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Although research has made significant findings in the neurophysiological process behind the pupillary light reflex, the temporal prediction of the pupil diameter triggered by polychromatic or chromatic stimulus spectra is still not possible. State of the art pupil models rested in estimating a static diameter at the equilibrium-state for spectra along the Planckian locus. Neither the temporal receptor-weighting nor the spectral-dependent adaptation behaviour of the afferent pupil control path is mapped in such functions. Here we propose a deep learning-driven concept of a pupil model, which reconstructs the pupil’s time course either from photometric and colourimetric or receptor-based stimulus quantities. By merging feed-forward neural networks with a biomechanical differential equation, we predict the temporal pupil light response with a mean absolute error below 0.1 mm from polychromatic (2007 ± 1 K, 4983 ± 3 K, 10,138 ± 22 K) and chromatic spectra (450 nm, 530 nm, 610 nm, 660 nm) at 100.01 ± 0.25 cd/m 2 . This non-parametric and self-learning concept could open the door to a generalized description of the pupil behaviour.

In the context of intelligent and integrative lighting, in addition to the need for color quality and brightness, the non-visual effect is essential. This refers to the retinal ganglion cells (ipRGCs) and their function, which were first proposed in 1927. The melanopsin action spectrum has been published in CIE S 026/E: 2018 with the corresponding melanopic equivalent daylight (D65) illuminance (mEDI), melanopic daylight (D65) efficacy ratio (mDER), and four other parameters. Due to the importance of mEDI and mDER, this work synthesizes a simple computational model of mDER as the main research objective, based on a database of 4214 practical spectral power distributions (SPDs) of daylight, conventional, LED, and mixed light sources. In addition to the high correlation coefficient R2 of 0.96795 and the 97% confidence offset of 0.0067802, the feasibility of the mDER model in intelligent and integrated lighting applications has been extensively tested and validated. The uncertainty between the mEDI calculated directly from the spectra and that obtained by processing the RGB sensor and applying the mDER model reached ± 3.3% after matrix transformation and illuminance processing combined with the successful mDER calculation model. This result opens the potential for low-cost RGB sensors for applications in intelligent and integrative lighting systems to optimize and compensate for the non-visual effective parameter mEDI using daylight and artificial light in indoor spaces. The goal of the research on RGB sensors and the corresponding processing method are also presented and their feasibility is methodically demonstrated. A comprehensive investigation with a huge amount of color sensor sensitivities is necessary in a future work of other research.

Multi-channel LED luminaires offer a powerful tool to vary retinal receptor signals while keeping visual parameters such as color or brightness perception constant. This technology could provide new fields of application in indoor lighting since the spectrum can be enhanced individually to the users’ favor or task. One possible application would be to optimize a light spectrum by using the pupil diameter as a parameter to increase the visual acuity. A spectral- and time-dependent pupil model is the key requirement for this aim. We benchmarked in our work selected L- and M-cone based pupil models to find the estimation error in predicting the pupil diameter for chromatic and polychromatic spectra at 100 cd/m 2 . We report an increased estimation error up to 1.21 mm for 450 nm at 60–300 s exposure time. At short exposure times, the pupil diameter was approximately independent of the used spectrum, allowing to use the luminance for a pupil model. Polychromatic spectra along the Planckian locus showed at 60–300 s exposure time, a prediction error within a tolerance range of ± 0.5 mm. The time dependency seems to be more essential than the spectral dependency when using polychromatic spectra.

