Abstract Cognitive buildings use data on how occupants respond to the built environment to proactively make occupant-centric adjustments to lighting, temperature, ventilation, and other environmental parameters. However, sensors that unobtrusively and ubiquitously measure occupant responses are lacking. Here we show that Doppler-radar based sensors, which can sense small physiological motions, provide accurate occupancy detection and estimation of vital signs in challenging, realistic circumstances. Occupancy was differentiated from an empty room over 93% of the time in a 3.4 m × 8.5 m conference room with a single sensor in both wall and ceiling-mounted configurations. Occupancy was successfully detected while an occupant was under the table, visibly blocked from the sensor, a scenario where infrared, ultrasound, and video-based occupancy sensors would fail. Heart and respiratory rates were detected in all seats in the conference room with a single ceiling-mounted sensor. The occupancy sensor can be used to control HVAC and lighting with a short, 1–2 min delay and to provide information for space utilization optimization. Heart and respiratory rate sensing could provide additional feedback to future human-building interactive systems that use vital signs to determine how occupant comfort and wellness is changing with time.
more »
« less
Doppler Radar Occupancy Sensing and Monitoring for Smart Buildings
Smart buildings promise to adapt environmental conditions to the needs of occupants based on statistical analytics applied to various monitored data. While sensors for accurate monitoring of building parameters such as temperature, lighting, and air-quality abound, currently available occupancy sensors are limited to sensing of presence only, with limited accuracy. Doppler radar sensors have shown great promise for unobtrusive recognition and monitoring of occupant presence, count, activity, and cardiopulmonary vital signs. With such measures, a smart building can optimize operations not only for the most efficient use of energy and space, but also to create healthy and sustainable environments that support occupant wellness, comfort, and productivity. This paper presents an overview of Doppler radar occupancy sensors for smart building applications.
more »
« less
- Award ID(s):
- 2039089
- PAR ID:
- 10547783
- Publisher / Repository:
- IEEE
- Date Published:
- ISBN:
- 979-8-3503-4702-9
- Page Range / eLocation ID:
- 105 to 108
- Subject(s) / Keyword(s):
- Doppler radar occupancy sensing smart buildings
- Format(s):
- Medium: X
- Location:
- Nis, Serbia
- Sponsoring Org:
- National Science Foundation
More Like this
-
-
Occupancy sensors are electronic devices used to detect the presence of people in monitored areas, and the output of these sensors can be used to optimize lighting control, heating and ventilation control, and real-estate utilization. Testing methods already exist for certain types of occupancy sensors (e.g., passive infrared) to evaluate their relative performance, allowing manufacturers to report coverage patterns for different types of motion. However, the existing published techniques are mostly tailored for passive-infrared sensors and therefore limited to evaluation of large motions, such as walking and hand movement. Here we define a characterization technique for a Doppler radar occupancy sensor based on detecting a small motion representing human breathing, using a well-defined readily reproducible target. The presented technique specifically provides a robust testing method for a single-channel continuous wave Doppler-radar based occupancy sensor, which has variation in sensitivity within each wavelength of range. By comparison with test data taken from a human subject, we demonstrate that the mobile target provides a reproducible alternative for a human target that better accounts for the impact of sensor placement. This characterization technique enables generation of coverage patterns for breathing motion for single-channel continuous wave Doppler radar-based occupancy sensors.more » « less
-
This study examines the use of a Doppler radar occupancy sensor to assess thermal adaptation. Current heating, ventilation, and air-conditioning (HVAC) systems are important for the productivity of employees and the healing of patients; however, their control systems are typically limited to a narrow temperature range, which is usually not comfortable for most occupants. Occupant vital signs can be used to assess thermal comfort, due to the role cardiovascular regulation plays in heat dissipation. This research aims to correlate physiological and thermal adaptation with the goal of optimizing HVAC system operation. A Doppler radar occupancy sensor was used to measure the physiological parameters of ten human subjects under two temperature conditions, and thermal comfort surveys were used to record thermal sensation. The results demonstrate that the Doppler radar occupancy sensor could not only detect heart rate changes due to a significant environmental temperature difference but also detect subtle changes in heart rate during thermal adaptation that were not captured by the surveys.more » « less
-
Activity recognition has applications in a variety of human-in-the-loop settings such as smart home health monitoring, green building energy and occupancy management, intelligent transportation, and participatory sensing. While fine-grained activity recognition systems and approaches help enable a multitude of novel applications, discovering them with non-intrusive ambient sensor systems pose challenging design, as well as data processing, mining, and activity recognition issues. In this paper, we develop a low-cost heterogeneous Radar based Activity Monitoring (RAM) system for recognizing fine-grained activities. We exploit the feasibility of using an array of heterogeneous micro-doppler radars to recognize low-level activities. We prototype a short-range and a long-range radar system and evaluate the feasibility of using the system for fine-grained activity recognition. In our evaluation, using real data traces, we show that our system can detect fine-grained user activities with 92.84% accuracy.more » « less
-
Abstract This paper introduces a database of 34 field-measured building occupant behavior datasets collected from 15 countries and 39 institutions across 10 climatic zones covering various building types in both commercial and residential sectors. This is a comprehensive global database about building occupant behavior. The database includes occupancy patterns (i.e., presence and people count) and occupant behaviors (i.e., interactions with devices, equipment, and technical systems in buildings). Brick schema models were developed to represent sensor and room metadata information. The database is publicly available, and a website was created for the public to access, query, and download specific datasets or the whole database interactively. The database can help to advance the knowledge and understanding of realistic occupancy patterns and human-building interactions with building systems (e.g., light switching, set-point changes on thermostats, fans on/off, etc.) and envelopes (e.g., window opening/closing). With these more realistic inputs of occupants’ schedules and their interactions with buildings and systems, building designers, energy modelers, and consultants can improve the accuracy of building energy simulation and building load forecasting.more » « less