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Occupancy sensor

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An indoor light switch equipped with PIR-based occupancy sensor[1]

An occupancy sensor is an indoor device used to detect the presence of a person. Applications include automatic adjustment of lights or temperature or ventilation systems in response to the quantity of people present. The sensors typically use infrared, ultrasonic, microwave, or other technology. The term encompasses devices as different as PIR sensors, hotel room keycard locks and smart meters. Occupancy sensors are typically used to save energy, provide automatic control, and comply with building codes.[2]

Vacancy sensor

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A vacancy sensor works like an occupancy sensor, however, lights must be manually turned ON, but will automatically turn OFF when motion is no longer detected.[3]

Sensor types

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Occupancy sensor types include:

  1. PIR sensors, which work on heat difference detection, measuring infrared radiation. Inside the device is a pyroelectric sensor which can detect the sudden presence of objects (such as humans) who radiate a temperature different from the temperature of the background, such as the room temperature of a wall.
  2. Environmental sensors, such as temperature, humidity and CO2 sensors,[4][5][6] which detect the change in the environment due to the presence of a human.[7]
  3. Ultrasonic sensors, similar to radar. they work on the doppler shift principle. An ultrasonic sensor will send high frequency sound waves in area and will check for their reflected patterns. If the reflected pattern is changing continuously then it assumes that there is occupancy and the lighting load connected is turned on. If the reflected pattern is the same for a preset time then the sensor assumes there is no occupancy and the load is switched off.
  4. Microwave sensors. Similar to the ultrasonic sensor, a microwave sensor also works on the doppler shift principle. A microwave sensor will send high frequency microwaves in an area and will check for their reflected patterns. If the reflected pattern is changing continuously then it assumes that there is occupancy and the lighting load connected is turned on. If the reflected pattern is the same for a preset time then the sensor assumes there is no occupancy and the load is switched off. A microwave sensor has high sensitivity as well as detection range compared to other types of sensors.
  5. Keycard light slots, used in a hotel energy management system to detect when a hotel room is occupied, by requiring the guest to place their keycard in a slot to activate lights and thermostats.[8]
  6. Smart meters, which work by detecting the change in power consumption patterns that exhibit distinct characteristics for occupied and vacant states.[9]
  7. Barometric Pressure sensors[10] can be used to monitor door openings, which are associated with foot traffic, in rooms containing positive pressure, including operating rooms.
  8. Door operated switch.
  9. Audio detection.
  10. Image processing. Overhead CCTV camera tracks people’s movements. Camera feed connects to occupancy detection software which counts the number of people in the designated area.[11]

Occupancy sensors for lighting control

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Motion sensors are often used in indoor spaces to control electric lighting. If no motion is detected, it is assumed that the space is empty, and thus does not need to be lit. Turning off the lights in such circumstances can save substantial amounts of energy. In lighting practice occupancy sensors are sometime also called "presence sensors" or "vacancy sensors". Some occupancy sensors (e.g. LSG's Pixelview, Philips Lumimotion, Ecoamicatechs Sirius etc.) also classify the number of occupants, their direction of motion, etc., through image processing. Pixelview is a camera-based occupancy sensor, using a camera that is built into each light fixture.

System design and components

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Occupancy sensors for lighting control typically use infrared (IR), ultrasonic, tomographic motion detection, microwave sensors, or camera-based sensors (image processing).[12] The field of view of the sensor must be carefully selected/adjusted so that it responds only to motion in the space served by the controlled lighting. For example, an occupancy sensor controlling lights in an office should not detect motion in the corridor outside the office. Tomographic motion detection systems have the unique benefit of detecting motion through walls and obstructions, yet do not trigger as easily from motion on the outside of the detection area like traditional microwave sensors.

