toll collection using raspberry pi with computer...

International Journal of Applied Sciences, Engineering and Management ISSN 2320 – 3439, Vol. 06, No. 02, March 2017, pp. 115-117

IJAEM 060224 Copyright @ 2017 SRC. All rights reserved.

Toll Collection Using Raspberry Pi with Computer Vision Based Technology

J.Sridevi1, P. Durga Anuhya2, D.Ravali2, CH. Manikanta Swamy2, P.Sandeep2

1Assistant Professor, Department of Electronics & Communication Engineering, Ramachandra College of Engineering, Eluru, Andhra Pradesh, India.

2B. Tech. Students, Department of Electronics & Communication Engineering, Ramachandra College of Engineering, Eluru, Andhra Pradesh, India

Email:[email protected], [email protected], [email protected], [email protected], [email protected]

ABSTRACT: The main aim of this project is to design wireless communication system to manage the vehicle entry exit toll collection automatically using Raspberry Pi. The proposed system eliminates the need for motorists and toll authorities to manually perform ticket payments and toll fee collections. Our project is designed with Camera interfaced with Raspberry Pi, computer server and host computer. The working analogy can be explained as follows: the vehicle owners have to maintain a certain balance in their account which when their vehicles cross a toll gate, camera would capture the vehicle number from the number plate. The captured image is thus processed and is checked with the database and generates the available balance. The server computer now generates the toll gate bill by cutting its charges from the available balance. The major advantages are: the vehicle need not wait till the manual process of noting down the number and then a message will be send to them; traffic would be less in the proposed project. Key Words: Camera, Image Processing, RFID Readers, Raspberry PI 3, Python programming language, Open CV image processing library. INTRODUCTION Automated Toll System has been implemented in some countries like Canada, Poland where the toll amount is deducted from the vehicle owner’s bank account and a notification can be provided in the form of a message. Automated Toll Collection in India is beneficial because it can provide a means with the help of which we can reduce the congestion near the toll collection areas. Usually the congestion near the toll collection areas is because the vehicle owner pays the toll in the form of physical cash. Automated Toll Collection will also be beneficial for smart card holders. The vehicles number plate will be detected using a camera that will be placed at the toll checkpoint, with the help of which a image processing technique will be implemented to extract the registration number of the car from the number plate, with the help of this extraction the details of the vehicles owner will be extracted from the database and the respective amount will be deducted, if the vehicle owner acquires a smart card, even that information will be extracted from the database because that person has already paid the toll amount in advance for a respective duration. EXISTING SYSTEM MANUAL TOLL COLLECTION

According to the manual toll collection methodology, a driver has to stop at a charging booth and pay the required fee directly to a collector. The amount to be paid by each vehicle is determined by its characteristics or classification. The manual toll is the conventional toll collection system which is made by an operator in the cabin that carries out the payment of the fee for each vehicle, using multiple methods of payment:

Cash (coins or banknotes), credit cardsetc, Manual toll collection is most widely used collection method in India. It requires a toll collector or attendant. Based on the vehicle classification, cash toll is received by the collector. The collector, who also dispenses change, may accept and sell scrip, tickets, coupons, making an entry of the vehicle in the system and issuing receipt to the patron. Due to manual intervention, the processing time is highest. Electronic Toll Collection

Electronic Toll Collection (ETC) is a system that automatically identifies a vehicle equipped with a valid encoded data tag or transponder as it moves through a toll lane or checkpoint. The ETC system then posts a debit or charge to a patron's account, without the patron having to stop to pay the toll. ETC increases the lane throughput because vehicles need not stop to pay the toll. Block Diagram

Fig 1. Block diagram

Toll Collection Using Raspberry Pi with Computer Vision Based Technology


BARCODE READERS Electronic toll collection (ETC) system using barcode reader technology. The system uses tags (barcode) that are mounted on the number plate of vehicles, or on the front side of vehicles through which information embedded on the barcode are read by barcode reader, the proposed system eliminates toll authorities to manually perform ticket payments and collection of cash. It is more efficient method because it reduces the traffic and possible human errors by exchanging the data information between the motorists and toll authorities. Barcodes are much smaller and lighter and therefore easier to use. Barcodes are less expensive than RFID tags because barcodes are directly printed onto material such as plastic or paper materials and therefore the only cost involved is the ink. This technology has many advantages such as automatic and accurate toll collection, improvement in highway efficiency and low fuel consumption. RFID TAGS

ATCS is an Automated Toll Collection System used for collecting tax automatically. In this we do the identification with the help of radio frequency. A vehicle will hold an RFID tag. This tag is nothing but unique identification number assigned. This will be assigned by RTO or traffic governing authority. In accordance with this number we will store, all basic information as well as the amount he has paid in advance for the TOLL collection. Reader will be strategically placed at toll collection center. Whenever the vehicle passes the toll plazza, the tax amount will be deducted from his prepaid balance. New balance will be updated. In case if one has insufficient balance, his updated balance will be negative one. To tackle this problem, we are alarming a sound, which will alert the authority that this vehicle doesn’t have sufficient balance and that particular vehicle can be trapped. PROPOSED METHOD

