Abstract
Today’s cities must respond to multiple challenges related to the evolutions of the contemporary world. The safety of people and goods has become a strategic issue for countries and companies. An intelligent system for Smart Cities is a desired technology in the 21st century. The main attraction of any automated system using the Internet of Things (IoT) is to reduce human labour, effort, time and errors due to human negligence. Managing the security of people in a public space is very important in the smart cities. The challenge is to find a system that offers many security solutions at the same time? An affordable and effective tool. In this paper a global system that manages different solutions in a single application using the IoT is proposed. Various sensors based on facial recognition, fire detection, vehicle number plate recognition can be added at this prototype to improve the intelligence and ability to make more accurate decisions.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Hu, V., Ni, Q.: IoT-driven automated object detection algorithm for urban surveillance systems in Smart Cities. IEEE Internet Things J. PP(99), 1 (2017)
Aslan, E.S., Özdemir, Ö.F., Hacıoğlu, A., İnce, G.: Smart pass automation system. In: 24th Signal Processing and Communication Application Conference (SIU), Zonguldak, Turkey (2016)
Vanus, J., Kucera, P., Martinek, R., Koziorek, J.: Development and testing of a visualization application software, implemented with wireless control system in smart home care. Hum. Centric Comput. Inf. Sci. 4(1), 1–19 (2014)
Li, M., Lin, H.-J.: Design and implementation of smart home control systems based on wireless sensor networks and power line communications. IEEE Trans. Ind. Electron. 62(7), 4430–4442 (2015)
Zuo, F., De With, P.H.: Real-time embedded face recognition for smart home. IEEE Trans. Consum. Electron. 51(1), 183–190 (2005)
Kumar, S.: Ubiquitous smart home system using android application. arXiv preprint arXiv:1402.2114 (2014)
Al-Audah, Y.K., Al-Juraifani, A.K., Deriche, M.A.: A real-time license plate recognition system for Saudi Arabia using LabVIEW. In: 2012 3rd International Conference on Image Processing Theory, Tools and Applications (IPTA), Istanbul, pp. 160–164 (2012)
Saleem, N., Muazzam, H., Tahir, H.M., Farooq, U.: Automatic license plate recognition using extracted features. In: 2016 4th International Symposium on Computational and Business Intelligence (ISCBI), Olten, pp. 221–225 (2016)
Matai, J., Irturk, A., Kastner, R.: Design and implementation of an FPGA-based real-time face recognition system. In: 2011 IEEE 19th Annual International Symposium on Field-Programmable Custom Computing Machines, Salt Lake City, UT, pp. 97–100 (2011)
Ru, F., Peng, X., Hou, L., Wang, J., Geng, S., Song, C.: The design of face recognition system based on ARM9 embedded platform. In: 2015 IEEE 11th International Conference on ASIC (ASICON), Chengdu, pp. 1–4 (2015)
Premal, C.E., Vinsley, S.S.: Image processing based forest fire detection using YCbCr colour model. In: 2014 International Conference on Circuits, Power and Computing Technologies (ICCPCT-2014), Nagercoil, pp. 1229–1237 (2014)
http://whatis.techtarget.com/definition/Raspberry-Pi-35-computer
Soumaya, F.T.: Développement d’un système de reconnaissance faciale à base de la méthode LBP pour le contrôle d’accès. École National Supérieure de Technologie (ENST), Alger, chapitre 2, pp. 19–25 (2016)
Chaari, A.: Nouvelle approche d’identification dans les bases de données biométriques basée sur une classification non supervisée. Modélisation et simulation, Université d’Evry-Val d’Essonne, Français (2009). <tel-00549395>
Mithe, R., Indalkar, S., Divekar, N.: Optical character recognition. Int. J. Recent Technol. Eng. (IJRTE) 2, 72–75 (2013)
Binti Zaidi, N.I., Binti Lokman, N.A.A., Bin Daud, M.R., Achmad, H., Chia, K.A.: Fire recognition using RGB and YCBCR color space. ARPN J. Eng. Appl. Sci. 10(21), 9786–9790 (2015)
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2018 Springer International Publishing AG
About this paper
Cite this paper
Khoumeri, EH., Cheggou, R., Farhah, K. (2018). IoT-Safety and Security System in Smart Cities. In: Hatti, M. (eds) Artificial Intelligence in Renewable Energetic Systems. ICAIRES 2017. Lecture Notes in Networks and Systems, vol 35. Springer, Cham. https://doi.org/10.1007/978-3-319-73192-6_3
Download citation
DOI: https://doi.org/10.1007/978-3-319-73192-6_3
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-73191-9
Online ISBN: 978-3-319-73192-6
eBook Packages: EngineeringEngineering (R0)