Sensors and their placement are never perfect, therefore most systems incorporate a delay time before switching. This delay time is often user-selectable, but a typical default value is 15 minutes. This means that the sensor must detect no motion for the entire delay time before the lights are switched. Most systems switch lights off at the end of the delay time, but more sophisticated systems with dimming technology reduce lighting slowly to a minimum level (or zero) over several minutes, to minimize the potential disruption in adjacent spaces. If lights are off and an occupant re-enters a space, most current systems switch lights back on when motion is detected. However, systems designed to switch lights off automatically with no occupancy, and that require the occupant to switch lights on when they re-enter are gaining in popularity due to their potential for increased energy savings. These savings accrue because in a spaces with access to daylight the occupant may decide on their return that they no longer require supplemental electric light.[13]

Originally invented by Kevin D. Fraser of San Francisco. The prototype utilized existing ultrasonic intrusion alarm technology coupled to conventional industrial timers, with basic switching elements. First prototype was crafted on a plywood base; the first model required a separate transmitter and receiver processing 20,200 cycles per second of sound energy. Mr. Fraser was employed by and developed the device for the Embarcadero Center high-rise office complex in San Francisco, and as such employee did not profit from the invention. He took the concept to Unisec security devices and had them build a single piece transceiver based on 277VAC - the level of electricity used for commercial lighting in the Embarcadero Center complex. Four hundred of these units were installed under a newly named UNENCO brand, and installed in the bathrooms of the four high-rise towers. This was an immediate success. This application received Congressional Mention for Kevin Fraser's efforts, as well as various Pacific Gas & Electric awards. Noted local columnist Herb Cain made mention that one should not sit too long in the stalls at Embarcadero Center, and the word caught on regarding the technology. While not receiving a patent, Mr. Fraser was acknowledged by the Association of Energy Engineers (AEE) as the inventor.

See also

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References

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  1. ^ Product Specification for PR150-1L/PR180-1L (PDF). Leviton. Retrieved 6 October 2018.
  2. ^ "Guest Room Occupancy Controls—2013 California Building Energy Efficiency Standards" (PDF). California Energy Commission. 2011. Archived from the original (PDF) on 2016-06-09. Retrieved May 10, 2016.
  3. ^ "Occupancy and Vacancy Sensors". Leviton Manufacturing Company. Retrieved October 2, 2018.
  4. ^ Carroll, G.T.; Kirschman, D.L.; Mammana, A. (2022). "Increased CO2 levels in the operating room correlate with the number of healthcare workers present: an imperative for intentional crowd control". Patient Safety in Surgery. 16 (1): 35. doi:10.1186/s13037-022-00343-8. PMC 9672642. PMID 36397098.
  5. ^ Arief-Ang, I.B.; Hamilton, M.; Salim, F. (2018-06-01). "RUP: Large Room Utilisation Prediction with carbon dioxide sensor". Pervasive and Mobile Computing. 46: 49–72. doi:10.1016/j.pmcj.2018.03.001. ISSN 1873-1589. S2CID 13670861.
  6. ^ Arief-Ang, I.B.; Salim, F.D.; Hamilton, M. (2018-04-14). "SD-HOC: Seasonal Decomposition Algorithm for Mining Lagged Time Series". Data Mining [SD-HOC: Seasonal Decomposition Algorithm for Mining Lagged Time Series]. Communications in Computer and Information Science. Vol. 845. Springer, Singapore. pp. 125–143. doi:10.1007/978-981-13-0292-3_8. ISBN 978-981-13-0291-6.
  7. ^ Ang, I.B.A.; Salim, F.D.; Hamilton, M. (2016-03-14). Human occupancy recognition with multivariate ambient sensors. 2016 IEEE International Conference on Pervasive Computing and Communication Workshops. Sydney, Australia. pp. 1–10. doi:10.1109/PERCOMW.2016.7457116.
  8. ^ Catharine Hamm (February 16, 2015). "Do hotel thermostats with motion sensors have you waking up in a sweat?". Los Angeles Times. Retrieved May 10, 2016.
  9. ^ Jin, M.; Jia, R.; Spanos, C. (2017-01-01). "Virtual Occupancy Sensing: Using Smart Meters to Indicate Your Presence". IEEE Transactions on Mobile Computing. PP (99): 3264–3277. arXiv:1407.4395. doi:10.1109/TMC.2017.2684806. ISSN 1536-1233. S2CID 1997078.
  10. ^ Carroll, G.T.; Kirschman, D.L. (2022). "Discrete room pressure drops predict door openings and contamination levels in the operating room setting". Perioperative Care and Operating Room Management. 29: 100291. doi:10.1016/j.pcorm.2022.100291.
  11. ^ "Occupancy Sensing – 9 methods compared". Retail Sensing. 28 May 2024. Retrieved June 14, 2024.
  12. ^ "Technology comparison of Occupancy sensors". Retrieved 19 July 2014.
  13. ^ Did It Move? Detecting Motion with PIR + Arduino
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