MEC202

Project Background and Objectives

Background: To help people with social phobia and social enthusiasts express themselves better and integrate into social occasions, a smart mask was designed.

Market Research: A questionnaire survey was conducted among college students. The results showed that 53% of the respondents were willing to wear it. Users expected the mask to change expressions through head movements, voice, and environmental brightness. Most of them thought that the mask was helpful to adapt to the party atmosphere and relieve communication pressure. The acceptable price was mostly between 100 – 400 yuan.

Project Planning and Division of Labor: The team members had a clear division of labor. Hong.Qin was responsible for material procurement and sample production, etc.; Chang.Liu was responsible for sensor code implementation, etc.; Yuxuan.Sun was responsible for circuit construction and hardware-software connection, etc.; Hanbo.Zheng was responsible for report writing and team content integration, etc.; Qian.Cheng was responsible for the implementation of the gyroscope sensor, etc. Each person’s contribution accounted for 20%.

Design Concepts

It aims to solve the problems of people with social difficulties and enhance the social experience. Intelligent technology is integrated to enable the mask to adjust expressions according to head movements, environmental brightness and voice volume. Compared with existing masks, it has unique technical styles and multiple functions.

Functions of the Mask

Gyroscope Sensor: It can detect head movements (such as shaking, nodding, turning) in real time and convert them into digital signals to drive the expression changes of the mask and enhance interactivity.

Brightness Sensor: It can detect the ambient light intensity and automatically adjust the brightness of the LEDs on the mask to ensure that the expressions are clearly visible and without glare in different lighting conditions, improving the user experience.

Sound Sensor and Touch Sensor: The sound sensor detects the voice volume, and the touch sensor controls the switch of the voice expression change function. The two sensors work together to enable the mask to better convey the user’s emotions and adapt to different scenarios and user needs.

Prototyping and Testing

Prototyping

Circuit Construction: Sound, light, acceleration and touch sensors were used to realize voice detection, brightness adjustment, head movement sensing and function control respectively, and the corresponding circuits were constructed.

Prototype Design: The appearance of the mask was inspired by anime. It consists of a 268-LED light board, two brackets and two semicircular structures. The design was optimized to ensure the reasonable layout of circuit components. The Arduino nano board was used and the expressions were edited by programming the LEDs.

Logic Design: After the mask is powered on, it first performs a self-test and then enters a loop. The brightness sensor detects the ambient light and adjusts the LED brightness; the touch sensor determines the working state of the sound sensor, and when the sound is greater than the set value, the mask expression changes; in the normal mode, the acceleration sensor detects head movements and triggers expression changes.

Programming Implementation: Corresponding codes were written for different sensors. The gyroscope sensor changes the expression by calculating the average value to judge the head movement; the sound sensor changes the expression when the voice volume exceeds the threshold; the touch sensor switches the working mode of the mask; the brightness sensor adjusts the LED brightness according to the ambient light intensity.

Testing plans

Automatic Brightness Test: Some sensors were turned off to simulate the change of ambient light. The test results showed that the mask could respond accurately and the automatic brightness adjustment effect was good in different scenarios.

Speech Recognition Test: A large number of users were invited to test in different noisy environments to ensure that the speech recognition function worked properly and track the problems to improve the product.

Expression Control Test: 100 volunteers were tested, data and feedback were collected, problems were classified and processed, and the report was updated and the code was adjusted in time.

User Feedback: Users recognized the facial expression control, speech recognition and automatic brightness adjustment functions of the mask, but also pointed out that there were problems such as delay, misjudgment and failure. They also hoped to add more expressions and voice commands and develop a supporting application program.

Project Summary

Through sensor technology, the core functions of the mask are realized, which improves the user experience and operation convenience and has practical value in social scenarios. In the future, functions and interactivity can be considered to be added to further enhance the user experience.