Name
Title | ||
|---|---|---|
Energy Considerations for Continuous Group Activity Recognition Using Mobile Devices: The Case of GroupSense |
Abstract | ||
|---|---|---|
Human activity recognition using mobile sensors is becoming increasingly important. Scaling up from individuals to groups, that is, Group Activity Recognition (GAR), has attracted significant attention recently. This paper investigates energy consumption for GAR and proposes a novel distributed middleware called GroupSense for mobile GAR. We implemented and tested GroupSense, which incorporates a protocol for the exchange of information required for GAR. We also investigated the battery drain of continuous activity recognition in a range of simple GAR scenarios. We then conclude with lessons learnt for GAR. |
Year | DOI | Venue |
|---|---|---|
2016 | 10.1109/AINA.2016.94 | 2016 IEEE 30th International Conference on Advanced Information Networking and Applications (AINA) |
Keywords | Field | DocType |
group activity recognition,energy efficient group activity recognition,mobile sensing,context-awareness | Mobile computing,Middleware,Activity recognition,Computer science,Group activity recognition,Context awareness,Mobile device,Energy consumption,Mobile telephony,Distributed computing | Conference |
ISSN | Citations | PageRank |
1550-445X | 1 | 0.35 |
References | Authors | |
13 | 4 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Amin B. Abkenar | 1 | 1 | 0.35 |
| Seng Wai Loke | 2 | 778 | 88.71 |
| J. Wenny Rahayu | 3 | 1275 | 106.72 |
| Arkady B. Zaslavsky | 4 | 943 | 168.27 |