Name
Abstract | ||
|---|---|---|
This paper introduces basic concept of mood fatigue detection and existing solutions as well as some typical solutions, such as mobile sensing and cloud computing technology. In the first place, we sum up main challenges of mood fatigue detection and the direction of future study. Then one type of system implementation is put forward, such system consists of: 1) Wearable devices used to detect the users’ mood fatigue; 2) Clouds data center; 3) Application and service manager. We take overall consideration of many factors like the user’s physiological information, external environment conditions and user behavior, evaluate accurately through big data analytic technology the users’ state of mood fatigue and to what extent shall one keeps vigilant as well as what measures shall be adopted to improve the users’ working performance and alert the users to keep themselves away from the danger. Finally a real system is established in this paper, it is composed of the smart clothing, cloud platform and mobile terminal application. |
Year | DOI | Venue |
|---|---|---|
2016 | https://doi.org/10.1007/s11036-016-0757-x | MONET |
Keywords | Field | DocType |
Mood fatigue,Deep learning,Convolution auto-encoder | Mood,Service management,Computer security,Computer science,Implementation,Artificial intelligence,Deep learning,Wearable technology,Data center,Big data,Cloud computing | Journal |
Volume | Issue | ISSN |
21 | 5 | 1383-469X |
Citations | PageRank | References |
1 | 0.35 | 26 |
Authors | ||
7 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Xiaobo Shi | 1 | 6 | 1.81 |
| Yixue Hao | 2 | 583 | 27.68 |
| Delu Zeng | 3 | 164 | 11.46 |
| Lu Wang | 4 | 32 | 1.38 |
| M. Shamim Hossain | 5 | 1171 | 83.62 |
| Sk. Md. Mizanur Rahman | 6 | 23 | 2.50 |
| Abdulhameed Al-elaiwi | 7 | 631 | 47.05 |