Smart City Gnosys
Smart city article details
| Title | From Faces To Traffic Lights: A Multi-Scale Approach For Emotional State Representation |
|---|---|
| ID_Doc | 27190 |
| Authors | Nguyen M.; Yan W.Q. |
| Year | 2023 |
| Published | Proceedings - 2023 IEEE International Conference on High Performance Computing and Communications, Data Science and Systems, Smart City and Dependability in Sensor, Cloud and Big Data Systems and Application, HPCC/DSS/SmartCity/DependSys 2023 |
| DOI | http://dx.doi.org/10.1109/HPCC-DSS-SmartCity-DependSys60770.2023.00136 |
| Abstract | This paper presents an innovative Smart Traffic Light System designed to assess Emotional Expression in enclosed settings such as corporate offices and educational facilities. The system combines artificial intelligence, super-resolution algorithms, and facial recognition to provide both real-time and longitudinal insights into the collective emotional atmosphere. Utilizing a three-tier light indicator, the system visualizes emotional trends in the short-term (immediate), medium-term (daily or weekly), and long-term (semi-annual or annual) contexts, employing a color-coded scheme to denote positive or negative emotional states. This augments situational awareness and contributes to the emotional well-being of individuals in these settings. The underlying technology leverages closed-circuit television (CCTV) footage and introduces a state-of-the-art temporal expression recognition mechanism to capture a broad spectrum of human emotions. A notable innovation is the incorporation of facial super-resolution techniques to enhance the quality of low-resolution facial data, thereby boosting the system's overall accuracy and robustness. This enhancement is accomplished while maintaining adherence to ethical standards for data collection and usage. This system has implications that reach far beyond simple emotional recognition. It serves as a cornerstone for the development of emotionally intelligent smart cities. Providing both immediate feedback and historical data on community emotional states, it enables more informed decision-making, streamlined resource allocation, and ultimately, an improvement in the overall quality of life. This research contributes to the evolving discussion on how smart cities can foster communities that are not just more efficient, but also more emotionally resilient. © 2023 IEEE. |
| Author Keywords | Artificial Intelligence; Emotional Recognition; Facial Detection; Image Facial Super Resolution; Smart Cities; Temporal Expression Recognition; Urban Environments; Wellbeing |
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