors at whatever point the transport is touching base on time, ahead of time or behind time. Then the data is updated and displayed on the diverse remote inside and outside the transport station. The Versatile terminal unit is an installed framework containing RFID per user, GPS and a simple compass as information gadget to obtain area and position. The vehicle data can be seen on electronic guide by means of web programming. Alerts can also be sent using sensors which includes MEMS, Tilt and Eye-blink. MEMS can be used for direction observation. Tilt is used to determine whether the vehicle is in normal position. Eye blink is used to check the fatigue of the driver. These all sensors are interfaced in Arduino. GPS module is also incorporated with that. This level of mechanization is conceivable through an arrangement of calculations that utilizations GPS follows gathered from travel vehicle to decide the type of alerts encountered. It involves vehicle-mounted GPS beacons, a focal server framework and an online application. The area has to be checked graphically and significant alarms data of vehicle. This system is intended to serve undertakings with a boundless number of vehicles and complex use necessities. It also empowers client to peruse area track on outline created web application implant Google Map and associate with database server for vehicles track subtle elements. This item is one stop answer for all your truck following and ready needs. Fig 3: Shows the architecture of the interface of the proposed system, Figure 4: Shows the circuit diagram of the proposed system editor@iaeme.com

4 Truck Tracking and Alerts Monitoring System Figure 3 Architecture of the interface Figure 4 Circuit Diagram 5. DRIVER MONITORING AND ALERTING Remote sensor organizes utilized for checking of transport transportation framework and record of entry time of alerts at transport stops. Here eye blink is used to detect the driver s health status. If found any abnormalities in the data produced, the driver can be alerted or any nearby emergency services can be notified to look after the truck. This type of application is achieved using this system. Vehicle monitoring systems deals with the GPS and GSM innovation which gives the area of vehicle to the vehicle proprietor on account of vehicle is stolen. It can likewise be utilized as a part of natural life following, resource following and in stolen vehicle recuperation. Transportation is a vital shared asset that empowering productive and compelling utilization of assets like WSN and GPS units that can be deployed on to the vehicle and these units will help in tracking the location of the vehicle. Figure 5: Shows the various functionalities of the proposed system editor@iaeme.com

5 V. Kanchana Devi, A. David Maxim Gururaj, A. Kavya, E. Umamaheswari Figure 5 Functionalities of the proposed system 6. ALERT SYSTEM The proposed methodology will help users to track their vehicles remotely. The proposed vehicle tracking system will notify the location and route being travelled by vehicle. The information sent by tracking system can be viewed in any device, from any remote location. The accuracy of the location of the vehicle has been improved compared to existing methodologies. The user can track the vehicles in bad weather conditions also. The tracking system uses a tracking device with WSN using GPS tracking devices to manage, control and to know the identity and current location of the vehicle. Alerts given to the driver can also be viewed by the user from any remote location. Numerous methods are being used by various authors for vehicle tracking, vehicle monitoring and for the alerting driver and the system. These existing methods are deployed in different types of vehicles like bike, car, bud, truck, cargo lorry etc. [15]. The microcontroller obtains the data from the GPS module and transmits it to the control point with the help of WSN. In these existing methodologies GSM - Global System for Mobile & GPS - Global Positioning System are used to send information regarding the location and driver alerts to the cloud server. Using this data the vehicle can be tracked and stop anywhere in case of emergency. The Real time passenger information system uses various technologies to track location of vehicles like bus, train etc., in real-time to generate predictions of vehicle arrival time at a particular stop along the travel route. This system can also be used for real time tracking of vehicles, monitor the passengers in the vehicle, predict arrival time at a particular stop and send all these information to the base station. In the proposed system, the performance and accuracy of tracking is improved by using WSN. Google Map is used in the proposed methodology for tracking. The proposed system comes with both the advantages and complexity of Google maps. This proposed system tracks the location of the vehicles and send alerts to the drivers but doesn t predict the arrival time of the vehicle. The observation and experimental results, it is proved that the proposed system overcomes the problems in the existing system. Tracking accuracy and the reader efficiency are also increased with operating frequency and extending the range of the reader. The rate of data transmission, processing speed of the system has also been enhanced in the proposed system compared to the existing system. Vehicle tracking, monitoring and alerting system can be enhanced by using GPS, GSM/GPRS, RFID reader and ARM 11 processor for development of the vehicle tracking system. The proposed methodology is cost effective and user friendly when compared with the existing methodologies editor@iaeme.com

