Design of the sleeping aid system based on face recognition
Introduction
Sleep is an important physiological phenomenon in the process of life. If all the sleeping time on one's life is added up, it will occupy one third of one's life. Sleep and health, a joint report by the world health organization and the world sleep research organization, says the average amount of sleep we get per night fell by more than 20% in the 20th century, with jet lag, shift work and other modern lifestyles contributing to a significant increase in sleep problems [1]. Lack of sleep can lead to a series of problems such as memory, thinking, imagination, creativity and attention loss [2]. At the same time, due to the rapid development and widespread popularity of smart phones and the Internet, people's social lifestyle has also changed a lot. Therefore, the trend of shortened sleep time is likely to continue. Sleep problems have become a “silent epidemic”.
Under the background that life pressure and sleep problems have become world problems, this paper studies the factors affecting sleep and starts from the perspective that music can improve the sleep condition. It is composed of Arduino, Raspberry Pi, camera, DHT11, light intensity sensor and other hardware. Through sensor technology and face recognition, it uses air conditioning, lighting, audio and other home appliances to form an intelligent home and adjust the temperature, light intensity and music of the sleep environment to improve the sleep efficiency.
This design system is based on the Internet of things and smart home.
Since the beginning of the 21st century, the Internet of things has developed rapidly and penetrated into life, production and other fields. Smart home as the application of the Internet of things industry into the line of sight. Smart home makes use of modern science and technology, such as Internet of things, mobile Internet and other technologies to connect all kinds of household equipment in traditional houses, so as to form an efficient, convenient and comfortable smart home environment [3]. Smart home can realize home appliances control and environmental detection, and then the home life for scientific intelligent management. In life, smart home and people have the most direct connection, because it can provide different services according to different users. So we combine the existing hardware, technology and home products to design an intelligent sleep aid home system, and put forward the sleep aid design, to create a comfortable and happy living environment.
Regular life, healthy body condition, comfortable sleeping environment (such as temperature, sound, light, color, aroma, etc.) are very important to have a good sleep. This paper aims at improving the external environment based on the factors of sleep environment, so that the sleep aid system can play a role.
- 1.
Temperature factor
Under the background of global warming and heat island effect, temperature, as an important environmental factor, has been one of the hot spots of domestic and foreign scholars [4], [5]. Good sleep is closely related to body temperature. To get good sleep, one must master the ambient temperature. The relationship between sleep and body temperature has been confirmed by more and more scientists. When the temperature is 25–28 ℃ in summer and 16–20 ℃ in winter [6], it is easier to fall asleep. People of different ages are slightly different.
- 2.
Light factor
Once, Lisa Shives, medical director of the north coast sleep institute in Illinois, United States, clearly stated that light is one of the main factors affecting sleep, and light plays a crucial role in the biological clock [7].For example, you can go to bed with your curtains closed and wake up in the morning without feeling any changes in the light outside. Or forcing yourself out of sleep with an alarm in the dark. In either case, the body is still at rest, and being suddenly awakened can be harmful to the body, causing nerve fatigue and affecting sleep quality.
- 3.
Sound factor
Music can help us improve sleep, and music has a significant impact on human physiological functions. For example, the rhythm, pattern and melody of music can affect a listener's heart rate, breathing and blood pressure. There are many randomized controlled trials (RCTs) at home and abroad that study music for sleep problems. For example, Wenjuan et al. [8] applied music therapy to insomnia patients, and polysomnography showed significant improvement in sleep indicators. Johnson [9] found that music therapy for insomnia patients can shorten the sleep latency and reduce the number of waking up at night. At present, domestic and foreign medical workers using music treatment insomnia has achieved significant results. Clinical practice also proves that music can be used as one of the important means to improve sleep.
Section snippets
The design scheme of the system
Based on the consideration of cost and practical operation, this design adopts all the open source and relatively cheap devices and software to build a platform model of intelligent sleeping home for the Internet of things. Software and hardware are organized according to the three-layer architecture of the Internet of things from the bottom to the top: perception layer, transport layer and application layer [10], as shown in Fig. 1.
