Smart Indoor Home Surveillance Monitoring System Using Raspberry Pi

Lee Han Keat - University Tun Hussein Onn Malaysia, Johor, Malaysia
Chuah Wen - University Tun Hussein Onn Malaysia, Johor, Malaysia

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Internet of Things (IoTs) are internet computing devices which are connected to everyday objects that can receive and transmit data intelligently. IoTs allow human to interact and control everyday objects wirelessly to provide more convenience in their lifestyle. The Raspberry Pi is a small, lightweight and cheap single board computer that can fit on human’s palm. Security plays a big role in a home. People concern about security by preventing any intruders to enter their home. This is to prevent loss of privacy and assets. The closed-circuit television (CCTV) is one of the device used to monitor the secured area for any intruders. The use of traditional CCTV to monitor the secured area have three limitations, which are requiring a huge volume of storage to store all the videos regardless there are intruders or not, does not notify the users immediately when there are motions detected, and users must always check the CCTV recorded videos regularly to identity any intruders. Therefore, a smart surveillance monitoring system is proposed to solve this problem by detecting intruders and capturing image of the intruder. Notifications will also be sent to the user immediately when motions are detected. This smart surveillance monitoring system only store the images of the intruders that triggered the motion sensor, making this system uses significantly less storage space. The proposed Raspberry Pi is connected with a passive infrared (PIR) motion sensor, a webcam and internet connection, the whole device can be configured to carry out the surveillance tasks. The objectives of this project are to design, implement and test the surveillance system using the Raspberry Pi. This proposed surveillance system provides the user with live stream of video feed for the user. Whenever a motion is detected by the PIR motion sensor, the web camera may capture an image of the intruder and alert the users (owners) through Short Message Service (SMS) and email notifications. The methodology used to develop this system is by using the object-oriented analysis and design (OOAD) model.


internet of things; Raspberry Pi; closed-circuit television; smart surveillance monitoring system; short message service; e-mail

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Pi, R. (2013). Raspberry pi. Raspberry Pi, 1, 1.

Richardson, M., & Wallace, S. (2012). Getting started with raspberry PI. " O'Reilly Media, Inc.".

Upton, E., & Halfacree, G. (2014). Raspberry Pi user guide. John Wiley & Sons.

Rao, P. B., & Uma, S. K. (2015). Raspberry Pi home automation with wireless sensors using smart phone. Int. J. Comput. Sci. Mob. Comput, 4, 797-803.

Senthilkumar, G., Gopalakrishnan, K., & Kumar, V. S. (2014). Embedded image capturing system using raspberry pi system. International Journal of Emerging Trends & Technology in Computer Science, 3(2), 213-215.

McManus, S., & Cook, M. (2017). Raspberry Pi for dummies. John Wiley & Sons.

Maksimović, M., Vujović, V., Davidović, N., Milošević, V., & Perišić, B. (2014). Raspberry Pi as Internet of things hardware: performances and constraints. design issues, 3, 8.

Ferdoush, S., & Li, X. (2014). Wireless sensor network system design using Raspberry Pi and Arduino for environmental monitoring applications. Procedia Computer Science, 34, 103-110.

Dennis, A. K. (2013). Raspberry Pi home automation with Arduino. Packt Publishing Ltd.

Ha, K. N., Lee, K. C., & Lee, S. (2006, October). Development of PIR sensor based indoor location detection system for smart home. In SICE-ICASE, 2006. International Joint Conference (pp. 2162-2167). IEEE.

McConnell, S. (2004). Code complete. Pearson Education.

Dempsey, John S. (2008). Introduction to private security. Belmont, CA: Thomson Wadsworth. p. 78. ISBN 9780534558734.

Armitage, R. (2002). To CCTV or not to CCTV. A review of current research into the effectiveness of CCTV systems in reducing crime, 8.

Kruegle, H. (2011). CCTV Surveillance: Video practices and technology. Butterworth-Heinemann.

Park, J. O., & Kim, S. (2015). Study on strengthening plan of safety network CCTV monitoring by steganography and user authentication. Advances in Multimedia, 2015, 10.

Keval, H. (2006, September). Cctv control room collaboration and communication: Does it work?. In Proceedings of human centred technology workshop (pp. 11-12)..

Lee, J. V., Chuah, Y. D., & Chai, C. T. (2013). A multilevel home security system (mhss). International Journal of Smart Home, 7(2).

Poole, N. R., Zhou, Q., & Abatis, P. (2009). Analysis of CCTV digital video recorder hard disk storage system. digital investigation, 5(3), 85-92.

Gerrard, G., Parkins, G., Cunningham, I., Jones, W., Hill, S., & Douglas, S. (2007). National CCTV Strategy. Home Office, London.

Boghossian, B. A., & Velastin, S. A. (1999, September). Motion-based machine vision techniques for the management of large crowds. In Electronics, Circuits and Systems, 1999. Proceedings of ICECS'99. The 6th IEEE International Conference on (Vol. 2, pp. 961-964). IEEE.

Design, O. O. (2009). Object-Oriented Analysis and Design.


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