Title:
Infrastructure mediated sensing
Infrastructure mediated sensing
| dc.contributor.advisor | Abowd, Gregory D. | |
| dc.contributor.author | Patel, Shwetak Naran | en_US |
| dc.contributor.committeeMember | Edwards, W. Keith | |
| dc.contributor.committeeMember | Grinter, Rebecca | |
| dc.contributor.committeeMember | LaMarca, Anthony | |
| dc.contributor.committeeMember | Starner, Thad | |
| dc.contributor.department | Computing | en_US |
| dc.date.accessioned | 2008-09-17T19:57:02Z | |
| dc.date.available | 2008-09-17T19:57:02Z | |
| dc.date.issued | 2008-07-08 | en_US |
| dc.description.abstract | Ubiquitous computing application developers have limited options for a practical activity and location sensing technology that is easy-to-deploy and cost-effective. In this dissertation, I have developed a class of activity monitoring systems called infrastructure mediated sensing (IMS), which provides a whole-house solution for sensing activity and the location of people and objects. Infrastructure mediated sensing leverages existing home infrastructure (e.g, electrical systems, air conditioning systems, etc.) to mediate the transduction of events. In these systems, infrastructure activity is used as a proxy for a human activity involving the infrastructure. A primary goal of this type of system is to reduce economic, aesthetic, installation, and maintenance barriers to adoption by reducing the cost and complexity of deploying and maintaining the activity sensing hardware. I discuss the design, development, and applications of various IMS-based activity and location sensing technologies that leverage the following existing infrastructures: wireless Bluetooth signals, power lines, and central heating, ventilation, and air conditioning (HVAC) systems. In addition, I show how these technologies facilitate automatic and unobtrusive sensing and data collection for researchers or application developers interested in conducting large-scale in-situ location-based studies in the home. | en_US |
| dc.description.degree | Ph.D. | en_US |
| dc.identifier.uri | http://hdl.handle.net/1853/24829 | |
| dc.publisher | Georgia Institute of Technology | en_US |
| dc.subject | Ubiquitous computing | en_US |
| dc.subject | Human-computer interaction | en_US |
| dc.subject | Sensing | en_US |
| dc.subject | Power lines | en_US |
| dc.subject | Activity sensing | en_US |
| dc.subject | Location tracking | en_US |
| dc.subject.lcsh | Ubiquitous computing | |
| dc.subject.lcsh | Sensor networks | |
| dc.subject.lcsh | Detectors | |
| dc.subject.lcsh | Context-aware computing | |
| dc.subject.lcsh | Multisensor data fusion | |
| dc.title | Infrastructure mediated sensing | en_US |
| dc.type | Text | |
| dc.type.genre | Dissertation | |
| dspace.entity.type | Publication | |
| local.contributor.advisor | Abowd, Gregory D. | |
| local.contributor.corporatename | College of Computing | |
| local.relation.ispartofseries | Doctor of Philosophy with a Major in Computer Science | |
| relation.isAdvisorOfPublication | a9e4f620-85d6-4fb9-8851-8b0c3a0e66b4 | |
| relation.isOrgUnitOfPublication | c8892b3c-8db6-4b7b-a33a-1b67f7db2021 | |
| relation.isSeriesOfPublication | 41e6384f-fa8d-4c63-917f-a26900b10f64 |
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