| dc.contributor | 資科系;傳播學院數位學程 | |
| dc.creator (作者) | Liao, Chun-Feng;Cheng, Chao-Ting;Weng, Tzu-Yuan;Lu, Wei-Chen;Chen, Kung | |
| dc.creator (作者) | 廖峻鋒;陳恭 | zh_TW |
| dc.date (日期) | 2015-01 | |
| dc.date.accessioned | 22-Jun-2016 17:10:23 (UTC+8) | - |
| dc.date.available | 22-Jun-2016 17:10:23 (UTC+8) | - |
| dc.date.issued (上傳時間) | 22-Jun-2016 17:10:23 (UTC+8) | - |
| dc.identifier.uri (URI) | http://nccur.lib.nccu.edu.tw/handle/140.119/98231 | - |
| dc.description.abstract (摘要) | A Pervasive-computing-enriched smart environment, which contains hundreds of embedded devices coordinated by service management mechanisms, is capable of anticipating intensions of occupants and providing appropriate services accordingly. To acquire high-level contexts, such as human activities, usually involves analyzing and identifying causality and temporal ordering relationships among a bulk stream of sensor readings. However, there are relatively few works investigating this issue. We notice that Complex Event Processing (CEP) is useful for dealing with the issue mentioned above. In this work, we propose a platform for integrating CEP concepts with Per SAM, a service application model for pervasive environments. Applications and experiments are performed to verify the effectiveness of the proposed platform. | |
| dc.format.extent | 270807 bytes | - |
| dc.format.mimetype | application/pdf | - |
| dc.relation (關聯) | Proc. International Conference on Platform Technology and Service, 2015, 7-8 | |
| dc.subject (關鍵詞) | Bismuth; Time-Causality Analysis; Smart Environments; Complex Event Processing | |
| dc.title (題名) | A Platform for Detecting High-Level Contexts from Complex Event Streams in Pervasive Environment | |
| dc.type (資料類型) | conference | |
| dc.identifier.doi (DOI) | 10.1109/PlatCon.2015.22 | |
| dc.doi.uri (DOI) | http://dx.doi.org/10.1109/PlatCon.2015.22 | |
