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A polypyrrole-bismuth tungstate (Ppy-Bi2WO6) core-shell nanocomposite (n-type material) has been developed on a layered Ppy (p-type) base as an efficient light-capturing material exhibiting photodiode behavior. This device demonstrates promising sensitivity for light sensing and captures across a broad spectral range, from near IR to UV. The Bi2WO6/Ppy nanocomposite boasts an optimal bandgap of 2.0 eV, compared to 3.4 eV for Ppy and 2.5 eV for Bi2WO6. The crystalline size of the core-shell composite is approximately 21 nm, emphasizing its photon absorption capabilities. The composite particles, around 100 nm in length, feature a highly porous morphology that effectively traps incident photons. The performance of this optoelectronic device is evaluated using current density (J) measurements under light (Jph) and dark (Jo) conditions. In darkness, the n-p type semiconductor exhibits limited current with a Jo of −0.22 mA cm−2 at 2.0 V. When exposed to white light, the Ppy- Bi2WO6/Ppy device generates hot electrons, achieving a Jph value of 1.1 mA/cm−2 at 2.0 V. It shows a superior responsivity (R) of 6.6 mA/W at 340 nm, gradually decreasing to 6.3 mA/W at 440 nm and 4.2 mA/W at 540 nm, indicating high sensitivity across the UV-Vis spectrum. At 730 nm, the R-value is 2.6 mA/W, highlighting its sensitivity in the near IR region. Additionally, at 340 nm, the device achieves a detectivity (D) value of 0.15 × 10¹⁰ Jones, which decreases with longer wavelengths to 0.14 × 10¹⁰ Jones at 440 nm, 0.9 × 10⁹ Jones at 540 nm, and 0.63 × 10⁹ Jones at 730 nm. With its great stability, low cost, easy fabrication, and potential for mass production, this optoelectronic light sensor and photodiode device holds significant promise for industrial applications as a highly effective optoelectronic device. [ABSTRACT FROM AUTHOR]

Abstract A polypyrrole-bismuth tungstate (Ppy-Bi2WO6) core-shell nanocomposite (n-type material) has been developed on a layered Ppy (p-type) base as an efficient light-capturing material exhibiting photodiode behavior. This device demonstrates promising sensitivity for light sensing and captures across a broad spectral range, from near IR to UV. The Bi2WO6/Ppy nanocomposite boasts an optimal bandgap of 2.0 eV, compared to 3.4 eV for Ppy and 2.5 eV for Bi2WO6. The crystalline size of the core-shell composite is approximately 21 nm, emphasizing its photon absorption capabilities. The composite particles, around 100 nm in length, feature a highly porous morphology that effectively traps incident photons. The performance of this optoelectronic device is evaluated using current density (J) measurements under light (Jph) and dark (Jo) conditions. In darkness, the n-p type semiconductor exhibits limited current with a Jo of −0.22 mA cm−2 at 2.0 V. When exposed to white light, the Ppy- Bi2WO6/Ppy device generates hot electrons, achieving a Jph value of 1.1 mA/cm−2 at 2.0 V. It shows a superior responsivity (R) of 6.6 mA/W at 340 nm, gradually decreasing to 6.3 mA/W at 440 nm and 4.2 mA/W at 540 nm, indicating high sensitivity across the UV-Vis spectrum. At 730 nm, the R-value is 2.6 mA/W, highlighting its sensitivity in the near IR region. Additionally, at 340 nm, the device achieves a detectivity (D) value of 0.15 × 10¹⁰ Jones, which decreases with longer wavelengths to 0.14 × 10¹⁰ Jones at 440 nm, 0.9 × 10⁹ Jones at 540 nm, and 0.63 × 10⁹ Jones at 730 nm. With its great stability, low cost, easy fabrication, and potential for mass production, this optoelectronic light sensor and photodiode device holds significant promise for industrial applications as a highly effective optoelectronic device.

