In this paper, we present an energy-saving controller that is capable of shaping the light output of an LED lighting system autonomously based on data received from sensors. We implement an optimized smart algorithm on a controller to process the sensor feedback and employ pulse width modulation dimming to vary the brightness of the luminaire. A wireless sensor module was designed to provide accurate sensor feedback to the controller. A purpose-built smart luminaire complete with an LED driver was designed and constructed to study the performance of the control system. We validate the energy saving potential of the designed controller under different real world situations. It is shown experimentally that the controller achieved 55% energy savings in a continuous usage pattern environment and 62% energy savings in a discrete usage pattern environment under our test conditions. A cost analysis showed that the proposed energy-saving system is 32% more cost-effective than a near-equivalent commercial system while promising greater energy savings through the use of additional energy-saving techniques.

Light emitting diodes (LEDs), with their ability to produce tunable light spectrums, present a significant opportunity to improve on existing lighting systems. They can be applied to smart and specialized lighting, which can be highly beneficial in the residential, commercial, and industrial sectors. In this paper, we present a novel closed-loop control algorithm with feedback from a spectral sensor, which allows the light output spectrum to converge toward a target spectrum. The control system was experimentally validated by the hardware implementation of a wireless smart lighting system with the eight tunable LED channels with different dominant wavelengths (450-650 nm) designed to cover a large portion of the visible light spectrum. Experimental results show a near perfect replication of target spectra, with an accuracy within 5% for the correlated color temperatures and Euclidean distances which fall well within a five-step u'v' unit circle.

Potential advantages offered by multichannel luminaires with regards to spectral tuning are frequently overshadowed by its design challenges, a major one being the non-uniformity in illuminance and color distribution. In this paper, we present a formulation using genetic algorithm (GA) to optimize the Light Emitting Diode (LED) placement, yielding 40% superior uniformity in illuminance and color distributions compared to existing analytical formulations, substantially reducing the reliance on optical design for this purpose. It is specifically shown that our approach is employable for circadian tuning applications, even when heavily constrained by industry specifications on panel size and minimum LED separation.

The regular rise and fall of the sun resulted in the development of 24-h rhythms in virtually all organisms. In an evolutionary heartbeat, humans have taken control of their light environment with electric light. Humans are highly sensitive to light, yet most people now use light until bedtime. We evaluated the impact of modern home lighting environments in relation to sleep and individual-level light sensitivity using a new wearable spectrophotometer. We found that nearly half of homes had bright enough light to suppress melatonin by 50%, but with a wide range of individual responses (0–87% suppression for the average home). Greater evening light relative to an individual’s average was associated with increased wakefulness after bedtime. Homes with energy-efficient lights had nearly double the melanopic illuminance of homes with incandescent lighting. These findings demonstrate that home lighting significantly affects sleep and the circadian system, but the impact of lighting for a specific individual in their home is highly unpredictable.

There exists a need for the design of light emitting diode (LED) luminaires which can deliver both visual and non-visual benefits of light to humans. In this work, we introduce an optimization approach based on spectral shaping for a minimalistic and practical design of a circadian-tunable multi-channel luminaire which also outputs white light with high quality and luminous efficacy of radiation (LER). The spectral optimization approach utilizes Multi-objective Genetic Algorithm to maximize circadian tunability, light quality and LER while minimizing the number of channels. Solution sets are constrained using the non-visual quality metric, Melanopic Efficacy of Luminous Radiation (MELR) from the Melanopic Equivalent Daylight Illuminance (MEDI) approach and the more stringent visual quality metric TM-30 in addition to conventional Color Rendering Index (CRI). By matching theoretically optimized LED parameters to commercially available LED parameters for commercialization purposes, we establish the maximum MELR tunability that is achievable with 4 and 5 LED channels and the resulting trade-off in efficacy and light quality. Based on the results and analysis in this work, we detail a spectral optimization approach to propel the field of indoor lighting towards human-centric lighting.

Smart homes and Internet of Things are emerging concepts in modern society, with intelligent lighting being an important part of it. Besides providing visual satisfaction through its color-rendering properties, lighting also has other effects on human well-being. In order to exploit the full potential of a smartly lit home, lighting systems need to be equipped with accurate controllers that can control the spectrum and color characteristics of light in addition to conventional ON-OFF and dimming control. However, current commercial smart lighting products with such capabilities need to employ expensive sensors which are still lacking in terms of closed-loop feedback which is imperative for accurate color control of light-emitting diode (LED)-based luminaires. This paper presents a novel approach that uses the camera available on modern smartphones to perform closed-loop color control for lighting systems in smart homes. The algorithm is able to perform multi-channel mixing for any color and also white light at a desired correlated color temperature with high color-rendering index. This approach proves to be very economical and convenient as no external sensors are required and can be performed using any Android smartphone on a compatible LED-based luminaire.

This paper presents novel LED-based lighting solutions that can impact the mobility of individuals with low vision. By conducting three separate experiments involving mobility courses, the authors evaluate the effects of illuminance, correlated color temperature, object edge enhancement and contrast-enhancing lighting on the mobility of people with low vision. Using a total of 134 participants comprising of elderly, low vision subjects, and normal vision subjects wearing low-vision simulation glasses, the impact of these lighting solutions on the mobility of low vision subjects with blurry vision, central scotoma, tunnel vision and cataract are presented, making them a potential alternative to conventional mobility aids.

As smartphones become increasingly powerful and ubiquitous, integrating them into intelligent lighting systems can boost both convenience and energy efficiency. This paper presents an intelligent lighting system prototype with enhanced security features for smart homes. The custom-built Android mobile application made use of the onboard ambient light sensor to run a novel closed-loop feedback algorithm to implement daylight harvesting. A cost analysis shows that the whole system setup is slightly cheaper than commercial products and due to its daylight harvesting capabilities, has potential for monetary savings in the long run, outperforming current commercial products.