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Context Recognition in Multiple Occupants Situations: Detecting the Number of Agents in a Smart Home Environment with Simple Sensors
Örebro University, School of Science and Technology. (Machine Perception and Interaction Lab, Center for Applied Autonomous Sensor Systems, AASS)ORCID iD: 0000-0002-2385-9470
Örebro University, School of Science and Technology. (Machine Perception and Interaction Lab, Center for Applied Autonomous Sensor Systems, AASS)ORCID iD: 0000-0002-4001-2087
Örebro University, School of Science and Technology. (Center for Applied Autonomous Sensor Systems, AASS)ORCID iD: 0000-0002-0458-2146
Örebro University, School of Science and Technology. (Center for Applied Autonomous Sensor Systems, AASS)
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2017 (English)In: Knowledge-based techniques for problem solving and reasoning(KnowProS 2017): A workshop at AAAI 2017, February 5, 2017, San Francisco, U.S.A., Palo Alto: AAAI Press, 2017, Vol. ws17, p. 758-764, article id WS-17-12Conference paper, Published paper (Refereed)
Abstract [en]

Context-recognition and activity recognition systems in multi-user environments such as smart homes, usually assume to know the number of occupants in the environment. However, being able to count the number of users in the environment is important in order to accurately recognize the activities of (groups of) agents. For smart environments without cameras, the problem of counting the number of agents is non-trivial. This is in part due to the difficulty of using a single non-vision based sensors to discriminate between one or several persons, and thus information from several sensors must be combined in order to reason about the presence of several agents. In this paper we address the problem of counting the number of agents in a topologically known environment using simple sensors that can indicate anonymous human presence. To do so, we connect an ontology to a probabilistic model (a Hidden Markov Model) in order to estimate the number of agents in each section of the environment. We evaluate our methods on a smart home setup where a number of motion and pressure sensors are distributed in various rooms of the home.

Place, publisher, year, edition, pages
Palo Alto: AAAI Press, 2017. Vol. ws17, p. 758-764, article id WS-17-12
Series
The Workshops of the Thirty-First AAAI Conference on Artificial Intelligence: Technical Reports WS-17-01 - WS-17-15
National Category
Computer Sciences
Identifiers
URN: urn:nbn:se:oru:diva-62763ISBN: 9781577357865 (print)ISBN: 1577357868 (print)OAI: oai:DiVA.org:oru-62763DiVA, id: diva2:1159233
Conference
Workshop on Knowledge-Based Techniques for Problem Solving and Reasoning (KnowProS’17)
Available from: 2017-11-22 Created: 2017-11-22 Last updated: 2018-01-26Bibliographically approved

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Renoux, JenniferAlirezaie, MarjanKarlsson, LarsKöckemann, UwePecora, FedericoLoutfi, Amy
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