An Indoor Smart Lamp For Environments Illuminated Day Time
Abstract
Lighting energy consumption constitutes % 9-25 of final consumption in buildings. In addition, lights are kept open during daytime in some buildings such as public institutions and schools. The main purpose of this study is to design a remotely controlled smart lamp that measures the illumination of the environment and adjusts illumination level of lamp according to demand in order to decrease the electricity consumption due to lighting during daytime. Also, in this study energy savings that can be achieved with the usage of this lamp in a school building in analyzed. Many studies are conducted to develop smart lamps, however to the authors best knowledge a remotely controlled autonomous smart lamp by Wi-Fi module and a software developed in C# interface, to update required minimum illumination level of the room is not found in literature. By using the developed software minimum illumination levels of the rooms of a whole building can be managed remotely which is useful in cases such as changing the purpose or color of the rooms or changing minimum level seasonally. System consists of Arduino, BH1750 light sensor, strap LEDs, transistors and Wi-Fi module. Daylight illumination level is measured with BH1750. Smart lamp changes its illumination level by taking the difference of measured illumination data from minimum illumination level data, if the measured illumination level is lower than minimum level. In order to analyze the energy saving that could be achieved, illumination level of the indoor and outdoor environment of Faculty of Technology of Selcuk University is measured at 30 minutes' intervals for one day. Energy saving to be obtained in case of using developed smart lamp is calculated as 1747 kWh/year only for daytimes.
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Energy consumption in commercial buildings in the US is up to 25%, and in Turkey up to 9%.
“Cihan and Güğül [73] adds that energy consumption in commercial buildings in the US is up to 25%, and in Turkey, it is up to 9%.”
From Machine Learning Methods in Smart Lighting Toward Achieving User Comfort: A Survey (2022) · cites this paper as Cihan and Güğül [73]
Cites
Intelligent system for lighting control in smart cities
De Paz, J. F., Bajo, J., Rodríguez, S., Villarrubia, G., & Corchado, J. M. (2016) · Information Sciences · doi:10.1016/j.ins.2016.08.045 · Cited by 146 · see citing works
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Machine Learning Methods in Smart Lighting Toward Achieving User Comfort: A Survey
Putrada, A. G., Abdurohman, M., Perdana, D., & Nuha, H. H. (2022) · IEEE Access · doi:10.1109/access.2022.3169765 · Cited by 101 · see citing works
“Cihan et al. [73] adds that energy consumption in commercial buildings in the US is up to 25%, and in Turkey, it is up to 9%.”
Background
- Authors
- Cihan, A. N., & Gugul, G. N.
- Affiliations
- Selçuk University (TR)
- Venue
- 2020 IEEE East-West Design & Test Symposium (EWDTS)
- Publisher
- IEEE
- Published
- 2020-09
- Volume
- 6
- Pages
- 1-5
- OpenAlex
- W3094539972
- Cited by
- 5
- References
- 1
- Citations by year
- 2023: 1 · 2022: 4
- FWCI
- 1.76
- Type
- conference paper
- Language
- en
- Open access
- closed
- Licence
- Locations
- IEEE East-West Design & Test Symposium (EWDTS) (publishedVersion)
- Topics
- Physical Sciences › Engineering › Electrical and Electronic Engineering › Arduino and IoT Applications
- Physical Sciences › Engineering › Electrical and Electronic Engineering › IoT-based Smart Home Systems
- Physical Sciences › Engineering › Building and Construction › Building Energy and Comfort Optimization
- Keywords
- smart lamp, daylighting, daylight measurement, BH1750 light sensor, Wi-Fi remote control, Arduino, LED lighting control, energy conservation, school buildings
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