How Low Can You Go?

Author:

Rinta-Homi Mikko1,Motlagh Naser Hossein1,Zuniga Agustin1,Flores Huber2,Nurmi Petteri1

Affiliation:

1. University of Helsinki, Helsinki, Finland

2. University of Tartu, Tartu, Estonia

Abstract

We contribute by systematically analysing the performance trade-offs, costs (privacy loss and deployment cost) and limits of low-resolution thermal array sensors for occupancy detection. First, to assess performance limits, we manipulate the frame rate and resolution of images to establish the lowest possible values where reliable occupancy information can be captured. We also assess the effect of different viewing angles on the performance. We analyse performance using two datasets, an open-source dataset of thermal array sensor measurements (TIDOS) and a proprietary dataset that is used to validate the generality of the findings and to study the effect of different viewing angles. Our results show that even cameras with a 4 × 2 resolution - significantly lower than what has been used in previous research - can support reliable detection, as long as the frame rate is at least 4 frames per second. The lowest tested resolution, 2 × 2, can also offer reliable detection rates but requires higher frame rates (at least 16 frames per second) and careful adjustment of the camera viewing angle. We also show that the performance is sensitive to the viewing angle of the sensor, suggesting that the camera's field-of-view needs to be carefully adjusted to maximize the performance of low-resolution cameras. Second, in terms of costs, using a camera with only 4 × 2 resolution reveals very few insights about the occupants' identity or behaviour, and thus helps to preserve their privacy. Besides privacy, lowering the resolution and frame rate decreases manufacturing and operating costs and helps to make the solution easier to adopt. Based on our results, we derive guidelines on how to choose sensor resolution in real-world deployments by carrying out a small-scale trade-off analysis that considers two representative buildings as potential deployment areas and compares the cost, privacy and accuracy trade-offs of different resolutions.

Funder

European Regional Funds

Publisher

Association for Computing Machinery (ACM)

Subject

Computer Networks and Communications,Hardware and Architecture,Human-Computer Interaction

Cited by 9 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Mapping Thermal Footprints: Occupancy Estimation and Localization in Diverse Indoor Settings with Thermal Arrays;Proceedings of the 7th ACM SIGCAS/SIGCHI Conference on Computing and Sustainable Societies;2024-07-08

2. LIZARD: Pervasive Sensing for Autonomous Plastic Litter Monitoring;2024 IEEE/ACM Ninth International Conference on Internet-of-Things Design and Implementation (IoTDI);2024-05-13

3. Digital Twins for Smart Spaces—Beyond IoT Analytics;IEEE Internet of Things Journal;2024-01-01

4. Overcoming Data Scarcity through Transfer Learning in CO2-Based Building Occupancy Detection;Proceedings of the 10th ACM International Conference on Systems for Energy-Efficient Buildings, Cities, and Transportation;2023-11-15

5. Occupancy counting in dense and sparse settings with a low-cost thermal camera;2023 15th International Conference on COMmunication Systems & NETworkS (COMSNETS);2023-01-03

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