Eigenplaces: Segmenting Space Through Digital Signatures
Researchers use eigendecomposition to leverage MIT's Wi-Fi network activity data and analyze to the physical environment. We proposed a method to analyze and categorize wireless access points based on common usage characteristics that reflect real-world, placed-based behaviors. It uses eigendec...
| Main Authors: | , , |
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| Other Authors: | |
| Format: | Article |
| Language: | en_US |
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Institute of Electrical and Electronics Engineers
2010
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| Subjects: | |
| Online Access: | http://hdl.handle.net/1721.1/52542 https://orcid.org/0000-0003-2026-5631 |
| Summary: | Researchers use eigendecomposition to leverage MIT's Wi-Fi network activity data and analyze to the physical environment. We proposed a method to analyze and categorize wireless access points based on common usage characteristics that reflect real-world, placed-based behaviors. It uses eigendecomposition to study the Wi-Fi network at the Massahusetts Institute of Technology (MIT), correlating data generated as a byproduct of network activity with the physical environment. Our approach provides an instant survey of building use across the entire campus at a surprisingly fine-grained level. The resulting eigenplaces have implications for reseach across a range of wireless technology as well as potential applications in network planning, traffic and tourism management, and even marketing. |
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