Light enhances or disrupts circadian rhythms, depending on the timing of exposure. Circadian disruption contributes to poor health outcomes that increase mortality risk. Whether personal light exposure predicts mortality risk has not been established. We therefore investigated whether personal day and night light, and light patterns that disrupt circadian rhythms, predicted mortality risk. UK Biobank participants (N = 88,905, 62.4 ± 7.8 y, 57% female) wore light sensors for 1 wk. Day and night light exposures were defined by factor analysis of 24-h light profiles. A computational model of the human circadian pacemaker was applied to model circadian amplitude and phase from light data. Cause-specific mortality was recorded in 3,750 participants across a mean (±SD) follow-up period of 8.0 ± 1.0 y. Individuals with brighter day light had incrementally lower all-cause mortality risk (adjusted-HR ranges: 0.84 to 0.90 [50 to 70th light exposure percentiles], 0.74 to 0.84 [70 to 90th], and 0.66 to 0.83 [90 to 100th]), and those with brighter night light had incrementally higher all-cause mortality risk (aHR ranges: 1.15 to 1.18 [70 to 90th], and 1.21 to 1.34 [90 to 100th]), compared to individuals in darker environments (0 to 50th percentiles). Individuals with lower circadian amplitude (aHR range: 0.90 to 0.96 per SD), earlier circadian phase (aHR range: 1.16 to 1.30), or later circadian phase (aHR range: 1.13 to 1.20) had higher all-cause mortality risks. Day light, night light, and circadian amplitude predicted cardiometabolic mortality, with larger hazard ratios than for mortality by other causes. Findings were robust to adjustment for age, sex, ethnicity, photoperiod, and sociodemographic and lifestyle factors. Minimizing night light, maximizing day light, and keeping regular light–dark patterns that enhance circadian rhythms may promote cardiometabolic health and longevity. [ABSTRACT FROM AUTHOR]

The synthesis of coral reefs-like lead diiodide-polypyrrole growth on a seeded polypyrrole film (PbI2-Ppy/Ppy) nanocomposite involves a redox polymerization reaction utilizing iodine as an oxidizing agent. This nanocomposite exhibits remarkable morphological characteristics, comprising porous spherical particles (diameter of approximately 350 nm). Intriguingly, these particles are coated with smaller particles measuring around 20 nm. Noteworthy is the nanocomposite’s excellent optical behavior, characterized by a 2.6 eV bandgap, rendering it a highly photon sensor in the UV or visible (Vis) regions. The PbI2-Ppy/Ppy thin film, derived from this nanocomposite, emerges as a favorable choice for light sensing applications in the UV and Vis regions. The study evaluates its performance by subjecting it to monochromatic light ranging from 340 to 730 nm, with the resulting current density (Jph) values serving as indicators of its light-sensing capabilities. At 340 nm, the Jph reaches 0.076 mA/cm2, with corresponding responsiveness (R) and detectivity (D) values of 0.76 mA.W-1 and 1.7 × 108 Jones, correspondingly. The ease of fabrication associated with the PbI2-Ppy/Ppy thin film positions it as a promising electrical device for light sensing across a broad optical spectrum. Its impressive behavior in light sensing applications, combined with its straightforward fabrication process, underscores its potential as a promising solution for a wide range of optical sensing. [ABSTRACT FROM AUTHOR]

Aiming at sports tourism environment simulation, this paper aims to explore the application of machine learning algorithm based on light sensor in this field. We propose a new method for sports tourism simulation, which is based on optical sensor data acquisition and processing. The aim of this research is to develop an accurate and efficient algorithm to simulate the optical properties of sports event venues in order to provide a more realistic sports tourism experience. The research method consists of two main steps: optical sensor data collection and machine learning algorithm modeling and training. First, a network of optical sensors was set up to collect light intensity and color information at different locations in the stadium. This data is then used to train a machine learning algorithm to predict and simulate the sports tourism environment under different optical scenarios. Through experiments and evaluations, the proposed algorithm performs well in terms of accuracy and efficiency, and can simulate the lighting characteristics of sports venues with high accuracy. This provides a strong technical support for sports tourism simulation, which can provide users with a more realistic experience. [ABSTRACT FROM AUTHOR]

With the rapid development of the Internet of Things, the real-time monitoring of residents' sports health service system has become a key demand. As a common optical sensing technology, light sensor has the advantages of high sensitivity and real-time performance. Therefore, this paper discusses the application potential of real-time monitoring of Internet of Things based on light sensor in residents' physical health service system, and evaluates its effectiveness and feasibility in monitoring users' movement, physical signs and environmental information. A real-time monitoring system of Internet of Things based on light sensor is designed and integrated into the residents' sports health service system. Multiple optical sensor modules are used to collect real-time user movement, physical signs and environmental information. By analyzing and processing sensor data, the performance of the system in real-time monitoring of user movement, physical signs and environmental information was evaluated. Experiments show that the real-time monitoring system based on light sensor can effectively monitor the user's movement, physical signs and environmental information in real time. The system has a high degree of sensitivity and accuracy, and can accurately identify the user's type of exercise, heart rate changes, and environmental parameters. [ABSTRACT FROM AUTHOR]

