Lighting control with distributed wireless sensing and actuation for daylight and occupancy adaptation

Peruffo, Andrea; Pandharipande, Ashish; Caicedo, David; Schenato, Luca

doi:10.1016/j.enbuild.2015.03.049

Cited by 63 publications

(31 citation statements)

References 14 publications

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“…The path loss propagation model (6) has been widely used in wireless communications to model RSSI values at a receiver as a function of its distance from the transmitter [36], [37]. This RSSI model has also been used in the evaluation of wireless positioning methods [9], [19].…”

Section: A Simulation Scenariosmentioning

confidence: 99%

“…This sensing information is used to adapt the light output of luminaires to occupancy and daylight changes for reducing energy consumption and providing better illumination comfort [1], [2]. Lighting systems are also getting interconnected, with wireless technologies providing a flexible way to communicate data across sensors and controllers [3], [4], [5], [6]. Such a wireless lighting control system can provide an enabling infrastructure for offering a host of building services [7].…”

Section: Introductionmentioning

confidence: 99%

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Location-Based Illumination Control Access in Wireless Lighting Systems

Pandharipande

2015

IEEE Sensors J.

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Indoor lighting systems with wireless sensorequipped luminaires are considered as an infrastructure for offering location-based illumination control. Wireless occupancy and light sensors transmit sensing information to a lighting controller, which then adapts artificial illumination from luminaires to user occupancy and daylight changes. Such wireless sensor transmissions can be used to collect received signal strength indicator (RSSI) values at a user device. We propose to use the RSSI measurements at the user device, in combination with accelerometer sensor data, to determine user location zone when a user seeks personalized light control. Based on its location zone, the user is granted control of associated luminaires. The performance of the proposed system and positioning method is evaluated in a large indoor lighting open-plan office model.

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Section: A Simulation Scenariosmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Location-Based Illumination Control Access in Wireless Lighting Systems

Pandharipande

2015

IEEE Sensors J.

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“…This can potentially lead to slower response of the lighting system due to daylight changes and dimming jumps in luminaires; thus, control messaging protocols and lighting control methods need to be designed for system robustness and to ensure that the end user has a similar lighting experience irrespective of the underlying communication interface. In [48], the impact of wireless impairments owhen using stand-alone PI control laws was studied. Transmission redundancy was introduced and enhancements in the controller were considered to improve the performance of the wireless lighting control system.…”

Section: Technical Challengesmentioning

confidence: 99%

Smart indoor lighting systems with luminaire-based sensing: A review of lighting control approaches

Pandharipande

Caicedo

2015

Energy and Buildings

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149

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“…On the other hand, wireless networks suffer from unreliable communications leading to high packet-loss rates and large random delays due to interferences, power failures, multipath fading. An accurate work should thus be done studying the effect of these packet losses on the proposed controller, as was done in [24] for the stand-alone controller used as a benchmark in this work.…”

Section: Sensor-driven Personal Lighting Controlmentioning

confidence: 99%

Personal lighting control with occupancy and daylight adaptation

Rossi

Pandharipande

Caicedo

et al. 2015

Energy and Buildings

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AcknowledgementsTo whom has always been with me ... AbstractPersonal control with occupancy and daylight adaptation is considered in a lighting system with multiple luminaires. Each luminaire is equipped with a co-located occupancy sensor and light sensor that respectively provide local occupancy and illumination information to a central controller. Users may also provide control inputs to indicate a desired illuminance value. Using sensor feedback and user input, the central controller determines dimming values of the luminaires using an optimization framework. The cost function consists of a weighted sum of illumination errors at light sensors and the power consumption of the system. The optimum dimming values are determined by solving an unconstrained optimization and a constrained optimization. The constrained solution is solved with the constraints that the illuminance value at the light sensors are above the reference set-point at the light sensors and the dimming levels are within physical allowable limits. Different approaches to determine the set-points at light sensors associated with multiple user illumination requests are considered. The performance of the proposed controllers is compared with a reference stand-alone controller under different simulation scenarios in an open-plan office lighting system.

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Lighting control with distributed wireless sensing and actuation for daylight and occupancy adaptation

Cited by 63 publications

References 14 publications

Location-Based Illumination Control Access in Wireless Lighting Systems

Location-Based Illumination Control Access in Wireless Lighting Systems

Smart indoor lighting systems with luminaire-based sensing: A review of lighting control approaches

Personal lighting control with occupancy and daylight adaptation

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