An IoT system for smart building combining multiple mmWave FMCW radars applied to people counting
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Abstract (arXiv)
In contemporary society, the pressing challenge of preserving user privacy clashes with the imperative for smart buildings to efficiently manage their resources, particularly in the context of occupancy monitoring for optimized energy utilization. This paper delves into the application of millimiter wave (mmWave) frequency modulated continuous wave (FMCW) radar technology for occupancy monitoring. mmWave FMCW radar, unlike conventional methods that often require the use of identifiable tags or involve image analysis, operates without the need for such identifiers, mitigating privacy concerns. However, challenges arise when attempting to cover extensive indoor spaces due to the limited range of individual mmWave FMCW radar devices. The present work proposes the use of a flexible software architecture to integrate the measurements of several mmWave FMCW radar devices, so that the whole behaves as a single sensor. To validate the proposal, an example of use in a real environment in an indoor space monitored with three mmWave FMCW radar devices is also presented. The example details the whole process, from the physical installation of the devices to the use of the different software modules that allow the integration of the data into a common internet of things (IoT) management platform such as Home Assistant. All the elements, from the measurements captured during the test to the different software implementations, are shared publicly with the scientific community.
Key facts. Cited by 2 papers in the map (data through 14 Oct 2026). First posted on arXiv 28 Jan 2024.
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Citing papers per year: 2025: 1; 2026: 1.
2 papers.
- 2025Comprehensive Evaluation of Rule-Based, Machine Learning, and Deep Learning in Human Estimation Using Radio Wave Sensing: Accuracy, Spatial Generalization, and Output Granularity Trade-offscited by 0
- 2026MultiGait: A Multi-Sensor Multi-Perspective Multi-Session Biometric Inference Benchmark and its Datasetcited by 0
- 2026MultiGait: A Multi-Sensor Multi-Perspective Multi-Session Biometric Inference Benchmark and its Dataset1 Sep 2026
- 2025Comprehensive Evaluation of Rule-Based, Machine Learning, and Deep Learning in Human Estimation Using Radio Wave Sensing: Accuracy, Spatial Generalization, and Output Granularity Trade-offs15 Dec 2025