Wushu has unique movement requirements and techniques, but the traditional methods of optimizing wushu have some problems, such as unstable effect and difficult quantitative evaluation. In recent years, light sensors have been widely used in the field of image processing and detection, but there is little research on the application of martial arts motion optimization and image defect detection. The purpose of this study is to optimize martial arts movements and detect image defects by using light sensors based on reinforcement learning (RL) algorithm. The system collected the data of martial arts movement and image defects. Based on RL algorithm, the optimization model of optical sensor is established. The model is trained to optimize martial arts movements and detect image defects. The experimental results show that the light sensor based on RL can effectively optimize martial arts movements and accurately detect image defects. The proposed method improves the accuracy and fluency of martial arts movements in terms of optimization, and achieves high precision and efficiency in image defect detection, providing a new method and idea for martial arts training and image processing. [ABSTRACT FROM AUTHOR]

In martial arts training, a system that can accurately capture and analyze the movement trajectory is needed so that the trainer can better master the skills and improve the movement. The aim of this research is to design and implement a visualization system based on light sensor for simulating image trajectory in martial arts training. Through the use of optical sensors, the movement of the trainer is captured in real time and converted into a visual image trajectory, so that the trainer can intuitively understand their own movements and skills. The study used optical sensors to capture the movements of the trainers. The sensor is able to detect motion with high precision and convert it into digital data. A set of algorithms is developed to convert these digital data into visual image tracks, through which trainers can observe their movements and skills in real time. The results show that the system performs well in capturing and simulating image trajectories. By capturing and simulating image trajectories in real time, trainers can understand their own movements and skills more intuitively, and make targeted improvements. [ABSTRACT FROM AUTHOR]

Effective physical training is the necessary condition to achieve good physical training effect and greatly improve the level of physical competition. Therefore, it is necessary to take scientific and reasonable technical means to carry out systematic and effective supervision and management to ensure the effectiveness of training. This paper first analyzes the leg movement of swimmers, and defines the different intensity of swimming. After careful study, an image acquisition system based on light sensor is designed and developed for technical analysis and simulation of swimmers. The research uses advanced light sensor technology to design an image acquisition system that can record various movements of swimmers in the water in real time and convert them into digital data. By establishing a set of effective algorithms, these data are analyzed and simulated accurately. The experimental results show that the image acquisition system can accurately record swimmers' movements, and accurately analyze and simulate their technical performance. Compared with the traditional technical analysis method, the system in this paper is not only more accurate, but also can provide more comprehensive data support, which can effectively improve the accuracy and credibility of technical analysis, and has great significance for the improvement of swimming training and competitive level. [ABSTRACT FROM AUTHOR]

Due to the advancement of technology and artificial intelligence, visual inspection technology is rapidly and vigorously developing. It is not only widely used in various industries, but also deeply embedded in human daily life. For example, in the traditional camera calibration process, calibration blocks and other related data such as images, text, maps, etc. can be used to accurately obtain the image center. The purpose of this study is to improve the application effect of light sensor in the simulation analysis of dance teaching mode by improving the vision extraction algorithm. In this study, an improved vision extraction algorithm is adopted, which can more accurately extract key information in the images of dance teaching mode, and reasonable arrangement and parameter setting of the light sensor are carried out to ensure that the collected images have high quality and clarity. By applying the improved algorithm to the collected images, the key information in the images of dance teaching mode is extracted. This article conducts simulation analysis on dance teaching mode images based on visual extraction algorithms. The optimized algorithm can significantly reduce the occurrence of ghosts and effectively suppress the shadow of the target. This greatly improves the accuracy of the optimized dance action recognition model, making it a reliable dance education tool. It not only captures the dynamics of dancers more accurately, but also records them more effectively, making it a widely used dance teaching tool. [ABSTRACT FROM AUTHOR]

This paper focuses on a human motion image detection and tracking method that utilizes a Gaussian mixture model and light sensor. The objective is to develop an accurate and efficient approach for detecting and tracking human motion images in various applications such as human behavior analysis and intelligent monitoring. To achieve this, the method utilizes a Gaussian mixture model to establish a background model of the scene. The background model is used to estimate the static elements in the scene. By computing the background difference of the current image, a binary image of the foreground region is obtained. Additionally, data from the light sensor is incorporated to further segment and filter the foreground area, removing noise and irrelevant motion. The detection and tracking of human motion is realized through trajectory analysis and matching techniques. Experimental evaluation confirms the effectiveness and accuracy of the proposed method. The results demonstrate that the method achieves high accuracy and robustness in human motion image detection and tracking. Compared to traditional methods, this approach significantly improves the accuracy of recognizing human body boundaries and tracking motion. [ABSTRACT FROM AUTHOR]

