Reducing energy demand in the residential and industrial sectors is an important challenge worldwide. In particular, lights account for a great portion of total energy consumption, and unfortunately a huge amount of this energy is wasted. Light-emitting diode (LED) lights are being used to light offices, houses, industrial, or agricultural facilities more efficiently than traditional lights. Moreover, the light control systems are introduced to current markets, because the installed lighting systems are outdated and energy inefficient. However, due to high costs, installation issues, and difficulty of maintenance; existing light control systems are not successfully applied to home, office, and industrial buildings. This paper proposes a low cost, wireless, easy to install, adaptable, and smart LED lighting system to automatically adjust the light intensity to save energy and maintaining user satisfaction. The system combines motion sensors and light sensors in a low-power wireless solution using Zigbee communication. This paper presents the design and implementation of the proposed system in a real-world deployment. Characterization of a commercial LED panel was performed to evaluate the benefit of dimming for this light technology. Measurements of total power consumption over a continuous six months period (winter to summer) of a busy office were acquired to verify the performance and the power savings across several weather conditions scenarios. The proposed smart lighting system reduces total power consumption in the application scenario by 55% during a six month period and up to 69% in spring months. These figures take also into account individual user preferences.

Magno, M., Polonelli, T., Benini, L., Popovici, E. (2015). A low cost, highly scalable wireless sensor network solution to achieve smart LED light control for green buildings. IEEE SENSORS JOURNAL, 15(5), 2963-2973 [10.1109/JSEN.2014.2383996].

A low cost, highly scalable wireless sensor network solution to achieve smart LED light control for green buildings

MAGNO, MICHELE;POLONELLI, TOMMASO;BENINI, LUCA;
2015

Abstract

Reducing energy demand in the residential and industrial sectors is an important challenge worldwide. In particular, lights account for a great portion of total energy consumption, and unfortunately a huge amount of this energy is wasted. Light-emitting diode (LED) lights are being used to light offices, houses, industrial, or agricultural facilities more efficiently than traditional lights. Moreover, the light control systems are introduced to current markets, because the installed lighting systems are outdated and energy inefficient. However, due to high costs, installation issues, and difficulty of maintenance; existing light control systems are not successfully applied to home, office, and industrial buildings. This paper proposes a low cost, wireless, easy to install, adaptable, and smart LED lighting system to automatically adjust the light intensity to save energy and maintaining user satisfaction. The system combines motion sensors and light sensors in a low-power wireless solution using Zigbee communication. This paper presents the design and implementation of the proposed system in a real-world deployment. Characterization of a commercial LED panel was performed to evaluate the benefit of dimming for this light technology. Measurements of total power consumption over a continuous six months period (winter to summer) of a busy office were acquired to verify the performance and the power savings across several weather conditions scenarios. The proposed smart lighting system reduces total power consumption in the application scenario by 55% during a six month period and up to 69% in spring months. These figures take also into account individual user preferences.
2015
Magno, M., Polonelli, T., Benini, L., Popovici, E. (2015). A low cost, highly scalable wireless sensor network solution to achieve smart LED light control for green buildings. IEEE SENSORS JOURNAL, 15(5), 2963-2973 [10.1109/JSEN.2014.2383996].
Magno, Michele; Polonelli, Tommaso; Benini, Luca; Popovici, Emanuel
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11585/544975
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