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Synthetic generation of passive infrared motion sensor data using a game engine
Malmö universitet, Internet of Things and People (IOTAP). Malmö universitet, Fakulteten för teknik och samhälle (TS), Institutionen för datavetenskap och medieteknik (DVMT).ORCID-id: 0000-0002-6079-6026
Sony Network Communications, 223 62 Lund, Sweden.
Sony Network Communications, 223 62 Lund, Sweden.
Malmö universitet, Fakulteten för teknik och samhälle (TS), Institutionen för datavetenskap och medieteknik (DVMT). Malmö universitet, Internet of Things and People (IOTAP).ORCID-id: 0000-0002-4261-281X
2021 (Engelska)Ingår i: Sensors, E-ISSN 1424-8220, Vol. 21, nr 23, artikel-id 8078Artikel i tidskrift (Refereegranskat) Published
Abstract [en]

Quantifying the number of occupants in an indoor space is useful for a wide variety of applications. Attempts have been made at solving the task using passive infrared (PIR) motion sensor data together with supervised learning methods. Collecting a large labeled dataset containing both PIR motion sensor data and ground truth people count is however time-consuming, often requiring one hour of observation for each hour of data gathered. In this paper, a method is proposed for generating such data synthetically. A simulator is developed in the Unity game engine capable of producing synthetic PIR motion sensor data by detecting simulated occupants. The accuracy of the simulator is tested by replicating a real-world meeting room inside the simulator and conducting an experiment where a set of choreographed movements are performed in the simulated environment as well as the real room. In 34 out of 50 tested situations, the output from the simulated PIR sensors is comparable to the output from the real-world PIR sensors. The developed simulator is also used to study how a PIR sensor’s output changes depending on where in a room a motion is carried out. Through this, the relationship between sensor output and spatial position of a motion is discovered to be highly non-linear, which highlights some of the difficulties associated with mapping PIR data to occupancy count. 

Ort, förlag, år, upplaga, sidor
MDPI, 2021. Vol. 21, nr 23, artikel-id 8078
Nyckelord [en]
Motion sensor, Occupancy count, Passive infrared, People count, PIR, Simulation, Synthetic data generation, Large dataset, Learning systems, Infrared motion sensors, Motion sensors, Passive infrared sensors, Sensors data, Synthetic data generations, Simulators
Nationell ämneskategori
Signalbehandling
Identifikatorer
URN: urn:nbn:se:mau:diva-48361DOI: 10.3390/s21238078ISI: 000778245100007PubMedID: 34884081Scopus ID: 2-s2.0-85120341488OAI: oai:DiVA.org:mau-48361DiVA, id: diva2:1623527
Tillgänglig från: 2021-12-29 Skapad: 2021-12-29 Senast uppdaterad: 2024-02-05Bibliografiskt granskad

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Stefansson, PetterOlsson, Carl Magnus

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