The proposed system provides a base for implementing automatic number plate detection using image processing for toll collection at toll checkpoints. This system will help in saving time as well as help in reducing congestion at toll checkpoints. The proposed system will capture an image placed at the toll checkpoint and will perform certain processes to detect the number plate of a vehicle. ALGORITHM Step 1: With the help of a camera, the number plate of the vehicle will be captured. Step 2: The number plate of the vehicle will be processed using an image processing technique. Step 3: Once the license number is extracted from

the overall image, it will be compared and searched in the centralize database and the respective vehicle owner’s details will be fetched. Step 4: Along with the details, it will also check whether the owner of the vehicle obtains a smart card. Step 5: If the possession of the smart card does not exists, then go to step 7. Else check for the validity of the card. Step 6: If the card is not valid, then go to step 7. Else the toll amount will not be deducted from the vehicle owner’s bank account. Step 7: Toll amount will be deducted from the vehicle owner’s bank account.

FLOW CHART

Fig 2: Flow chart RESULT The Circuit module of RFID Automatic tollgate system designed could automatically detect the identities of the vehicles and performed the billing in accordance to the identity of each vehicle as pre recorded in the database. The system could automatically open and close the gate as well as automatically emailing the owners of the vehicles. These were the major achievements met in the project, among other objectives also achieved, which include tracking of the vehicles and remote database connection. However the proper demonstration of some of the objectives did not yield to the wanted extent due to lack of resources.

J.Sridevi, P. Durga Anuhya, D.Ravali, CH. Manikanta Swamy, P.Sandeep


Fig 3: Hardware of the project

Fig 4: Software of the project.

Conclusion and Future Scope In this project, we have discussed the

image processing technique to implement the automated toll collection in order to reduce congestion and fraudulent behaviour at the toll checkpoints. Further we have discussed the working of the proposed system including the smart card implementation and the automated deduction of the toll from the vehicle owner's bank account. The proposed system will help in reduce the human intervention at the toll collection areas. The purpose of this project was to improvise the toll collection as well as implement a system for smart card users as smart cards is being used by many people in order to avoid physical cash.

The future of this system is very wide. In this the simple web camera, periodically, images can be taken and sent on the internet. E-mail sending is also possible easily on raspberry pi using the smtplib function present already. By combining all these features, this can be a complete production monitoring system or can be used as a building automation and control system. The applications are literally limitless. Wherever, data monitoring, remote sending and remote controlling is required, the same system is applicable directly with little modifications.

Thus, such a system can be implemented using a low cost computer like Raspberry Pi which can function like a mini computer. The said system can run for 24 hours a day 7 days a week

continuously for satisfying the most demanding application toll system. The latest advancements of technology and new boards coming every day, it apparent that all embedded applications and systems will be implemented as IoT application. REFERENCES

[1] Ieee Transactions On Intelligent Transportation Systems, Vol. 12, No. 3, September 2011 An Algorithm for License Plate Recognition Applied to Intelligent Transportation System. Ying Wen, Yue Lu, Member, IEEE, Jingqi Yan, Zhenyu Zhou, Karen M. von Deneen, and Pengfei Shi, Senior Member, IEEE [2] International Journal of Advanced Research in Computer Science and Software Engineering, Volume 4, Issue 3, March 2014 Study of Different Electronic toll Collection Systems and Proposed toll Snapping and Processing System. ApurvaHemantKulkarni M.E Department of Computer Science & Engineering, G.H.R.I.E.M jalgaon North Maharashtra university,INDIA [3] Rafael C. Gonzalez and Richard E. Woods, “Digital Image Processing”3rd edition, Pearson/Prentice Hall, 2008 (variance) pp. 96 97,(Mathematical Morphology) pp. 628-635, (Segmentation) pp.700-725, (Thresholding) pp.738-742, (Object Recognition - Correlation) pp. 866-872. [4] KHADIJAH KAMARULAZIZI ,DR.WIDID ISMAIL electronic toll collection system using rfid technologies Journal of Theoretical and Applied information technology © 2005 - 2010 JATIT & LLS.. [5] ZhigangXu, Honglei Zhu, “An Efficient Method of Locating Vehicle Licence Plate”, 3rd International conference on Natural Computetion, IEEE, 0-7695-2875-9/07, 2007. [6] Prathamesh Kulkarni (Student Member, IEEE), AshishKhatri, PrateekBanga, Kushal Shah, “Automatic Number Plate Recognition (ANPR) System for Indian conditions”, IEEE Transactions, 2009. [7] International Journal of Scientific Engineering Research Volume 3, Issue 8, August -2012 1. Still Image Recognition Of License Plate System. N.Kanagaraj1, G.Baskaran2,S.Saravanan3,A.Ramachandran4 1,2,3,4 Assistant professor, Srinivasan Engineering College, Perambalur, Tamilnadu, India [8] AbhijeetSuryatali and V. B. Dharmadhikari, “Computer Vision Based Vehicle Detection for Toll Collection System Using Embedded Linux,” International Conference on Ciricuit, Power and Computing Technologies [ICCPCT], 2015. [9] UkeNilesh J. and Ravindra C. Thool, “Moving Vehicle Detection for Measuring Traffic Count Using OpenCV,” Journal of Automation and Control Engineering, 2013, vol. 1.4.

toll collection using raspberry pi with computer...

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