Name
Abstract | ||
|---|---|---|
In this paper, we present a novel application, HeatWatch, which predicts heatstroke and prevents heatstroke by ensuring users breaking and water intake. The application estimates user's core temperature based on human thermal model and vital sensors equipped with smart watches. We also designed the application tracks user's water intake by assuming to apply existing activity recognition technique to acceleration sensors inside a smart watch. We have discussed how to detect heatstroke sign and evaluated its performance through a real data set over 100 hours. Finally, the result showed that our method is able to instantly notify high temperature states with more than 0.9 recall and 0.53 precision by allowing early/late notification within 6 minutes. |
Year | Venue | Field |
|---|---|---|
2017 | 2017 IEEE INTERNATIONAL CONFERENCE ON PERVASIVE COMPUTING AND COMMUNICATIONS WORKSHOPS (PERCOM WORKSHOPS) | Thermal model,Activity recognition,Computer science,Simulation,Heatstroke,Core temperature,Acceleration,Smartwatch,Water heating |
DocType | ISSN | Citations |
Conference | 2474-2503 | 0 |
PageRank | References | Authors |
0.34 | 4 | 3 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Takashi Hamatani | 1 | 12 | 5.27 |
| Akira Uchiyama | 2 | 78 | 14.48 |
| Higashino, T. | 3 | 19 | 15.19 |