Thermopile sensor arrays provide a sufficient counterbalance between person detection and localization while preserving privacy through low resolution. The latter is especially important in the context of smart building automation applications. Current research has shown that there are two machine learning-based algorithms that are particularly prominent for general object detection: You Only Look Once (YOLOv5) and Detection Transformer (DETR). Over the course of this paper, both algorithms are adapted to localize people in 32 × 32-pixel thermal array images. The drawbacks in precision due to the sparse amount of labeled data were counteracted with a novel generative image generator (IIG). This generator creates synthetic thermal frames from the sparse amount of available labeled data. Multiple robustness tests were performed during the evaluation process to determine the overall usability of the aforementioned algorithms as well as the advantage of the image generator. Both algorithms provide a high mean average precision (mAP) exceeding 98%. They also prove to be robust against disturbances of warm air streams, sun radiation, the replacement of the sensor with an equal type sensor, new persons, cold objects, movements along the image frame border and people standing still. However, the precision decreases for persons wearing thick layers of clothes, such as winter clothing, or in scenarios where the number of present persons exceeds the number of persons the algorithm was trained on. In summary, both algorithms are suitable for detection and localization purposes, although YOLOv5m has the advantage in real-time image processing capabilities, accompanied by a smaller model size and slightly higher precision.

Cortisol secretion has a fundamental role in human circadian regulation. The cortisol awakening response (CAR) can be observed as a daily recurring sharp increase in cortisol concentration within the first hour after awakening and is influenced by environmental light conditions. The current work provides the study protocol for an ongoing research project that is intended to explore the spectral dependencies and to discuss measures of emotional state and cognitive functioning potentially related to the CAR. Based on a controlled within-subjects sleep laboratory study, the impact of a two-hour, (quasi-)monochromatic, post-awakening light exposure of different peak wavelength (applied from 6:00 to 8:00 am) on resulting CAR levels should be investigated in a systematic manner to eventually derive a corresponding spectral sensitivity model. As a secondary outcome, it should be explored whether a potentially light-enhanced cortisol secretion might also impact different measures of sleepiness, mood, and vigilance for certain wavelengths. The study protocol described in the present work discusses the various protocol steps using pilot data collected for two different wavelength settings (i.e., short-wavelength blue-light at λ max = 476 nm and long-wavelength red-light at λ max = 649 nm) experienced by a group of four healthy male adults at an average ± SD age of 25.25 ± 3.59 years.

The time spent indoors under artificial (electric) lighting has continued to increase and currently amounts to up to 90% of the day. Light is the most important stimulus for the circadian rhythm and has, besides long-term effects, also a direct impact on emotional and physiological aspects such as sleepiness, alertness, or performance. This article presents the results of two studies investigating the acute effects of light during morning and early afternoon on people in a controlled office environment. Melanopically optimized lighting conditions, and a dose–response dependency are investigated, measuring cognitive performance, subjective sleepiness, and user preferences of the lighting scenarios as well as cardiac effort. The results show a dependency in subjective sleepiness ratings depending on light conditions and time of day. Further parameters did not show any statistical differences. The presented studies extend the findings of acute light effects during the day but are limited due to relatively small sample sizes.

Intelligent systems for interior lighting strive to balance economical, ecological, and health-related needs. For this purpose, they rely on sensors to assess and respond to the current room conditions. With an augmented demand for more dedicated control, the number of sensors used in parallel increases considerably. In this context, the present work focuses on optical sensors with three spectral channels used to capture color-related information of the illumination conditions such as their chromaticities and correlated color temperatures. One major drawback of these devices, in particular with regard to intelligent lighting control, is that even same-type color sensors show production related differences in their color registration. Standard methods for color correction are either impractical for large-scale production or they result in large colorimetric errors. Therefore, this article shows the feasibility of a novel sensor binning approach using the sensor responses to a single white light source for cluster assignment. A cluster specific color correction is shown to significantly reduce the registered color differences for a selection of test stimuli to values in the range of 0.003–0.008 Δu′v′, which enables the wide use of such sensors in practice and, at the same time, requires minimal additional effort in sensor commissioning.

