Abstract
Currently, the integration of IoT technology in various fields is very widely used, however, data security remains the essential point to be monitored especially in companies, and also in homes. To control and overcome security-related problems, we adopted Internet of Things technology based on a Raspberry pi4 as the main data processing element in this study. In this paper, we present a simple, efficient, and very reliable study for the monitoring of a video stream coming from a camera installed on a Raspberry pi4 which constitutes the essential element in our project. To reproduce this realization, we did not use a motion sensor, but we took advantage of the algorithm advantages of the Motion software integrated into the free operating system MotionEyeOs on a Raspberry pi4 to trigger motion detection by causing a beep to draw attention.
On the other hand, our study was implemented without noticed difficulty, and with a great level of performance and stability which shows that our realization of the Video Stream Surveillance System is successful.
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References
Rekha, S., Thirupathi, L., Renikunta, S., Gangula, R.: Study of security issues and solutions in Internet of Things (IoT). Mater. Today Proc. (2021). https://doi.org/10.1016/j.matpr.2021.07.295
Neeli, J., Patil, S.: Insight to security paradigm, research trend & statistics in Internet of Things (IoT). Glob. Transit. Proc. 2(1), 84–90 (2021). https://doi.org/10.1016/j.gltp.2021.01.012
Ammi, M., Alarabi, S., Benkhelifa, E.: Customized blockchain-based architecture for secure smart home for lightweight IoT. Inf. Process. Manag. 58(3) (2021). https://doi.org/10.1016/j.ipm.2020.102482
Delgosha, M.S., Hajiheydari, N., Talafidaryani, M.: Discovering IoT implications in business and management: a computational thematic analysis. Technovation (2021). https://doi.org/10.1016/j.technovation.2021.102236
Wu, K., Lagesse, B.: Detecting hidden webcams with delay-tolerant similarity of simultaneous observation. Pervasive Mob. Comput. 65 (2020). https://doi.org/10.1016/j.pmcj.2020.101154
Abas, K., Obraczka, K., Miller, L.: Solar-powered, wireless smart camera network: an IoT solution for outdoor video monitoring. Comput. Commun. 118, 217–233 (2018). https://doi.org/10.1016/j.comcom.2018.01.007
Coquin, D., Boukezzoula, R., Benoit, A., Nguyen, T.L.: Assistance via IoT networking cameras and evidence theory for 3D object instance recognition: application for the NAO humanoid robot. Internet Things 9 (2020). https://doi.org/10.1016/j.IoT.2019.100128
Gu, Z.: Home smart motion system assisted by multi-sensor. Microprocess. Microsyst. 80 (2021). https://doi.org/10.1016/j.micpro.2020.103591
Verma, M., Kaler, R.S., Singh, M.: Sensitivity enhancement of Passive Infrared (PIR) sensor for motion detection. Optik 244 (2021). https://doi.org/10.1016/j.ijleo.2021.167503
Surantha, N., Wicaksono, W.R.: Design of smart home security system using object recognition and PIR sensor. Procedia Comput. Sci. 135, 465–472 (2018). https://doi.org/10.1016/j.procs.2018.08.198
Stolojescu-Crisan, C., Crisan, C., Butunoi, B.-P.: Access control and surveillance in a smart home. High Confid. Comput., 100036 (2021). https://doi.org/10.1016/j.hcc.2021.100036
Anandhalli, M., Baligar, V.P.: A novel approach in real-time vehicle detection and tracking using Raspberry Pi. Alex. Eng. J. 57(3), 1597–1607 (2018). https://doi.org/10.1016/j.aej.2017.06.008
Didi, Z., El Azami, I.: IoT design and realization of a supervision device for photovoltaic panels using an approach based on radiofrequency technology. In: Motahhir, S., Bossoufi, B. (eds.) ICDTA 2021. LNNS, vol. 211, pp. 365–375. Springer, Cham (2021). https://doi.org/10.1007/978-3-030-73882-2_34
Santhosh, C., et al.: IoT based smart energy meter using GSM. Mater. Today Proc. 46, Part 9, 4122–4124 (2021). https://doi.org/10.1016/j.matpr.2021.02.641
Chakraborty, A., Banerjee, A.: Modular and parallel VLSI architecture of multi-dimensional quad-core GA co-processor for real time image/video processing. Microprocess. Microsyst. 65, 180–195 (2019). https://doi.org/10.1016/j.micpro.2019.02.002
Ali, R., Chuah, J.H., Talip, M.S.A., Mokhtar, N., Shoaib, M.A.: Automatic pixel-level crack segmentation in images using fully convolutional neural network based on residual blocks and pixel local weights. Eng. Appl. Artif. Intell. 104 (2021). https://doi.org/10.1016/j.engappai.2021.104391
Sasi, G.: Motion detection using Passive Infrared Sensor using IoT. J. Phys. Conf. Ser. 1717, 012067 (2021). https://doi.org/10.1088/1742-6596/1717/1/012067
Li, X., Zheng, H.: Target detection algorithm for dance moving images based on sensor and motion capture data. Microprocess. Microsyst. 81 (2021). https://doi.org/10.1016/j.micpro.2020.103743
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Didi, Z., El Azami, I., Boumait, E.M. (2022). Design of a Security System Based on Raspberry Pi with Motion Detection. In: Motahhir, S., Bossoufi, B. (eds) Digital Technologies and Applications. ICDTA 2022. Lecture Notes in Networks and Systems, vol 455. Springer, Cham. https://doi.org/10.1007/978-3-031-02447-4_44
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