Abstract
Light is one of the most important elements for residential and work spaces, which affects visual performance, comfort, productivity and well-being. The measures that quantify the characteristics of a light source are derived directly from the spectral power distribution (SPD). In addition the SPD is an important factor influencing the quality of a light source. However, measuring light source spectrum with traditional spectrometers is expensive, difficult to adapt to normal spaces, and hard to integrate with other systems. To address these challenges, a low-cost spectrometer was developed using an Artificial Neural Network, with a resolution of 5 nm in the visible spectrum. The reconstructed SPD has an error lower than 2% and allows the derivation of measurements to characterize the colour quality of light sources. Additionally, the device has wireless communication (Bluetooth and Wi-Fi) in real time, which allows integration into lighting control applications and other Internet of things (IoT) applications.
Original language | English (US) |
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Pages (from-to) | 579-587 |
Number of pages | 9 |
Journal | Energy and Buildings |
Volume | 199 |
DOIs | |
State | Published - Sep 15 2019 |
All Science Journal Classification (ASJC) codes
- Civil and Structural Engineering
- Building and Construction
- Mechanical Engineering
- Electrical and Electronic Engineering