With the development of wearable device technology, light sensor has been applied in the field of fitness, but in the aerobics teaching in colleges and universities, the use of light sensor technology for motion capture research is still limited. In order to monitor the aerobic exercise process of the students in real time, the experiment converts the movement into the corresponding data information through the sensor, and then the computer is combined with the projector or camera equipment for visual simulation. Therefore, this paper aims to design and develop a wearable device-based light sensor motion capture system for calisthenics teaching in colleges and universities. The research uses light sensor technology to monitor students' movements in real time by integrating light sensor devices into their wearable devices. Sensors collect data about body posture, range of motion, and speed, and transmit it to a virtual system for processing and analysis. Through the analysis of experimental data, it is found that the motion capture system based on light sensor has high accuracy and real-time in the aerobics teaching in colleges and universities. Students can get real-time feedback on posture, amplitude and speed to help them better master the technique of aerobics. [ABSTRACT FROM AUTHOR]

Sensor-related indoor localization has attracted considerable attention in recent years. The accuracy of conventional fingerprint solutions based on a single sensor, such as a Wi-Fi sensor, is affected by multipath interferences from other electronic devices that are produced as a result of complex indoor environments. Light sensors and magnetic (i.e., geomagnetic) field sensors can be used to enhance the accuracy of a system since they are less vulnerable to disturbances. In this paper, we propose a deep feedforward (DFF)-neural-network-based method, termed DFF-WGL, which integrates the data from the embedded Wi-Fi sensor, geomagnetic field sensor, and light sensor (WGL) in a smart device to localize the device in an indoor environment. DFF-WGL does not require complex and expensive auxiliary equipment, except for basic fluorescent lamps and low-density Wi-Fi signal coverage, conditions that are easily satisfied in modern offices or educational buildings. The proposed system was implemented on a commercial off-the-shelf android device, and performance was evaluated through an experimental analysis conducted in two different indoor testbeds, one measuring 60.5 m2 and the other measuring 38 m2, with 242 and 60 reference points, respectively. The results indicate that the model prediction with an input consisting of the combination of light, a magnetic field sensor, and two Wi-Fi RSS signals achieved mean localization errors of 0.01 m and 0.04 m in the two testbeds, respectively, compared with any subset of combination of sensors, verifying the effectiveness of the proposed DFF-WGL method. [ABSTRACT FROM AUTHOR]

In our daily lives, we engage in a variety of tasks that rely on our senses, such as seeing. Blindness is the absence of the sense of vision. According to the World Health Organization, 2.2 billion people worldwide suffer from various forms of vision impairment. Unfortunately, blind people face a variety of indoor and outdoor challenges on a daily basis, limiting their mobility and preventing them from engaging in other activities. Blind people are very vulnerable to a variety of hazards, including falls. Various barriers, such as stairs, can cause a fall. The Internet of Things (IoT) is used to track falls and send a warning message to the blind caretakers. One of the gaps in the previous works is that they were unable to differentiate between falls true and false. Treating false falls as true falls results in many false alarms being sent to the blind caretakers and thus, they may reject the IoT system. As a means of bridging this chasm, this paper proposes an intelligent shoe that is able to precisely distinguish between false and true falls based on three sensors, namely, the load scale sensor, the light sensor, and the Flex sensor. The proposed IoT system is tested in an indoor environment for various scenarios of falls using four models of machine learning. The results from our system showed an accuracy of 0.96%. Compared to the state-of-the-art, our system is simpler and more accurate since it avoids sending false alarms to the blind caretakers. [ABSTRACT FROM AUTHOR]

