Integrated comfort sensing system on indoor climate

Kang, Jeongho; Park, Sekwang

doi:10.1016/s0924-4247(00)00289-2

Cited by 21 publications

(8 citation statements)

References 5 publications

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“…By using MEMS, an integrated comfort sensor for measuring temperature, humidity, air pressure, and air velocity was developed. In 2000, Kang et al exhibited a module that integrated thermal resistors, a hygroscopic layer, piezo-resistors, and flow sensors together [20]. The module fully illustrated an IC-type thermal comfort sensor.…”

Section: Development Of Sensor Technologymentioning

confidence: 99%

Enabling Smart Air Conditioning by Sensor Development: A Review

Cheng

Lee

2016

Sensors

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The study investigates the development of sensors, in particular the use of thermo-fluidic sensors and occupancy detectors, to achieve smart operation of air conditioning systems. Smart operation refers to the operation of air conditioners by the reinforcement of interaction to achieve both thermal comfort and energy efficiency. Sensors related to thermal comfort include those of temperature, humidity, and pressure and wind velocity anemometers. Improvements in their performance in the past years have been studied by a literature survey. Traditional occupancy detection using passive infra-red (PIR) sensors and novel methodologies using smartphones and wearable sensors are both discussed. Referring to the case studies summarized in this study, air conditioning energy savings are evaluated quantitatively. Results show that energy savings of air conditioners before 2000 was 11%, and 30% after 2000 by the integration of thermo-fluidic sensors and occupancy detectors. By utilizing wearable sensing to detect the human motions, metabolic rates and related information, the energy savings can reach up to 46.3% and keep the minimum change of predicted mean vote (∆PMV→0), which means there is no compromise in thermal comfort. This enables smart air conditioning to compensate for the large variations from person to person in terms of physiological and psychological satisfaction, and find an optimal temperature for everyone in a given space. However, this tendency should be evidenced by more experimental results in the future.

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Section: Development Of Sensor Technologymentioning

confidence: 99%

Enabling Smart Air Conditioning by Sensor Development: A Review

Cheng

Lee

2016

Sensors

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“…According to the feedback from the distributed sensor nodes and the estimated data, PMV values could be calculated by [18]:

PMV = (0.303 e^{- 0.36 M} + 0.028) {\begin{array}{l} left & (M - W) \\ left & - 3.05 \times 10^{- 3} [5733 - 6.99 (M - W) - P_{a}] \\ left & - 0.42 [(M - W) - 58.15] \\ left & - 1.7 \times 10^{- 5} M (5867 - P_{a}) \\ left & - 0.0014 M (34 - t_{a}) \\ left & - 3.96 \times 10^{- 8} f_{cl} [{(t_{cl} + 273)}^{4} - {(t_{r} + 273)}^{4}] \\ left & - f_{cl} h_{c} (t_{cl} - t_{a}) \end{array}}

Where:

\begin{array}{l} left & {normalt}_{cl} = 35.7 - 0.028 (M - W) - {normalI}_{cl} {3.96 \times 10^{- 8} {normalf}_{cl} [{({normalt}_{cl} + 273)}^{4} - {(t_{r} + 273 false)}^{4})] + {normalf}_{cl} {normalh}_{normalc} ({normalt}_{cl} - {normalt}_{normala})} ... \end{array}

…”

Section: Light Powered Sensor Network Architecturementioning

confidence: 99%

Development of Light Powered Sensor Networks for Thermal Comfort Measurement

Lee

2008

Sensors

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Recent technological advances in wireless communications have enabled easy installation of sensor networks with air conditioning equipment control applications. However, the sensor node power supply, through either power lines or battery power, still presents obstacles to the distribution of the sensing systems. In this study, a novel sensor network, powered by the artificial light, was constructed to achieve wireless power transfer and wireless data communications for thermal comfort measurements. The sensing node integrates an IC-based temperature sensor, a radiation thermometer, a relative humidity sensor, a micro machined flow sensor and a microprocessor for predicting mean vote (PMV) calculation. The 935 MHz band RF module was employed for the wireless data communication with a specific protocol based on a special energy beacon enabled mode capable of achieving zero power consumption during the inactive periods of the nodes. A 5W spotlight, with a dual axis tilt platform, can power the distributed nodes over a distance of up to 5 meters. A special algorithm, the maximum entropy method, was developed to estimate the sensing quantity of climate parameters if the communication module did not receive any response from the distributed nodes within a certain time limit. The light-powered sensor networks were able to gather indoor comfort-sensing index levels in good agreement with the comfort-sensing vote (CSV) preferred by a human being and the experimental results within the environment suggested that the sensing system could be used in air conditioning systems to implement a comfort-optimal control strategy.

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“…In this article, we have concentrated on thermal comfort estimation with air quality considerations because thermal comfort and air quality are very significant factors in deciding the human comfort level and building sustainability [7], [8]. According to the American Society of Heating, Refrigerating, and Air-Conditioning Engineers (ASHRAE) and International Organization for Standardization (ISO) 7730, thermal comfort is a "state of mind that expresses satisfaction with the thermal environment".…”

mentioning

confidence: 99%

“…They used three measured environmental parameters, that is, temperature, humidity, and air flow. Other parameters such as clothing level, activity level, and mean radiant temperature were considered according to ISO7730 standards [8]. Honeywell et al developed a TY4700 thermal comfort sensor.…”

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confidence: 99%

An Energy-Efficient Smart Comfort Sensing System Based on the IEEE 1451 Standard for Green Buildings

Kumar

Hancke

2014

IEEE Sensors J.

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Abstract-In building automation, comfort is an important aspect, and the real-time measurement of comfort is notoriously complicated. In this article, we have developed a wireless, smart comfort sensing system. The important parameters in designing the prevalent measurement of comfort systems such as portability, power consumption, reliability, and system cost were considered. To achieve the target design goals, the communication module, sensor node, and sink node were developed based on the IEEE1451 standard. Electrochemical and semiconductor sensors were considered for the development of the sensor array, and the results of both technologies were compared. The sensor and sink nodes were implemented using the ATMega88 microcontroller. Microsoft Visual Studio 2013 preview was used to create the graphical user interface (GUI) in C#. The sensors were calibrated after the signal processing circuit to ensure that the standard accuracy of the sensor was achieved. This article presents detailed design solutions to problems that existed in the literature.Index Terms-IEEE1451 standard, sensor node, thermal comfort, graphical user interface, smart sensor, green building.

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Integrated comfort sensing system on indoor climate

Cited by 21 publications

References 5 publications

Enabling Smart Air Conditioning by Sensor Development: A Review

Enabling Smart Air Conditioning by Sensor Development: A Review

Development of Light Powered Sensor Networks for Thermal Comfort Measurement

An Energy-Efficient Smart Comfort Sensing System Based on the IEEE 1451 Standard for Green Buildings

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