6 Truck Tracking and Alerts Monitoring System 7. RESULTS & SCREEN SHOTS Figure 6 depicts the screen shots of the proposed system and route map travelled by the vehicle. Figure 6 Screen Shots of the System developed & Route Map Travelled by the vehicle 8. CONCLUSION & FUTURE WORK The main objective of the project is to develop a GPS tracking system that tracks the vehicle and alert the system in case of emergencies, to a website where it can be viewed remotely. The proposed system stores the complete details about the travel of a vehicle like the route, distance travelled, driver control over the vehicle, and the cautions happened. This work will help in understanding the condition of the vehicle and the driver efficiency also. The project has wide range of scope in the future. The project can also be implemented as non-gps in future using only the sensor values. The process of updating can be performed easily, as the methodology proposed in flexible for expansion as per the requirement. With the proposed editor@iaeme.com

7 V. Kanchana Devi, A. David Maxim Gururaj, A. Kavya, E. Umamaheswari system, business owners can now able to control their fleet remotely and fully functional alert system is now able to give information about the conditions of the vehicle. REFERENCES [1] Umamaheswari E; Ajay D.M and Umang Sindal. Scope of Internet of Things: A Survey. Asian Journal of Pharmaceutical and Clinical Research, 2017, pp [2] Ajay D.M and Umamaheswari.E. An initiation for testing the security of a cloud service provider. Smart Innovation, Systems, Technologies. Switzerland: Springer Publications; pp [3] Ajay D.M and Umamaheswari.E. Why, how cloud computing- How not and cloud security issues?. Global Journal of Pure and Applied Mathematics (GJPAM), 12(1), 2016, pp.1-8. [4] D M Ajay and Umamaheswari E. Evaluating the Efficiency of Security Mechanisms in Cloud Environments. International Journal of Control Theory and Applications, Vol. 9, No.51, 2016, pp [5] I. Skog and P. Handel. In-car positioning and navigation technologies A survey. IEEE Trans. Intell. Transp. Syst., vol. 10, no. 1, 2009, pp [6] DachuanLi; Qing Li; Liangwen Tang; Sheng Yang; Nong Cheng and Jingyan Song. Invariant Observer-Based State Estimation for Micro-Aerial Vehicles in GPS-Denied Indoor Environments Using an RGB-D Camera and MEMS Inertial Sensors. Micromachines, vol. 6, no. 4, 2015, pp [7] E. Costa. Simulation of the effects of different urban environments on GPS performance using digital elevation models and building databases. IEEE Trans. Intell. Transp. Syst., vol. 12, no. 3, Sep. 2011, pp [8] X. Zhang; B. Xian; B. Zhao and Y. Zhang. Autonomous Flight Control of a Nano Quadrotor Helicopter in a GPS-denied Environment Using On-board Vision. IEEE Trans. Ind. Electron., vol. 62, no. 10, Oct pp [9] M. Barczyk and A. F. Lynch. Invariant observer design for a helicopter UAV aided inertial navigation system. IEEE Trans. Control Syst. Technol., vol. 21, no. 3, 2013, pp [10] A. Noureldin; T. B. Karamat; M. D. Eberts and A. El-Shafie, Performance enhancement of MEMS-based INS/GPS integration for low-cost navigation applications. IEEE Trans. Veh. Technol., vol. 58, no.3, 2009, pp [11] D. Bhatt; P. Aggarwal; V. Devabhaktuni and P. Bhattacharya. A novel hybrid fusion algorithm to bridge the period of GPS outages using low-cost INS. Expert Systems with Applications, vol. 41, no. 5, 2014, pp [12] S. Adusumilli; D. Bhatt; H. Wang; P. Bhattacharya and V. Devabhaktunia. A low-cost INS/GPS integration methodology based on random forest regression. Expert Systems with Applications, vol. 40, no. 11, 2013, pp [13] A. Noureldin; A. El-Shafie, and M. Bayoumi. GPS/INS integration utilizing dynamic neural networks for vehicular navigation. Information Fusion, vol. 12, no. 1, Jan. 2011, pp [14] R. Sharaf, and A. Noureldin. Sensor integration for satellite-based vehicular navigation using neural networks. IEEE Trans. Neural Netw., vol. 18, no. 2, 2007, pp , [15] Z. Xu; Y. Li; C. Rizos and X. Xu. Novel hybrid of LS-SVM and kalman filter for GPS/INS integration. Journal of Navigation, vol. 63, no. 02, 2010, pp editor@iaeme.com