The use of plastic bottles has become a significant environmental concern, and recycling them has become a priority. Small and medium-sized recycling companies must collect and categorize large volumes of plastic bottles and sell them to larger recycling firms, a process that is time-consuming, costly, and labor-intensive. This manual sorting process can pose health risks, particularly during the COVID-19 pandemic, and can affect worker productivity. To address these issues, this study proposes the development of an automated conveyor belt system that can rapidly and accurately separate plastic bottles by type. The system utilizes an opaque and transparent plastic bottle separation platform, which saves time, cost, and manpower. This system design provides recycling SMEs with a competitive advantage by serving as a practical application model and a prototype with an easy-to-use concept. Key tools employed in this research include product design development (PDD), Kansei engineering, manufacturing process design, controlling system, and fault tree analysis (FTA). The light sensors are critical components in the separation process, detecting the opacity or transparency of the bottles’ surfaces. The proposed prototype’s reliability will be assessed by FTA, which considers all potential failures. This study contributes to the body of knowledge surrounding the integration of conveyor systems and provides valuable information for businesses seeking to optimize their sorting processes. The guidelines developed in this study can serve as a starting point for further research on the integration of conveyors in waste sorting plants.

The utilization of solar energy has become increasingly popular due to its renewable and sustainable nature. However, one of the primary challenges in solar energy harvesting is the optimization of the amount of energy that can be captured from the sun. The implementation of solar trackers is an effective solution that enables the automatic adjustment of the solar panel's position to face the sun throughout the day. In this project, an Arduino-based solar tracker prototype was designed and implemented to optimize the solar energy harvesting process. The system employs Light-Dependent Resistors (LDRs) to detect sunlight intensity and a servo motor to adjust the position of the solar panel accordingly. The system was programmed using the Arduino programming language and was tested using a small-scale solar panel. The increasing demand for cost-effective and easy-to-install renewable energy systems has led to a growing interest in photovoltaic solar energy for residential use. To optimize energy production, a two-axis photovoltaic solar tracker that orients the solar panel toward the maximum solar radiation is proposed in this study. The use of Free Computer Aided Design (CAD) 0.15 for the prototype's design, combined with Arduino technology, provides an affordable solution for mounting the solar tracker on flat roofs and other horizontal building elements. The performance of the solar tracker was evaluated under various testing conditions, showcasing an enhanced level of accuracy and energy production when compared to traditional fixed systems. The prototype's successful demonstration represents a significant advancement in the field, providing a practical solution for small-scale and residential solar energy applications. This research prototype was developed and installed on the roof of the Electrical department of QUEST, Campus Larkana, and validated through simulation results. [ABSTRACT FROM AUTHOR]

Abstract Background Studying the anti-predatory behavior of mammals represents an important challenge, especially for fossorial small mammals that hide in burrows. In the Arctic, such behaviors are critical to the survival of lemmings considering that predation risks are high every summer. Because detailed information about how lemmings use burrows as hideouts is still lacking, we developed a 1.59 g photosensitive collar to record any event of a small mammal moving between a dark area (e.g., burrow) and a bright area (e.g., outside the burrow). Tests of how collars affected lemming behavior were conducted in captivity in Cambridge Bay, Nunavut, Canada, in November 2019 and field tests were conducted on Bylot Island, Nunavut, Canada, in August 2021. Results The device was made of two chemical batteries and a printed circuit board (PCB) equipped with a photosensor and a real-time clock that recorded amplitude transient thresholds of light (lux) continuously. In accordance with ethical use of such devices, we verified that no abnormal loss of body mass was observed in captive or free-ranging lemmings, and no difference in recapture rates were observed between those with and without a collar, though we could not test this for periods longer than 108 h. Measurements of light intensities revealed consistent patterns with high lux levels at mid-day and lowest during the night. Lemmings showed clearly defined behavioral patterns alternating between periods outside and inside burrows. Despite 24-h daylight in the middle of the summer, August nighttime (i.e., 11 PM to 4 AM) lux levels were insufficient for amplitude transient thresholds to be reached. Conclusion By taking advantage of the long periods of daylight in the Arctic, such technology is very promising as it sets new bases for passive recording of behavioral parameters and builds on the prospect of further miniaturization of batteries and PCBs.

Aging is a significant contributor to changes in sleep patterns, which has compounding consequences on cognitive health. A modifiable factor contributing to poor sleep is inadequate and/or mistimed light exposure. However, methods to reliably and continuously collect light levels long-term in the home, a necessity for informing clinical guidance, are not well established. We explored the feasibility and acceptability of remote deployment and the fidelity of long-term data collection for both light levels and sleep within participants' homes. The original TWLITE study utilized a whole-home tunable lighting system, while the current project is an observational study of the light environment already existing in the home. This was a longitudinal, observational, prospective pilot study involving light sensors remotely deployed in the homes of healthy adults (n = 16, mean age: 71.7 years, standard deviation: 5.0 years) who were co-enrolled in the existing Collaborative Aging (in Place) Research Using Technology (CART) sub-study within the Oregon Center for Aging and Technology (ORCATECH). For 12 weeks, light levels were recorded via light sensors (ActiWatch Spectrum), nightly sleep metrics were recorded via mattress-based sensors, and daily activity was recorded via wrist-based actigraphy. Feasibility and acceptability outcomes indicated that participants found the equipment easy to use and unobtrusive. This proof-of-concept, feasibility/acceptability study provides evidence that light sensors can be remotely deployed to assess relationships between light exposure and sleep among older adults, paving the way for measurement of light levels in future studies examining lighting interventions to improve sleep. [ABSTRACT FROM AUTHOR]

