Abstract
This paper proposed a system that automatically opens security gates. A system is designed and implemented to automatically open security gates for vehicles using Licence Plate Recognition. Image processing is used to extract the licence plate and characters, and an Artificial Neural Network is used to perform Optical Character Recognition on licence plate characters. Internet of Things principles are introduced to the system to allow for web and mobile application integration. A proximity sensor is designed to detect vehicles and to start the recognition process. An ambient light sensor and control circuit is developed to control ambient lighting conditions using an ambient light source. The neural network achieved an accuracy of 88% on training data and 93% on licence plate characters. A unique strong point of the system is the ability to monitor and control the system using a web interface or mobile application. The system is also able to produce mobile notifications regarding security gate access attempts.
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Notes
An epoch is one iteration through the training data.
Test data is used to measure the performance of the ANN.
The ANN can be seen as fully trained, and ready to be used.
An algorithm that produces pseudo-random standard normal variables.
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Acknowledgements
This work is supported in part by the National Research Foundation, South Africa (grant numbers: IFR160118156967 and RDYR160404161474). The authors would like thank Mr. Arun Jose Cyril for editing revised version of this paper.
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Cowdrey, K., Malekian, R. Home automation - an IoT based system to open security gates using number plate recognition and artificial neural networks. Multimed Tools Appl 77, 20325–20354 (2018). https://doi.org/10.1007/s11042-017-5407-1
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DOI: https://doi.org/10.1007/s11042-017-5407-1