Automatic Vehicle Entry Exit Log - Senior Year Project
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Transcript of Automatic Vehicle Entry Exit Log - Senior Year Project
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AUTOMATIC VEHICLE
ENTRY/EXIT LOG Ahmad AzharUmer Numan Guraya Umar Tabish Haque Taiyaba Saeed
AdvisorDr. Jahangir Ikram
Co-Advisor:Dr. Tariq JadoonDr. Murtaza Taj
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Project statement:The motivation for our project stems from a demand in the market to develop a system which can:
• Maintain an online log for entry/exit time of vehicles in a certain premises (factory etc)
• Maintain an online record with pictures for vehicles entering/exiting the premises
• Extract the number from these pictures through ANPR(Automatic Number Plate Recognition)
• ANPR should work on all legal number plates within Pakistan. E.g. Lahore, Karachi and Islamabad number plates
• Provide complete record of vehicles inside a premises at any given time, time of entry and exit of vehicle, setting up an action upon entry or exit of a vehicle (SMS etc – future additions)
• Provide vehicle count for past 10, 30 and 60 minutes.
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Aim of Project• Maintains a data for the entry/exit time of vehicles.
• Solves administrative issues by generating a text log for vehicles entering/ exiting the premises. This helps keep track of vehicle inflow, outflow and no. of vehicles in the premises which is helpful in fleet management.
• The system has a provision of keeping a record for a given period of time (e.g. 1 month).
• The system allows the user to ascertain the status of vehicles online, to know whether the vehicle is present in the premises or not.
• Provides a fast, efficient and reliable method of identifying presence of vehicles in a premises compared to traditional methods
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HOW THE SYSTEM WORKS
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Sends Signal
Trigger Camera
Send Image to Raspberry Pi
To ANPR System
Extracted Number
Info to WebsiteTo
server
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“AVELOG” is divided into three main parts
• Vehicle detection
• Database development and online log
• Number plate Identification via ANPR
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Vehicle Detection
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Vehicle Detection
Loop Specifications
1. 40/76 wire2. 4 turns3. Rectangular Octagon4. Twisted cable
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Vehicle Detection – the circuit
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Vehicle Detection – loop response• Change in voltage transmitted as car passes over
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Vehicle Detection• Voltage change ~0.2V
• Amplification of voltage change using ADC
• Setting upper and lower threshold
• Extensive testing to ensure no false readings
𝑈𝑝𝑝𝑒𝑟 h h𝑇 𝑟𝑒𝑠 𝑜𝑙𝑑❑
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Image Capture
• Image initially saved in RaspberryPI
• Image later transferred to Server using SSH communication
• Automatically run code every time RaspberryPI restarts using crontab
• Image name taken to be date and time i.e. 2016-04-22.09:00:00.jpeg
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SSH Communication
• Assign a static IP to both devices
• Use keyless SSH entry for communication between RaspberryPI and Server
• Generate public keys for both devices and share public keys among them
• Using crontab, send all images saved in RaspberryPI to Server every minute
• Delete image from RaspberryPI after sending image to Server
• Allows user access to Raspberry PI from Server
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Website Development• Images recived in html folder of Server, where website is being hosted
• Installation of following softwares:• Apache• PHP• html• Mysql• Phpmyadmin; GUI for databases• Nodejs
• traffic.lums.edu.pk
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Website Development – Main Page
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Website Development – 10 min
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Website Development – 60 min
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Website Development – No image
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Website Development
• Storing name directly into database
• Breaking name to get time and date and storing it into database
• Make four variables:
• Start_time; gives initial time
• end_time; gives end time
• date_start;
• date_end;
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Database
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ANPR using WebcamImage from Current Position Image from Up Close
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ANPR using WebcamGray Scale Image
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ANPR using WebcamBinary image
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ANPR using WebcamBounding Boxes plotted around the connected components
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ANPR using Webcam
LED 7658 LE 5033
Objects Extraction using Template Matching
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ANPR using Phone CameraImage from Current Position Image from Up Close
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ANPR using Phone CameraIdentification of the Connected Components
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ANPR using Phone Camera
LEB 8936 LEB 9493
Objects Extraction using Template Matching
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ANPR- ConclusionThe analysis on the mentioned methods leads to following conclusion:
• The camera must be of high quality
1.3MP Night Vision Waterproof License ANPR License Plate Capture(LPR) 1080P IP Camera
Plate Recognition Camera
US $ 275.00 US $255.00
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ANPR- Conclusion• Camera Positioning
• Ideal position is at road level
• Single camera covering one lane
• Distance of the camera from the vehicle should be kept minimum
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Hardware InstallationThe system was deployed at the out gate of LUMS. The following were included in it:
1. Webcam 2. Raspberry Pi (controller/client)3. Loop controlling circuit
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Cost Analysis
ITEM COST(PKR)
Raspberry Pi 5000
Webcam 8000
Wire (for loop) 1000
Labor 700
Hardware 1600
Total 16300
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ETAG and our system • No initial cost and logistics required to paste sticker on every vehicle
• No need to bring all vehicles within the system for system to work
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Future Work
• The proposed design is a prototype of cost effective solution to address an
important administrative issue. Potential future work on this project
includes:
• Application of same system on the entrance of LUMS.
• Improved image processing techniques for number plate identification
• An SMS alert system to inform arrival/exit of vehicle of choice