Although camera trapping has been effectively used for wildlife monitoring, its application to multihabitat insects (i.e., insects requiring terrestrial and aquatic ecosystems) is limited. Among such insects, perching dragonflies of the genus Sympetrum (darter dragonflies) are agroenvironmental indicators that substantially contribute to agricultural biodiversity. To examine whether custom-developed camera traps for perching dragonflies can be used to assess the relative population density of darter dragonflies, camera trapping, a line-transect survey of mature adult dragonflies, and a line-transect survey of exuviae were conducted for three years in rice paddy fields in Japan. The detection frequency of camera traps in autumn was significantly correlated with the density index of mature adults recorded during the transect surveys in the same season for both Sympetrum infuscatum and other darter species. In analyses of camera-detection frequency in autumn and exuviae in early summer, a significant correlation was observed between the camera-detection frequency of mature adults and the exuviae-density index in the following year for S. infuscatum; however, a similar correlation was not observed for other darter species. These results suggest that terrestrial camera trapping has the potential to be effective for monitoring the relative density of multihabitat users such as S. infuscatum, which shows frequent perching behavior and relatively short-distance dispersal. [ABSTRACT FROM AUTHOR]

In this work, a maxi dual axis solar tracker is proposed. This tracker is used to track the sun path within a day and during a year. The tracking system is composed of two parts: mechanical and electrical parts. The mechanical part is composed of panel carrier, panel carrier rotator according to horizontal/vertical axis, two actuators. The electrical part is composed of light sensor, microcontroller, relays. The light sensor receives an artificial light and sends a potential difference as an analog signal to microcontroller. The microcontroller converts the analog signal into a digital signal using ADC and sends it to relays. The relays activate the two actuators to orient the maxi solar PV into the artificial light with the purpose to produce maximum energy.

Phytochrome photoreceptors control plant growth, development, and the shade avoidance response that limits crop yield in high-density agricultural plantings. Cyanobacteriochromes (CBCRs) are distantly related photosensory proteins that control cyanobacterial metabolism and behavior in response to light. Photoreceptors in both families reversibly photoconvert between two photostates via photoisomerization of linear tetrapyrrole (bilin) chromophores. Spectroscopic and biochemical studies have demonstrated heterogeneity in both photostates, but the structural basis for such heterogeneity remains unclear. We report solution NMR structures for both photostates of the red/green CBCR NpR6012g4 from Nostoc punctiforme In addition to identifying structural changes accompanying photoconversion, these structures reveal structural heterogeneity for residues Trp655 and Asp657 in the red-absorbing NpR6012g4 dark state, yielding two distinct environments for the phycocyanobilin chromophore. We use site-directed mutagenesis and fluorescence and absorbance spectroscopy to assign an orange-absorbing population in the NpR6012g4 dark state to the minority configuration for Asp657. This population does not undergo full, productive photoconversion, as shown by time-resolved spectroscopy and absorption spectroscopy at cryogenic temperature. Our studies thus elucidate the spectral and photochemical consequences of structural heterogeneity in a member of the phytochrome superfamily, insights that should inform efforts to improve photochemical or fluorescence quantum yields in the phytochrome superfamily.

