University of Oulu

Konomi S., Sasao T., Hosio S., Sezaki K. (2017) Exploring the Use of Ambient WiFi Signals to Find Vacant Houses. In: Braun A., Wichert R., Maña A. (eds) Ambient Intelligence. AmI 2017. Lecture Notes in Computer Science, vol 10217. Springer, Cham. DOI: 10.1007/978-3-319-56997-0_10

Exploring the use of ambient WiFi signals to find vacant houses

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Author: Konomi, Shin’ichi1; Sasao, Tomoyo1; Hosio, Simo2;
Organizations: 1Center for Spatial Information Science, The University of Tokyo, Kashiwa, Japan
2Center for Ubiquitous Computing, The University of Oulu, Oulu, Finland
Format: article
Version: accepted version
Access: open
Online Access: PDF Full Text (PDF, 0.3 MB)
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Language: English
Published: Springer Nature, 2017
Publish Date: 2019-04-05


In many countries, the population is either declining or rapidly concentrating in big cities, which causes problems in the form of vacant houses in many local communities. It is often challenging to keep track of the locations and the conditions of vacant houses, and for example in Japan, costly manual field studies are employed to map the occupancy situation. In this paper, we propose a technique to infer the locations of occupied houses based on ambient WiFi signals. Our technique collects RSSI (Received Signal Strength Indicator) data based on opportunistic smartphone sensing, constructs hybrid networks of WiFi access points, and analyzes their geospatial patterns based on statistical shape modeling. We show that the technique can successfully infer occupied houses in a suburban residential community, and argue that it can substantially reduce the cost of field surveys to find vacant houses as the number of potential houses to be inspected decreases.

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Series: Lecture notes in computer science
ISSN: 0302-9743
ISSN-E: 1611-3349
ISSN-L: 0302-9743
ISBN: 978-3-319-56997-0
ISBN Print: 978-3-319-56996-3
Pages: 130 - 135
DOI: 10.1007/978-3-319-56997-0_10
Host publication: 13th European Conference, AmI 2017 Malaga, Spain, April 26–28, 2017 Proceedings
Host publication editor: Braun, Andreas
Wichert, Reiner
Maña, Antonio
Conference: Conference on Ambient Intelligence, AmI
Type of Publication: A4 Article in conference proceedings
Field of Science: 222 Other engineering and technologies
Copyright information: © Springer International Publishing AG 2017. This is a post-peer-review, pre-copyedit version of an article published in 13th European Conference, AmI 2017 Malaga, Spain, April 26–28, 2017 Proceedings. The final authenticated version is available online at: