A low-cost and portable device for measuring spectrum of light source as a stimulus for the human’s circadian system

Amirazar, Armin; Azarbayjani, Mona; Molavi, Maziyar; Karami, Morteza

doi:10.1016/j.enbuild.2021.111386

Cited by 8 publications

(8 citation statements)

References 60 publications

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“…Regarding the number of light sensor channels, [26] utilised a light sensor with 256 channels. In contrast [25], [27], [28], and this work used 14, 6, and 10 channels respectively.…”

Section: Discussionmentioning

confidence: 99%

“…It had dimensions of 77×46×28 mm, weighed 50 g, and with sampling every 30 s had a battery life of 23 hours for a real-world accuracy estimated as 17%. [26] developed a wearable light sensor designed to be worn as a pendant to measure Spectral Power Density (SPD) data in the visible wavelength range 380-780 nm using 256 channels. [27] developed a wearable light dosimeter using a light sensor with 6 channels covering a wavelength range of 400-1000 nm, which can be attached to spectacle frames.…”

Section: Introductionmentioning

confidence: 99%

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A Wrist-Worn Internet of Things Sensor Node for Wearable Equivalent Daylight Illuminance Monitoring

Mohammadian,

Didikoglu,

Beach

et al. 2024

IEEE Internet Things J.

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Light exposure is a vital regulator of physiology and behaviour in humans. However, monitoring of light exposure is not included in current wearable Internet-of-Things (IoT) devices, and only recently have international standards defined α-opic equivalent daylight illuminance measures for how the eye responds to light. This paper reports a wearable light sensor node that can be incorporated into the IoT to provide monitoring of equivalent daylight illuminance exposure in real-world settings. We present the system design, electronic performance testing, and accuracy of equivalent daylight illuminance measurements when compared to a calibrated spectral source. This includes consideration of the directional response of the sensor, and a comparison of performance when placed on different parts of the body, and a demonstration of practical use over 7 days. Our device operates for 3.5 days between charges, with a sampling period of 30 s. It has 10 channels of measurement, over the range 415-910 nm, balancing accuracy and cost considerations. Measured α-opic Equivalent Daylight Illuminance results for 13 devices show a mean absolute error of less than 0.07 log lx, and a minimum between device correlation of 0.99. These findings demonstrate that accurate light sensing is feasible, including at wrist worn locations. We provide an experimental platform for use in future investigations in real-world light exposure monitoring and IoT based lighting control.

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“…Regarding the number of light sensor channels, [26] utilised a light sensor with 256 channels. In contrast [25], [27], [28], and this work used 14, 6, and 10 channels respectively.…”

Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

A Wrist-Worn Internet of Things Sensor Node for Wearable Equivalent Daylight Illuminance Monitoring

Mohammadian,

Didikoglu,

Beach

et al. 2024

IEEE Internet Things J.

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“…In summary, NRMSE errors lower than 2 % are reported. Amirazar et al [36] also made use of an MLP model to reconstruct the SPDs of different light sources from 14 sensor responses to an SPD of 3.5 nm resolution in the wavelength range between 410 nm and 760 nm. NRMSE errors lower than 1 % are reported on simulated sensor data, but errors in a real world validation are considerably higher ranging from 11 up to 40 %.…”

Section: Spd Estimation From Spectral Sensor Responsesmentioning

confidence: 99%

“…NRMSE errors lower than 1 % are reported on simulated sensor data, but errors in a real world validation are considerably higher ranging from 11 up to 40 %. The authors attribute these discrepancies to insufficient training data for the real world application [36].…”

Section: Spd Estimation From Spectral Sensor Responsesmentioning

confidence: 99%

“…Botero et al [35] for example developed an alternative to a spectrometer for low-cost spectral light measurements using a multilayer perceptron (artificial neural network) for the relative SPD reconstruction from spectral sensor responses. Amirazar et al [36] applied this principle to build a device for monitoring a person's individual lighting exposure from an 18-channel spectral sensor, again relying on an artificial neural network for the SPD reconstruction. Instead of an SPD reconstruction, Botero et al [37] also investigated the feasability of directly estimating certain color rendition features, such as TM 30-18 R f and R g values or the CIE R a color rendering index, from spectral sensor responses.…”

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confidence: 99%

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LED Degradation Monitoring Using a Multi-Channel Spectral Sensor

Myland,

Herzog,

Babilon

et al. 2024

IEEE Access

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This study explores a novel approach to monitor the spectral emission of LEDs by estimating the spectral power distribution from the spectral sensor responses during an accelerated ageing experiment. Two methods for reconstructing the actual LED spectra from sensor responses are presented and tested, one solely requires sensor datasheet information and the other uses a full spectral characterisation of the sensor's spectral sensitivities. The reconstruction results show that a spectral sensor can provide accurate spectral estimates even after severe LED degradation. Only for an LED that suffered a phosphor crack, affecting its spatial radiation characteristics, limited ability to estimate the true spectral power distribution without prior assumptions about the spectral changes must be reported. Overall, the use of a spectral sensor, even without detailed characterisation of the sensor itself, allows for an accurate monitoring of the true emission of LEDs, with a maximum radiometric error of 0.73 %, a maximum colormetric error of 0.0017 ∆u ′ v ′ and a maximum spectral nRMSE error of 0.0097 compared to a spectroradiometric measurement. This advance holds great promise for improving lighting technology, particularly in applications that require constant radiometric output and stable color.

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Low-cost chronobiological monitoring: A tested IoT-enabled diagnostic tool in tropical and Antarctic environments

Marins,

Costa,

Rocha

et al. 2025

Internet of Things

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A low-cost and portable device for measuring spectrum of light source as a stimulus for the human’s circadian system

Cited by 8 publications

References 60 publications

A Wrist-Worn Internet of Things Sensor Node for Wearable Equivalent Daylight Illuminance Monitoring

A Wrist-Worn Internet of Things Sensor Node for Wearable Equivalent Daylight Illuminance Monitoring

LED Degradation Monitoring Using a Multi-Channel Spectral Sensor

Low-cost chronobiological monitoring: A tested IoT-enabled diagnostic tool in tropical and Antarctic environments

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