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Background: Studying the anti-predatory behavior of mammals represents an important challenge, especially for fossorial small mammals that hide in burrows. In the Arctic, such behaviors are critical to the survival of lemmings considering that predation risks are high every summer. Because detailed information about how lemmings use burrows as hideouts is still lacking, we developed a 1.59 g photosensitive collar to record any event of a small mammal moving between a dark area (e.g., burrow) and a bright area (e.g., outside the burrow). Tests of how collars affected lemming behavior were conducted in captivity in Cambridge Bay, Nunavut, Canada, in November 2019 and field tests were conducted on Bylot Island, Nunavut, Canada, in August 2021. Results: The device was made of two chemical batteries and a printed circuit board (PCB) equipped with a photosensor and a real-time clock that recorded amplitude transient thresholds of light (lux) continuously. In accordance with ethical use of such devices, we verified that no abnormal loss of body mass was observed in captive or free-ranging lemmings, and no difference in recapture rates were observed between those with and without a collar, though we could not test this for periods longer than 108 h. Measurements of light intensities revealed consistent patterns with high lux levels at mid-day and lowest during the night. Lemmings showed clearly defined behavioral patterns alternating between periods outside and inside burrows. Despite 24-h daylight in the middle of the summer, August nighttime (i.e., 11 PM to 4 AM) lux levels were insufficient for amplitude transient thresholds to be reached. Conclusion: By taking advantage of the long periods of daylight in the Arctic, such technology is very promising as it sets new bases for passive recording of behavioral parameters and builds on the prospect of further miniaturization of batteries and PCBs. [ABSTRACT FROM AUTHOR]

In this work, an energy-saving smart light controlling system has been proposed that can maintain the desired intensity of light in a room automatically. Unlike the conventional light controlling system, the proposed system splits a large room into several zones and analyzes the light intensity of each zone; hence, the controlling unit adjusts the light intensity to the desired level. The main controlling unit consists of a light sensor, a motion sensor, a relay with a driver unit, an LCD display, etc. for controlling light efficiently to reduce the power waste. The sensors measure the intensity of light, based on the standard light intensity data chart the controller units make a decision how many light bulbs are needed to be switched ON/OFF in a particular zone. Moreover, the system automatically switched-OFF all light bulbs when there is nobody in the room. Proteus design suite 8.0 is used to design and simulation of the proposed system. Moreover, the PCB layout is designed using ExpressPCB version 7.5.0. The proposed system is capable of minimizing the power loss by up to 44% in comparison to the conventional light management system.

In this report, we demonstrated an application of a thin film Barium Strontium Titanate (BST) as a light sensor integrated with an Android smartphone as a model of smart street lighting. BST thin films were fabricated using chemical solution deposition methods followed by spin coating with a variety of mole fractions. We assumed that changes in the lattice parameters of its tetragonal crystal structure caused by variations in the mole fraction result in different ions displacement characteristics that induce charges polarization in the crystal structure. We have confirmed that the BST thin film with mole fraction x = 0.500 was the best thin film for the light sensor in this prototype. Furthermore, it has been found that the smart street lighting gives ∼69.23 % power saving and lower power usage than a conventional street lighting. Additionally, this developed system has successfully reported the lamp status that is to be maintained to an Android phone of the maintainer by using a short message system. This self-reporting makes it easy for maintainer to identify broken lamps and to do repairs. Moreover, implementation of such features to the street lighting can reduce the operating cost.

This work reports on the synthesis of small molecular semiconductor 2-(1H-pyrrol-1-yl)-anthracene-9,10-dione (PAD) via wet chemical precipitation route method for its possible potential applications in sensors. Thin film characterization of the synthesized PAD is carried out by studying its surface morphology, bond dynamics, and optical properties. For studying sensing characteristics of the PAD, its 100 nm thick film is thermally deposited on pre-patterned silver (Ag) electrodes over glass substrate having ~45 µm inter-electrode gaps to prepare Ag/PAD/Ag sensor. The effects of humidity (%RH), temperature (T), and illumination of light (Ev) on the fabricated Ag/PAD/Ag sensor are studied by changing one of the three (%RH, T, and Ev) parameters at a time and measuring the corresponding variations in capacitance (C) and capacitive reactance (X) of the device. As C and X also depend on frequency, sensing properties of the Ag/PAD/Ag sensor are measured at two different frequencies (120 Hz and 1 kHz) to find the optimum sensitivity conditions. To investigate reproducibility and repeatability of Ag/PAD/Ag sensor, each measurement is taken several times and also hysteresis loops of %RH vs. C are plotted at 120 Hz and 1 kHz to find the percent errors in each cycle of measurements. The sensor is active to sense humidity, temperature, and illumination within a broad range, i.e., from 15–93%RH, 293–382 K, and 1500–20,000 lx, respectively. Other key parameters of the sensor i.e., the humidity response time (TRes) and recovery time (TRec), are measured, which are 5 and 7 s, respectively, whereas for light sensing the values of TRes and TRec are measured to be 3.8 and 2.6 s, respectively. The measured values of TRes and TRec for the fabricated Ag/PAD/Ag sensor are shorter and better as compared to those of previously reported for similar kind of small molecular based sensors. The sensing properties of Ag/PAD/Ag device exhibit the potential of PAD for humidity, temperature, and light sensing applications. [ABSTRACT FROM AUTHOR]

