Selective Sampling Strategies to Conserve Power in Context Aware Devices
We analyze the use of selective sampling strategies to aid in power conservation in sensor platforms for context-aware systems. In particular, we study an activity-aware system based on the eWatch sensor and notification platform, developed at CMU. We collected 94 hours of self-annotated activity da...
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| creator | French, B. Siewiorek, D.P. Smailagic, A. Deisher, M. |
| description | We analyze the use of selective sampling strategies to aid in power conservation in sensor platforms for context-aware systems. In particular, we study an activity-aware system based on the eWatch sensor and notification platform, developed at CMU. We collected 94 hours of self-annotated activity data from four subjects over several days each. We compare sampling strategies according to several metrics, each of which satisfies a different set of application needs. These metrics include: accuracy as the percentage of time between samples that sampled activity matches true activity, average latency of detecting a change in activity, the percentage of missed activities, and the percentage of redundant samples. We consider both the performance differences between strategies as well as differences between subjects. Accuracies of over 95% were achievable using only 3% of the samples. |
| doi_str_mv | 10.1109/ISWC.2007.4373783 |
| format | Conference Proceeding |
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In particular, we study an activity-aware system based on the eWatch sensor and notification platform, developed at CMU. We collected 94 hours of self-annotated activity data from four subjects over several days each. We compare sampling strategies according to several metrics, each of which satisfies a different set of application needs. These metrics include: accuracy as the percentage of time between samples that sampled activity matches true activity, average latency of detecting a change in activity, the percentage of missed activities, and the percentage of redundant samples. We consider both the performance differences between strategies as well as differences between subjects. 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Accuracies of over 95% were achievable using only 3% of the samples.</description><subject>Accelerometers</subject><subject>Batteries</subject><subject>Computational complexity</subject><subject>Computer science</subject><subject>Context awareness</subject><subject>Energy consumption</subject><subject>Sampling methods</subject><subject>Sensor phenomena and characterization</subject><subject>Sensor systems</subject><subject>Wearable sensors</subject><issn>1550-4816</issn><issn>2376-8541</issn><isbn>9781424414529</isbn><isbn>1424414520</isbn><fulltext>true</fulltext><rsrctype>conference_proceeding</rsrctype><creationdate>2007</creationdate><recordtype>conference_proceeding</recordtype><sourceid>6IE</sourceid><sourceid>RIE</sourceid><recordid>eNotkN1Kw0AUhFdRsNQ-gHizL5C4J2d_L0v8aaGgEMXLsmnOlpU2KcnS6tsbsXMzMB8MzDB2ByIHEO5hWX2WeSGEySUaNBYv2MwZC7KQEqQq3CWbFGh0ZpWEKzYBpUQmLegbNhuGLzEKnTYKJ2xR0Y42KR6JV35_2MV2y6vU-0TbSANPHS-7dqB-5G_diXoe278k0Xfi85PviT_SMW5ouGXXwe8Gmp19yj6en97LRbZ6fVmW81UWCwkps4Ea3YARljziRiBYFcK4IkgRFIraaamCroUyHmujhXFNY2ow6FxdAOGU3f_3RiJaH_q49_3P-vwD_gJJuU4-</recordid><startdate>200710</startdate><enddate>200710</enddate><creator>French, B.</creator><creator>Siewiorek, D.P.</creator><creator>Smailagic, A.</creator><creator>Deisher, M.</creator><general>IEEE</general><scope>6IE</scope><scope>6IL</scope><scope>CBEJK</scope><scope>RIE</scope><scope>RIL</scope></search><sort><creationdate>200710</creationdate><title>Selective Sampling Strategies to Conserve Power in Context Aware Devices</title><author>French, B. ; Siewiorek, D.P. ; Smailagic, A. ; Deisher, M.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-i241t-8fed6d1708ea33c03185ff373f40f530b9645f6b057a3b76079dd7b17399b21e3</frbrgroupid><rsrctype>conference_proceedings</rsrctype><prefilter>conference_proceedings</prefilter><language>eng</language><creationdate>2007</creationdate><topic>Accelerometers</topic><topic>Batteries</topic><topic>Computational complexity</topic><topic>Computer science</topic><topic>Context awareness</topic><topic>Energy consumption</topic><topic>Sampling methods</topic><topic>Sensor phenomena and characterization</topic><topic>Sensor systems</topic><topic>Wearable sensors</topic><toplevel>online_resources</toplevel><creatorcontrib>French, B.</creatorcontrib><creatorcontrib>Siewiorek, D.P.</creatorcontrib><creatorcontrib>Smailagic, A.</creatorcontrib><creatorcontrib>Deisher, M.</creatorcontrib><collection>IEEE Electronic Library (IEL) Conference Proceedings</collection><collection>IEEE Proceedings Order Plan All Online (POP All Online) 1998-present by volume</collection><collection>IEEE Xplore All Conference Proceedings</collection><collection>IEEE Electronic Library (IEL)</collection><collection>IEEE Proceedings Order Plans (POP All) 1998-Present</collection></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>French, B.</au><au>Siewiorek, D.P.</au><au>Smailagic, A.</au><au>Deisher, M.</au><format>book</format><genre>proceeding</genre><ristype>CONF</ristype><atitle>Selective Sampling Strategies to Conserve Power in Context Aware Devices</atitle><btitle>2007 11th IEEE International Symposium on Wearable Computers</btitle><stitle>ISWC</stitle><date>2007-10</date><risdate>2007</risdate><spage>77</spage><epage>80</epage><pages>77-80</pages><issn>1550-4816</issn><eissn>2376-8541</eissn><eisbn>9781424414529</eisbn><eisbn>1424414520</eisbn><abstract>We analyze the use of selective sampling strategies to aid in power conservation in sensor platforms for context-aware systems. In particular, we study an activity-aware system based on the eWatch sensor and notification platform, developed at CMU. We collected 94 hours of self-annotated activity data from four subjects over several days each. We compare sampling strategies according to several metrics, each of which satisfies a different set of application needs. These metrics include: accuracy as the percentage of time between samples that sampled activity matches true activity, average latency of detecting a change in activity, the percentage of missed activities, and the percentage of redundant samples. We consider both the performance differences between strategies as well as differences between subjects. Accuracies of over 95% were achievable using only 3% of the samples.</abstract><pub>IEEE</pub><doi>10.1109/ISWC.2007.4373783</doi><tpages>4</tpages></addata></record> |
| fulltext | fulltext |
| identifier | ISSN: 1550-4816 |
| ispartof | 2007 11th IEEE International Symposium on Wearable Computers, 2007, p.77-80 |
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| language | eng |
| recordid | cdi_ieee_primary_4373783 |
| source | Alma/SFX Local Collection |
| subjects | Accelerometers Batteries Computational complexity Computer science Context awareness Energy consumption Sampling methods Sensor phenomena and characterization Sensor systems Wearable sensors |
| title | Selective Sampling Strategies to Conserve Power in Context Aware Devices |
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