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Title
Abstract
Key Takeaways
Figures
Introduction
Results and Discussion
Conclusion
Future Work
References

IoT based Interactive Smart Mirror

Profile image of Samana JafriSamana Jafri

2017

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4 pages

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Abstract

Recent Advancement in Internet of Things (IoT) technology has seen many application mainly related with automation. Modernizing home appliances have become a trend but the only thing that has not been modernized is mirror. The Mirror being the most used objects in the house but there’s been no advancement in its design and application. Our project focuses on modernizing the mirror by enhancing its functionality at the same time make it more interactive and useful in saving our precious time. A mirror’s function is to display reflection of anything that comes in front of it. We present the idea of Smart Mirror which displays real-time information like mobile notifications, email notifications, Calendar, Live weather updates, reminders, and so on. In addition to this Amazon’s Alexa services have been used so that mirror takes voice commands from user. Available Smart Mirror lacks privacy of data and makes use of PIR sensor to recognize a human being also that Smart Mirror can only be ...

Key takeaways
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  1. The project proposes an IoT-based Smart Mirror enhancing interactivity with real-time notifications and voice commands.
  2. Facial recognition uses Local Binary Patterns Histogram for secure user identification and privacy protection.
  3. Raspberry Pi 3 B+ supports system functionality with a 1.2GHz CPU and 1GB RAM, enabling efficient processing.
  4. Using an external flash light increases facial recognition accuracy significantly during user image capture.
  5. Future applications include industry use for worker scheduling and enhanced communication through integrated Alexa services.
Figures (3)
In second case scenario, we capture and train the image of user with same distance but we added an external flash light with camera. The result of this scenario is shown in table 2 below. We developed Facial Recognition system in Smart Mirror using Local Binary Pattern Face Recognition algorithm to provide privacy to user. To test how this algorithm behaves in real life, we conducted some test as discuss below. In first test scenario, we captured and trained user image through the distance of 1 foot, 2 foot and 2.5 foot respectively and tested the accuracy. The accuracy is tested by conducting 10 recognition in a row. The result is shown in table 1 below.
In second case scenario, we capture and train the image of user with same distance but we added an external flash light with camera. The result of this scenario is shown in table 2 below. We developed Facial Recognition system in Smart Mirror using Local Binary Pattern Face Recognition algorithm to provide privacy to user. To test how this algorithm behaves in real life, we conducted some test as discuss below. In first test scenario, we captured and trained user image through the distance of 1 foot, 2 foot and 2.5 foot respectively and tested the accuracy. The accuracy is tested by conducting 10 recognition in a row. The result is shown in table 1 below.
We intend to keep researching user-adaptive services and systems by keeping on the evaluation to learn how much convenience the user will experience and how well the user will use when using this individually customized automatic system. When we started working on the system, it was figured that interface would allow any direct interaction with using the mirror. This would result in home automation shelf security which is accomplished using speech recognition. What was even more significant was the fact that the mirror should be usable as a normal mirror reflecting the person, and thus it should not be fully filled with unwanted information. Only the outer corners should be used for content display, leaving enough room to see the person. In this work honest efforts have been made to develop a system that is not only smart but also interactive with varied functionalities to carry out tasks with high precision and efficiency. The basic mirror that we know was changed to a new interactive system. With the help of amazon’s Alexa voice services (AVS) the system became voice enabled and opened the door for users to communicate through voice so anyone can use it. So a physically challenged user can also use it. User’s privacy security has been major problem throughout the process but this was solved by using face recognition technique. Now the user no longer have to worry about the security of his information. The real time notification was the key to the project.
We intend to keep researching user-adaptive services and systems by keeping on the evaluation to learn how much convenience the user will experience and how well the user will use when using this individually customized automatic system. When we started working on the system, it was figured that interface would allow any direct interaction with using the mirror. This would result in home automation shelf security which is accomplished using speech recognition. What was even more significant was the fact that the mirror should be usable as a normal mirror reflecting the person, and thus it should not be fully filled with unwanted information. Only the outer corners should be used for content display, leaving enough room to see the person. In this work honest efforts have been made to develop a system that is not only smart but also interactive with varied functionalities to carry out tasks with high precision and efficiency. The basic mirror that we know was changed to a new interactive system. With the help of amazon’s Alexa voice services (AVS) the system became voice enabled and opened the door for users to communicate through voice so anyone can use it. So a physically challenged user can also use it. User’s privacy security has been major problem throughout the process but this was solved by using face recognition technique. Now the user no longer have to worry about the security of his information. The real time notification was the key to the project.

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References (5)

  1. Dongyu Wang, Dixon Lo, Janak Bhimani and Kazunori Sugiura "AnyControl -IoT based Home Appliances Monitoring and Controlling,"IEEE 39th Annual International Computers, Software & Applications Conference, September 2015.
  2. Jovan Ivković, Biljana Radulović,"The advantages of using raspberry pi3 compared to raspberry pi2 SoC computer for sensor system supports,"International Conference on Applied Internet and Information Technologies, 2016.
  3. Athira S, Frangly Francis, Radwin Raphel, "SMART MIRROR: A Novel Framework for Interactive Display," inIEEE International Conference on Circuit, Power and Computing Technologies [ICCPCT], March 2016.
  4. Chakka Mounica and Venugopal P, "Face Detection and Recognition using LBPH," on International Journal of Engineering Research and Science & Technology, Vol. 5, No. 3, August 2016.
  5. Mohamed Ahmed Hail andStefan Fischern, "Flexible API for IoT Services with Named Data Networking," 2016 IEEE International Conference on Emerging Technologies and Innovative Business Practices for the Transformation ofSocieties (EmergiTech).

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