Smart integrative lighting systems aim to support human health and wellbeing by capitalising on the light-induced effects on circadian rhythms, sleep, and cognitive functions, while optimising the light’s visual aspects like colour fidelity, visual comfort, visual preference, and visibility. Metameric spectral tuning could be an instrument to solve potential conflicts between the visual preferences of users with respect to illuminance and chromaticity and the circadian consequences of the light exposure, as metamers can selectively modulate melanopsin-based photoreception without affecting visual properties such as chromaticity or illuminance. This work uses a 6-, 8- and 11-channel LED luminaire with fixed illuminance of 250 lx to systematically investigate the metameric tuning range in melanopic equivalent daylight illuminance (EDI) and melanopic daylight efficacy ratio (melanopic DER) for 561 chromaticity coordinates as optimisation targets (2700 K to 7443 K ± Duv 0 to 0.048), while applying colour fidelity index R f criteria from the TM-30-20 Annex E recommendations (i.e. R f ≥ 85, R f,h1 ≥ 85). Our results reveal that the melanopic tuning range increases with rising CCT to a maximum tuning range in melanopic DER of 0.24 (CCT: 6702 K, Duv: 0.003), 0.29 (CCT: 7443 K, Duv: 0) and 0.30 (CCT: 6702, Duv: 0.006), depending on the luminaire’s channel number of 6, 8 or 11, respectively. This allows to vary the melanopic EDI from 212.5–227.5 lx up to 275–300 lx without changes in the photopic illuminance (250 lx) or chromaticity ( Δ u ′ v ′ ≤ 0.0014). The highest metameric melanopic Michelson contrast for the 6-, 8- and 11-channel luminaire is 0.16, 0.18 and 0.18, which is accomplished at a CCT of 3017 K (Duv: − 0.018), 3456 K (Duv: 0.009) and 3456 K (Duv: 0.009), respectively. By optimising ~ 490,000 multi-channel LED spectra, we identified chromaticity regions in the CIExy colour space that are of particular interest to control the melanopic efficacy with metameric spectral tuning.

This work intends to define the resolution requirements for near-field projections in a psycho-physical study design to evaluate the participants’ perception under the influence of different ambient lighting levels and various viewing distances. The variation in ambient lighting and viewing distances relates to various daytime and critical distances in urban environments. The application of near-field projections increases the popularity of communication- or safety-relevant projections, such as for automated vehicles. However, previous studies in the filming industry have shown that the resolution requirements differ depending on the application. In this work, a field study design presents an experimental approach to define a perceived resolution on the street surface in the near field around the vehicle. Furthermore, the study evaluates the influence of viewing distance, ambient lighting and projection content on the perceived resolution in detail. The results reveal a significant dependency on ambient lighting (p < 0.05). Furthermore, this work states that the symbol-based projection has lower resolution requirements, e.g., a viewing distance of 1 m and 3 m results in a 2 pixels per degree resolution compared to the text-based projection in the parking garage scenario. Nevertheless, in the dusk/dawn scenario, the perceived resolution can be grouped for viewing distances above 1 m for content-independent projections.

Today, up to hundreds of RGB and W-LEDs are positioned in a vehicle’s interior context and are able to be individually controlled in intensity, color and sequence. However, which kind of illumination distracts or supports car occupants and how to define such a modern illumination system is still under discussion and unknown. For that, first a definition for an in-vehicle lighting system is introduced. Second, a globally distributed study was performed based on a free-access online survey to investigate in-vehicle lighting for visual signaling within 10 colors, eight positions and six dynamic patterns. In total, 238 participants from China and Europe rated color preferences, color moods, light-position preferences, differences between manual and autonomous driving and also different meanings for dynamic lighting patterns. Out of these, three strong significant (p < 0.05) color preference groups were identified with a polarized, accepted or merged character. For the important driving-signaling mood attention, we found a significant hue dependency for Europeans which was missing within the Chinese participants. In addition, we identified that light positioned at the door and foot area was globally favored. Furthermore, we evaluated qualitative results: men are primarily focusing on fast-forward, whereas women paid more attention on practical light usage. These findings conclude the need for a higher lighting-car-occupant adaptation in the future grounded by deeper in-vehicle human factors research to achieve a higher satisfaction level. In interdisciplinary terms, our findings might also be helpful for interior building or general modern cockpit designs for trains or airplanes.