The cultivation of mushrooms is not a simple task for traditional mushroom farmers, because the productivity of the mushroom farm depends on the ability to regulate the environment surrounding the mushroom farm. In addition, another problem for traditional mushroom farmers is that they cannot grow various types of mushrooms related to marketing. This research presents a mobile application for assisting mushroom farmers to understand the growing situation. The proposed mobile application called the easy mushroom application is based on the Internet of things (IoT) concept. The easy mushroom has been designed to analyse the humidity and light intensity relationship at a specific time. The experimental results show that the Easy-Mushroom mobile application provides a relationship between light intensity, humidity, and tolerance humidity level of mushroom.

A GPS sensor is the main part of the system in vehicle tracking applications. However, a GPS sensor becomes the limitation of low-cost vehicle tracking applications because a GPS sensor comes with the running cost of our vehicle tracking system. To solve this problem, this paper presents an IoT based concept to track a vehicle without a GPS sensor. To evaluate the proposed concepts, a light sensor and a vibration sensor have been compared to show the real-time data. The proposed algorithm shows that the vibration sensor provides a high accuracy more than a light sensor.

Light sensors are widely used to monitor light intensities, for instance in medical applications, in agriculture or for conservation of art. Most of these sensors are electronic devices that record continuously but applications that only require information of integrated intensities, measured over a long time, could greatly benefit from an integrating dosimeter that does not require a power supply. In this work a wireless and quantitative light dosimeter is presented based on SrAl2O4:Eu2+,Sm3+, a phosphor that exhibits stable energy storage upon exposure to blue and ultraviolet light. It is shown that a forward electron transfer from europium to samarium can be induced under illumination with blue or ultraviolet light while the reverse electron transfer can be achieved by illuminating the phosphors with green to infrared light. This reverse transfer is accomplished through excitation of the divalent samarium and results in bright, green optically stimulated luminescence. The stable energy storage, in combination with the possibility for optical read‐out, makes SrAl2O4:Eu2+,Sm3+ ideally suited to be used as an integrating light dosimeter for monochromatic to broadband light, from the ultraviolet to the near infrared. To demonstrate this, a proof of concept dosimeter was developed in which this phosphor was successfully used to measure average daylight intensities. [ABSTRACT FROM AUTHOR]

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Smartphone sensors are gaining research interest due to continuous sensor upgrades, leading to more precise readings of these sensors. For this study, the light sensor of a smartphone was used in determining light transmittance during the phase inversion process of ultrafiltration polysulfone-membrane manufacturing. Membrane separation is one of the best available technologies when it comes to water and wastewater treatment. The purpose of this study was to correlate light transmittance, at certain demixing steps during phase inversion, with membrane porosity, pure water flux and cross-sectional SEM images. Results show close relation between light transmittance and the mentioned membrane properties.

Aging is a significant contributor to changes in sleep patterns, which has compounding consequences on cognitive health. A modifiable factor contributing to poor sleep is inadequate and/or mistimed light exposure. However, methods to reliably and continuously collect light levels long-term in the home, a necessity for informing clinical guidance, are not well established. We explored the feasibility and acceptability of remote deployment and the fidelity of long-term data collection for both light levels and sleep within participants’ homes. The original TWLITE study utilized a whole-home tunable lighting system, while the current project is an observational study of the light environment already existing in the home. This was a longitudinal, observational, prospective pilot study involving light sensors remotely deployed in the homes of healthy adults (n = 16, mean age: 71.7 years, standard deviation: 5.0 years) who were co-enrolled in the existing Collaborative Aging (in Place) Research Using Technology (CART) sub-study within the Oregon Center for Aging and Technology (ORCATECH). For 12 weeks, light levels were recorded via light sensors (ActiWatch Spectrum), nightly sleep metrics were recorded via mattress-based sensors, and daily activity was recorded via wrist-based actigraphy. Feasibility and acceptability outcomes indicated that participants found the equipment easy to use and unobtrusive. This proof-of-concept, feasibility/acceptability study provides evidence that light sensors can be remotely deployed to assess relationships between light exposure and sleep among older adults, paving the way for measurement of light levels in future studies examining lighting interventions to improve sleep.