Abstract
Home security is a major concern worldwide, and there are various solutions available, but with limitations. This paper proposes a novel security system that overcomes the limitations of current systems by using piezoresistive sensors placed inside a mat to detect intruders with varying levels of pressure intensities. The proposed system incorporates a camera and a CNN algorithm with the EfficientNet model to detect whether the object is a human, and it is equipped with features like an email and SMS notification mechanism, backup battery, and a sophisticated tracking mechanism. The proposed system is highly resilient to tampering or circumvention and outperforms existing security systems in terms of being non-intrusive, providing tracking features for the intruder, and being resistant to blackouts. This paper documents the research, development, testing, evaluation process, and contributions made to address the security challenges by developing an affordable, easy-to-use, and effective home security system.
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References
Hoque, M.A., Davidson, C.: Design and implementation of an IoT-based smart home security system. IJNDC 7(2), 85 (2019). https://doi.org/10.2991/ijndc.k.190326.004
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
Rock, L.Y., Tajudeen, F.P., Chung, Y.W.: Usage and impact of the internet-of-things-based smart home technology: a quality-of-life perspective. Univ. Access Inf. Soc. (2022). https://doi.org/10.1007/s10209-022-00937-0
SafeHome.org Research, “Home Security Statistics in 2021,” SafeHome.org (2021). https://www.safehome.org/data/home-security-statistics/. Accessed 21 Sep 2022
Gonzalez, M.: Reducing false alarms with AI and deep learning (2022). https://www.security101.com/blog/reducing-false-alarms-with-ai-and-deep-learning. Accessed 21 Sep 2022
Doan, T.T., Safavi-Naini, R., Li, S., Avizheh, S.K.M.V., Fong, P.W.:Towards a resilient smart home. In: Proceedings of the 2018 Workshop on IoT Security and Privacy, pp. 15–21. ACM, Budapest Hungary, August 2018. https://doi.org/10.1145/3229565.3229570
Tholen, C.: If the Power Goes Out, Does My Security System Still Work? SafeWise, 12 April 2021. https://www.safewise.com/home-security-faq/do-security-systems-work-power-out/. Accessed 21 Sep 2022
Desnanjaya, I.G.M.N., Arsana, I.N.A.: Home security monitoring system with IoT-based raspberry Pi. IJEECS 22(3), 1295 (2021). https://doi.org/10.11591/ijeecs.v22.i3.pp1295-1302
Sharma, M., Assotally, A., Bekaroo, G.: RaspiMonitor: a raspberry pi based smart home monitoring system. In: 2022 3rd International Conference on Next Generation Computing Applications (NextComp), pp. 1–6. IEEE, Flic-en-Flac, Mauritius, October 2022. https://doi.org/10.1109/NextComp55567.2022.9932198
Ring, “Ring Alarm Pro,” Ring. https://ring.com/products/alarm-pro-base-station. Accessed 19 Mar 2023
Taiwo, O., Ezugwu, A.E.: Internet of things-based intelligent smart home control system. Secur. Commun. Netw. 2021, 1–17 (2021). https://doi.org/10.1155/2021/9928254
Adriano, D.B., Budi, W.A.C.: IoT-based integrated home security and monitoring system. J. Phys. Conf. Ser. 1140, 012006 (2018). https://doi.org/10.1088/1742-6596/1140/1/012006
Binti Ramli, R., Binti Nazri, N.D.A., Al-Sanjary, O.I., Rozzani, N.: The development of weight detection system using IOT flooring. In: 2021 IEEE 11th IEEE Symposium on Computer Applications & Industrial Electronics (ISCAIE), pp. 250–255. IEEE, Penang, Malaysia, April 2021. https://doi.org/10.1109/ISCAIE51753.2021.9431787
Das, S., Neelanarayan, V.: IoT Based Anti-Theft Flooring System, p. 4 (2020)
Dorothy, A.B., Kumar, S.B.R., Sharmila, J.J.: IoT based home security through digital image processing algorithms. In: 2017 World Congress on Computing and Communication Technologies (WCCCT), pp. 20–23. IEEE, Tiruchirappalli, Tamil Nadu, India, Feburary 2017. https://doi.org/10.1109/WCCCT.2016.15
Sivarathinabala, M., Abirami, S., Deivamani, M., Sudharsan, M.: A smart security system using multi-modal features from videos. Pattern Recognit Image Anal. 29(1), 89–98 (2019). https://doi.org/10.1134/S1054661819010218
Hopkins, M., Vaidyanathan, R., Mcgregor, A.H.: Examination of the performance characteristics of velostat as an in-socket pressure sensor. IEEE Sens. J. 20(13), 6992–7000 (2020). https://doi.org/10.1109/JSEN.2020.2978431
Kumar, V., Yeo, B.-C., Lim, W.-S., Ra, J.E., Koh, K.-B.: Development of electronic floor mat for fall detection and elderly care. Asian J. Sci. Res. 11(3), 344–356 (2018). https://doi.org/10.3923/ajsr.2018.344.356
Liu, R.: Higher accuracy on vision models with EfficientNet-Lite (2020). https://blog.tensorflow.org/2020/03/higher-accuracy-on-vision-models-with-efficientnet-lite.html. Accessed 30 Sep 2022
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Veerabudren, K., Ramsurrun, V., Sharma, M., Seeam, A. (2024). Enhancing Home Security with Pressure Mat Sensors: A Multi-modal IoT Approach. In: Seeam, A., Ramsurrun, V., Juddoo, S., Phokeer, A. (eds) Innovations and Interdisciplinary Solutions for Underserved Areas. InterSol 2023. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 541. Springer, Cham. https://doi.org/10.1007/978-3-031-51849-2_6
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