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253 results on '"Elngar, Ahmed A."'

5. Efficacy of Knowledge Graphs to Systematize Primitive Research Methodology

Author

Jyothi, B., Subbulakshmi, S., Elngar, Ahmed A., Kacprzyk, Janusz, Series Editor, Gomide, Fernando, Advisory Editor, Kaynak, Okyay, Advisory Editor, Liu, Derong, Advisory Editor, Pedrycz, Witold, Advisory Editor, Polycarpou, Marios M., Advisory Editor, Rudas, Imre J., Advisory Editor, Wang, Jun, Advisory Editor, Senjyu, Tomonobu, editor, So–In, Chakchai, editor, and Joshi, Amit, editor

Published
2024
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14. Secret Information Sharing Using Probability and Bilinear Transformation

Author

Mohan, Kala Raja, Rasappan, Suresh, Murugesan, Regan, Kumaravel, Sathish Kumar, Elngar, Ahmed A., Kacprzyk, Janusz, Series Editor, Pal, Nikhil R., Advisory Editor, Bello Perez, Rafael, Advisory Editor, Corchado, Emilio S., Advisory Editor, Hagras, Hani, Advisory Editor, Kóczy, László T., Advisory Editor, Kreinovich, Vladik, Advisory Editor, Lin, Chin-Teng, Advisory Editor, Lu, Jie, Advisory Editor, Melin, Patricia, Advisory Editor, Nedjah, Nadia, Advisory Editor, Nguyen, Ngoc Thanh, Advisory Editor, Wang, Jun, Advisory Editor, Peng, Sheng-Lung, editor, Lin, Cheng-Kuan, editor, and Pal, Souvik, editor

Published
2022
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19. Blockchain

Author

Chakraborty, Rajdeep, primary, Ghosh, Anupam, additional, Balas, Valentina Emilia, additional, and A Elngar, Ahmed, additional

Published
2022
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24. Subject Index

Author

Jena, Om Praksh, primary, Tripathy, Alok Ranjan, additional, Mishra, Brojo Kishore, additional, and Elngar, Ahmed A., additional

Published
2022
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36. A New Efficient and Secure Architecture Model for Internet of Things

Author

Elngar, Ahmed A., Elsayed, Eman K., Ibrahim, Asmaa A., Kacprzyk, Janusz, Series Editor, Pal, Nikhil R., Advisory Editor, Bello Perez, Rafael, Advisory Editor, Corchado, Emilio S., Advisory Editor, Hagras, Hani, Advisory Editor, Kóczy, László T., Advisory Editor, Kreinovich, Vladik, Advisory Editor, Lin, Chin-Teng, Advisory Editor, Lu, Jie, Advisory Editor, Melin, Patricia, Advisory Editor, Nedjah, Nadia, Advisory Editor, Nguyen, Ngoc Thanh, Advisory Editor, Wang, Jun, Advisory Editor, Khanna, Ashish, editor, Gupta, Deepak, editor, Bhattacharyya, Siddhartha, editor, Snasel, Vaclav, editor, Platos, Jan, editor, and Hassanien, Aboul Ella, editor

Published
2020
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50. Vehicle Security Systems using Face Recognition based on Internet of Things

Author

Elngar Ahmed A. and Kayed Mohammed

Subjects
internet of things, face recognition, haar-cascade, principle component analysis, vehicle security systems, Electronic computers. Computer science, QA75.5-76.95
Abstract

Nowadays, the automobile sector is one of the hottest applications, where vehicles can be intelligent by using IoT technology. But unfortunately, these vehicles suffer from many crimes. Hence it has become a big challenge for the IoT to avoid such these crimes from professional thieves. This paper presents a proposal for the development of a vehicle guard and alarm system using biometric authentication based on IoT technology. Whereas, for vehicle security issues; the proposed system VSS − IoT gives only full access for authorized vehicle’s driver based on the interface of a Raspberry Pi 3 Model B+ development board, Pi camera, PIR sensor, and smart-phone. Therefore, if the proposed system detects an unauthorized person inside the vehicle, then the system will notify and send his image to vehicle’s owner and/or to a police workstation through the Internet, as well as, its location in case the vehicle is stolen or damaged. The proposed system is tested on two datasets that are ORL dataset and our dataset. The experimental results of the VSS − IoT showed that the accuracy is 98.2% on ORL dataset, whereas 99.6% when applied on our dataset. Besides, the VSS − IoT enhances the sensitivity to 97.7% which is important for real-time. As well as the result demonstrated that the proposed system took shorter time 0.152 sec under different illumination conditions, when the value of the threshold is 3 * 103 and 3.50 * 103. Therefore, the VSS − IoT is very robust and reliable for face recognition when deployed on the low-power processor.

Published
2020
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