Intelligent Vehicular Flow Management System For Educational Hub
Onkar Swami1, Sachin Sakhare2, Subhash Tatale3
1Onkar Swami*, Computer Department, Vishwakarma Institute of Information Technology, Pune, India.
2Dr Sachin Sakhare, Computer Department, Vishwakarma Institute of Information Technology, Pune, India.
3Subhash Tatale, Computer Department, Vishwakarma Institute of Information Technology, Pune, India.
Manuscript received on 15 August 2019. | Revised Manuscript received on 25 August 2019. | Manuscript published on 30 September 2019. | PP: 770-775 | Volume-8 Issue-3 September 2019 | Retrieval Number: C4004098319/19©BEIESP | DOI: 10.35940/ijrte.C4004.098319
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: In rural and urban arenas, quantity of vehicle is expanding. To find parking area is turning into a primary concern. To design parking framework which is able to neglect physical efforts and also provide arena for vehicles parking. In later, instructive grounds are expanding which consist of Universities, designing, Art, Commerce and Science Colleges. The issue is parking spots either inadequate as indicated by the requests of understudies and staff or these spaces are ineffectively overseen. With each new individual entering college premises have an issue on grounds. In this method, we present the idea of the shrewd vehicle flow management. Here we will convey an Internet of Things (IoT) based framework which is utilized to detect the nearness and development of vehicles. Here, we have considered example of our V.I.I.T college campus to develop prototype which has 5 openings for each division. The vehicle flow management parking framework is creating in 2 stages. In the principal stage, the information, for example, vehicles utilized, offices, and so on about the educator and staff data will be gathered and information is grouped according to office. In the second stage, the observation camera is catching pictures of the vehicle. By utilizing a novel methodology like Quadrature lock-in Discrimination (QLD), decreasing poor visibility because of stray light or mist to peruse the vehicle plate number. For the majority of part, in existing propelled frameworks doesn’t give office shrewd separate stopping framework. We proposed a framework which has diverse vehicle flow management framework for various office and understudy/educator just from the office can stop in apportioned spaces. The framework utilizes Raspberry Pi has confederated with the Radio Frequency Identification (RFID) per user, associated with a website page by means of its integrated Wi-Fi. RFID tags are distributed to college members and slot allocation is given dynamically by system.
Keywords: GSM, Image Processing, IoT, Quadrature lock-in Discrimination(QLD), RFID, Raspberry Pi.
Scope of the Article: Evolutionary Computing and Intelligent Systems.