- 1.
Perception layer
It is controlled by an Arduino development
Raspberry Pi
The Raspberry Pi is an arm-based computer, the size of a bank card, that can connect to TVS, monitors, keyboards and mice. It was originally designed to provide students with cheap equipment for computer learning, but because of its powerful performance, including data processing, table processing, media center and so on, it is quickly widely used. Raspberry Pi has developed to the third generation, the CPU is 4 core ARM Cortex-A53, can smoothly execute multi-threaded tasks, so as to meet a
Facial expression recognition
Facial expression recognition is an innovation of this system. The 5-megapixel dedicated camera perfectly docks with the interface reserved on the raspberry Pi motherboard. Compared with Arduino, raspberry Pi can process audio and video information more easily and conveniently. Through raspberry Pi, we can complete the extraction and recognition of facial expressions by programming with Python language. The judged emotional results are returned to the system, and according to the results, the
Hardware test
The test environment is first built using hardware components. The hardware used includes: smart phone, STM32 with nb-iot integration, Arduino UNO, raspberry Pi, sensor, camera, music player, etc. The physical connection diagram is shown in Fig. 10. Then, the corresponding software was written for the hardware. After the compilation, the program was downloaded to the core board of the specified module, and the program was debugged to make it work normally.
The system test considers the software,
Summary
The progress of science and technology makes intelligent hardware product and industry get development. With the popularity of the Internet and the introduction of mobile smart devices into our lives, sleep health products have also entered the market. People begin to pay attention to sleep health and gradually realize the importance of sleep. This paper discusses the relationship between the whole sleep environment and the man-machine interaction in the environment, that is, forming the
Declaration of Competing Interest
The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.
Xiaonan Zhao received Ph.D. degree from Tianjin University, Tianjin, in 2015. Currently, he is working at the College of Electronic and Communication Engineering, Tianjin Normal University. His research interests include wireless communication channel measurement and modeling.
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Xiaonan Zhao received Ph.D. degree from Tianjin University, Tianjin, in 2015. Currently, he is working at the College of Electronic and Communication Engineering, Tianjin Normal University. His research interests include wireless communication channel measurement and modeling.
Jingjing Li entered the school of electronics and communication en-gineering, Tianjin Normal University in 2016. In 2018, she participated in the engineer program and studied communication related majors. At pre-sent, her research interest is electronic hardware debugging.
Wenqiang Liu now studying at the School of Computer and Information Engineering of Tianjin Normal University, specializing in network engineering, participated in the China University Student Service Outsourcing Innovation and Entrepreneurship Competition and designed the "Intelligent Waste Classification System Based on Internet of Things" to win the 12th Chinese Collegiate Computing Competition(CCCC) the first prize .His team also won 2019 HUA WEI CUP National Undergraduate IOT Design Contest the second price. He is currently studying the Internet of Things, has designed the IoT project of smart car, smart home and intelligent garbage sorting system.
Junjie Zhang majored in electronic information science and technology, studying at Hexi College. In 2017, he went to Tianjin Normal University as an exchange student. His current interests include integrated circuits and artificial intelligence.
Yang Li received the B.E. and M.E. degrees from the College of Information Technology and Science, Nankai University, Tianjin, in 2008 and 2012, respectively, and the Ph.D. degree from the Department of Engineering, Tohoku University, Sendai, in 2017. He is currently with the College of Electronic and Communication Engineering, Tianjin Normal University. His research interests include antenna design, EM-wave propagation, and sensor networks.
This work was supported by the Natural Science Foundation of Tianjin City (No. 18JCYBJC86400); Doctor Fund of Tianjin Normal University (No. 52XB1604); Natural Science Foundation of Tianjin City (No. 19JCQNJC01300); Doctor Fund of Tianjin Normal University (No. 52XB1905); Natural Science Foundation of Tianjin City (No. 18JCQNJC70900); National Natural Science Foundation of China (No. 61704122); National Natural Science Foundation of China (No. 61801327).