Daylight-Artificial Light Integrated Scheme Based on Digital Camera and Wireless Networked Sensing-Actuation System

Varghese, Susan G; Kurian, Ciji Pearl; George, V I; Kumar, Thakur Sanjay

doi:10.1109/tce.2019.2924078

Cited by 13 publications

(13 citation statements)

References 21 publications

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“…1, the window and work plane low dynamic range images are captured by the digital camera. Varghese et al [3] discussed, the image processing algorithm to detect occupancy, daylight information at the window, illuminance at the workplane. As the initial event, the camera act as occupancy sensor, and the information about occupant is present or not is sent to the controller.…”

Section: System Descriptionmentioning

confidence: 99%

“…After fixing the blind position based on the daylight availability, the gain scheduling-based luminaire dimming controller, controls the actuator nodes through ZigBee based networking scheme of the lighting control system. The networking and energy consumption evaluation method are discussed based on the window blind control signals generated in [3]. The blind operation is defined in two states, CW and ACW, for closing and opening of the blind respectively.…”

Section: System Descriptionmentioning

confidence: 99%

“…For a battery powered network scheme, the important sources of energy consumption are transmit power, receive power, power consumed for idle listening of sensor nodes. This paper presents the network framework architecture of the design and implementation associated with a camerabased Daylight-Artificial Light Integrated Scheme (DALIS) [3]. The energy model of the wireless nodes could help the users to get the awareness on battery life of the nodes.…”

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confidence: 99%

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Wireless Sensor Actuator Network Architecture and Energy Model of a Camera Based Lighting Management System

2022

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Communication protocols and wireless networking technique is a cohesive part of any light management system. IEEE 802.15.4 standard based networking techniques for the climate-adaptive light management system and its energy model for sensor actuator node is the focus of this paper. This light integrated scheme with adaptive controls provides the desired illuminance at appropriate times with uniformity, by reducing the discomfort glare and energy use. The first part of this paper investigates the architecture and energy consumption of camera-based wireless sensor-actuator nodes with the help of energy models, including a control unit for the Light Management System. Then focused on the energy savings and techno-economic analysis of this wireless networked lighting system in a test room with automated control of Light Emitting Diode luminaire and Venetian blinds. The wireless sensor actuator networked lighting system performance is analyzed by evaluating the node energy consumption in idle and active mode with real time measurements. The energy consumption evaluation of the nodes allows users to improve node life time and think about power management schemes. The climate-adaptive control scheme shows improved uniformity and significant energy savings.

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Section: System Descriptionmentioning

confidence: 99%

Section: System Descriptionmentioning

confidence: 99%

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confidence: 99%

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Wireless Sensor Actuator Network Architecture and Energy Model of a Camera Based Lighting Management System

2022

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“…In our earlier work, we proposed the data-driven models for the control of the window blind and LED luminaires [36], considered four predictors (solar irradiance, EDW, Temperature, ALT) and one response (F m (x)), and developed four different models for the four different window orientation.…”

Section: ) Feature Selectionmentioning

confidence: 99%

“…Here, the conventional sensor and Labview-myRIO based standalone system presented. Varghese et al [36] also proposed the wireless sensor network with digital camera technology for the daylight-artificial light integration scheme. Sanjeev et al, in their initial proposed [37] machine learning-based predictive model for the daylight-artificial light integration scheme, developed four different blind control models for four sides of windows.…”

Section: Introductionmentioning

confidence: 99%

Ensemble Learning Model-Based Test Workbench for the Optimization of Building Energy Performance and Occupant Comfort

2020

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Buildings consume tremendous energy for the improvement of living and working conditions. Control of daylight-artificial light has the potential to improve energy performance and occupant comfort in buildings. This research proposes an intelligent generalized ensemble learning technique to develop a novel control strategy for Venetian-blind positioning (up-down movement with static slat angle of 45 • ) of different window orientations. The proposed model helps to maintain occupant comfort and energy saving in a commercial building. The performance of the ensemble learning approach compared against Gaussian process regression, support vector regression and artificial neural network using conventional statistical indicators. Finally, the proposed data-driven model implemented in a real-time Labview-myRIO platform for the experimental validation. The data-driven model is compared with the baseline model and with the uncontrolled blind condition in terms of daylight glare, and energy consumption of lighting and air-conditioning system in the building. The data-driven model is derived using two years of data collected from a fuzzy-based daylight-artificial light integrated scheme. The blind position providing reduced energy consumption and daylight glare along with setpoint illuminance and temperature are validated. A high dynamic range image with EVALGLARE software used to verify the visual comfort based on daylight glare probability. While evaluating the overall energy savings, the ensemble learning model consumes 17% less power than the uncontrolled system and 15% less power than the baseline system. Here, though we are not controlling the air-conditioning system, the experimental validation confirmed that the air-conditioning system significantly reduces its energy consumption.INDEX TERMS Window blind control, data-driven models, ensemble learning, bayesian optimization, daylight glare, labview, myRIO, energy comparison, lighting control, air-conditioning.

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Low-Cost Image-Based Occupancy Sensor Using Deep Learning

Kumar

Varghese

Kurian

et al. 2021

Advances in Renewable Energy and Electric Vehicles

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Daylight-Artificial Light Integrated Scheme Based on Digital Camera and Wireless Networked Sensing-Actuation System

Cited by 13 publications

References 21 publications

Wireless Sensor Actuator Network Architecture and Energy Model of a Camera Based Lighting Management System

Wireless Sensor Actuator Network Architecture and Energy Model of a Camera Based Lighting Management System

Ensemble Learning Model-Based Test Workbench for the Optimization of Building Energy Performance and Occupant Comfort

Low-Cost Image-Based Occupancy Sensor Using Deep Learning

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