Abstract
With the rapid development of deep learning techniques in computer vision, emotion detection has been an emerging topic for different industries, including healthcare, mobile entertainment, and even securities. These organizations leverage emotion detection and apply it to both real-time cameras and offline videos to provide more interactivity between users and devices. In this study, we provide a lightweight personalized accompanying system for home security using emotion detection and IoT devices. We implement our design and demonstrate a practical scenario using Nvidia Jetson Nano. According to our design, we hope the system can benefit the health monitoring and interactivity for those elderly living alone.
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Abaya, W.F., Basa, J., Sy, M., Abad, A.C., Dadios, E.P.: Low cost smart security camera with night vision capability using raspberry Pi and OpenCV. In: 2014 International Conference on Humanoid, Nanotechnology, Information Technology, Communication and Control, Environment and Management (HNICEM), pp. 1–6. IEEE (2014)
Cacioppo, J.T., Cacioppo, S.: Loneliness in the modern age: an evolutionary theory of loneliness (ETL). In: Advances in Experimental Social Psychology, vol. 58, pp. 127–197. Elsevier (2018)
Chowdhury, M.N., Nooman, M.S., Sarker, S.: Access control of door and home security by raspberry Pi through Internet. Int. J. Sci. Eng. Res 4(1), 550–558 (2013)
Gupta, M.S.D., Patchava, V., Menezes, V.: Healthcare based on IoT using raspberry Pi. In: 2015 International Conference on Green Computing and Internet of Things (ICGCIoT), pp. 796–799. IEEE (2015)
Hardie, E., Tee, M.Y.: Excessive Internet use: the role of personality, loneliness and social support networks in Internet addiction. Aust. J. Emerg. Technol. Soc. 5(1), 34–47 (2007)
Ministry of Health Welfare: Taiwan alzheimer disease rate survey, Taiwan elderly over 65 years old was 4.97%. (2013). https://www.mohw.gov.tw/cp-3211-23536-1.html. Accessed 12 Apr 2013
Karapetsas, A.V., Karapetsas, V.A., Zygouris, N.C., Fotis, A.I.: Internet addiction and loneliness. Encephalos 52, 4–9 (2015)
Kumar, R., Rajasekaran, M.P.: An IoT based patient monitoring system using raspberry Pi. In: 2016 International Conference on Computing Technologies and Intelligent Data Engineering (ICCTIDE 2016), pp. 1–4. IEEE (2016)
Matthews, T., Danese, A., Caspi, A., Fisher, H.L., Goldman-Mellor, S., Kepa, A., Moffitt, T.E., Odgers, C.L., Arseneault, L.: Lonely young adults in modern britain: findings from an epidemiological cohort study. Psychol. Med. 49(2), 268–277 (2019)
Nowland, R., Necka, E.A., Cacioppo, J.T.: Loneliness and social Internet use: pathways to reconnection in a digital world? Perspect. Psychol. Sci. 13(1), 70–87 (2018)
Pardeshi, V., Sagar, S., Murmurwar, S., Hage, P.: Health monitoring systems using IoT and raspberry Pi—a review. In: 2017 International Conference on Innovative Mechanisms for Industry Applications (ICIMIA), pp. 134–137. IEEE (2017)
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Lin, PY., Liou, YS., Li, JX., Liew, JK., Chi, PW., Wang, MH. (2020). SmileJob: A Lightweight Personalized Accompanying System for Home Security. In: Jain, L., Peng, SL., Wang, SJ. (eds) Security with Intelligent Computing and Big-Data Services 2019. SICBS 2019. Advances in Intelligent Systems and Computing, vol 1145. Springer, Cham. https://doi.org/10.1007/978-3-030-46828-6_9
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DOI: https://doi.org/10.1007/978-3-030-46828-6_9
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