Light Control Research Articles

Advanced Traffic Light Controller using FPGA and ARDUINO

This study presents a novel approach to develop a traffic light controller using FPGA and Arduino platforms. The objective is to design a robust, adaptable, and efficient traffic management system. Methodology involves hardware integration of FPGA for real-time processing and Arduino for interfacing with sensors and actuators. The proposed system utilizes FPGA's parallel processing capabilities for rapid decision-making and Arduino's flexibility for sensor data acquisition and actuator control. Performance evaluation includes simulation and real-world testing to assess reliability, response time, and scalability. Results demonstrate the effectiveness of the proposed controller in optimizing traffic flow and improving intersection safety.

Intelligent Light Emitting Diode Flashing Supplementary Lighting Control Design and Its Big Data Illumination Analysis

Considering the inherent advantages of the Light Emitting Diode (LED) in the field of illumination, this work designs an intelligent supplementary lighting system using LED as the light source. Combining microcontroller and electronic circuit theory, the circuit is built with the microcontroller PIC16F873 as the core control chip. The system utilizes an external 220 V AC-20 V DC conversion power supply, hence operating on a 20 V DC power source. The system consists of four hardware parts: the onboard power supply uses TI-produced TPS54331 as the control chip to achieve voltage conversion; the external signals (flashing and burst flashing signals) are isolated from the microcontroller through an optocoupler circuit; the PWM pulses output from the microcontroller’s RC1/CCP2 pins drive the corresponding switching tubes to achieve the flashing function; the flashing synchronization signal is output externally after optocoupler isolation, and its synchronous output with the flashing signal is achieved through an optocoupler after LED conduction; the circuit is established using TI-produced differential bus transceiver SN65LBC184D to convert the external 485 differential signal to the level signal required by the microcontroller. In the experiment, after completing the hardware design, connecting the LED panel, and debugging the test program, it is found that the designed lighting system has a good supplementary lighting effect. According to the PWM output waveform, the flashing effect meets the design expectations. The Hadoop big data computing platform is introduced. Simulation testing reveals that under no backlight conditions, the system achieves an illumination intensity of around 20 klx at a distance of about 10 meters. With backlight conditions, the system maintains an illumination intensity of around 1.5 klx at a distance of about 10 meters. Further calculations are performed to analyze the variation in foot traffic within the test area’s illumination over 24 hours. The total illumination intensity during different time intervals is compiled, confirming that the system can autonomously adjust the illumination intensity of the area based on changes in foot traffic.

Traffic Monitoring and Signal Controlling using RFID for Emegency Vehicles

Abstract: This paper presents the concept, Traffic Monitroting and signal controlling using RFID technology to prioritize ambulance passage during emergencies. Traffic lights are crucial for managing the flow of vehicles on the road. In particular, when there are emergencies, the traffic situation is getting worse. Emergency vehicles find it challenging to cross busy road during periods of traffic congestion. A medical emergency vehicles like ambulances, or victims of accidents must be transferred to it as soon as possible. They could be late for rescue efforts because of traffic signals. Identification of emergency vehicles, control of traffic lights, and provision of a clear path for their travel are the objectives of our paper. The main element of this system that implements the control system is radio frequency Identification (RFID). Through RFID detection, the system identifies the presence of an ambulance approaching any lane and promptly initiates a sequence wherein traffic lights for the ambulance's intended lane turn green, while simultaneously halting traffic flow in other lanes. By integrating RFID technology into the traffic management infrastructure, the prototype ensures swift and efficient response to emergency situations, minimizing delays in medical assistance. The system's intelligent algorithm enables it to override regular traffic light patterns, granting immediate passage to ambulances without compromising safety or causing disruptions to traffic flow in adjacent lanes. This approach enhances emergency response capabilities, optimizing the delivery of critical healthcare services and potentially saving lives in urgent medical situations. The system's ability to dynamically adapt traffic signals based on real time ambulance detection underscores its potential to revolutionize emergency response protocols, contributing to enhanced public safety and well-being in densely populated urban areas. The RFID tag helps to verify that emergency vehicles The emergency vehicle can clear all junctions without wasting time at the traffic signals this keeps happening until the ambulance arrives at its destination.

Implementation of Sensor based Energy Conservation System for College Library

Abstract: The lighting libraries and maintaining fans and lights need an extensive amount of energy in the majority of educational establishments. Nevertheless, this may lead to more expenses and wasteful energy use. We have created an improved lighting control system to solve this problem and reduce energy consumption during daylight and vacant hours. This system makes sure that the library's light connections and fans stay off while no students are present and turn on automatically when they do. For the purpose of managing the automated lighting system, we created an integrated module. The contrast of the library is determined as well with an LDR sensor

Microcontroller Based Automatic Street Light Control by Using LDR & IR Sensors

This project aims at designing and executing the advanced development in embedded systems for energy saving of street lights. Nowadays, human has become too busy, and is unable to find time even to switch the lights wherever not necessary. The present system is like, the street lights which will be switched on in the evening before the sun sets and they are switched off the next day morning after there is sufficient light on the roads. This paper gives the best solution for electrical power wastage. Also the manual operation of the lighting system is completely eliminated. In this the two sensors are used which are Light Dependent Resistor(LDR) sensor to indicate a day/night time and theIRsensors to detect the movement on the street. The microcontroller PIC16F877A is used as brain to control the street light system, where the programming language used for developing the software to the microcontroller is C-language. Finally, the system has been successfully designed and implemented as prototype system. Key Words: Embeded systems, Microcontroller, LDR ,IR, Lighting

Local Light Field Control Enables Efficient Quantum Dot Color Conversion Films for Mini‐LED Backlit Displays

AbstractQuantum dot (QD) color conversion films (QD‐CCFs) are used in ultrahigh definition (UHD) Mini‐LED backlit displays due to their narrow band emission and high color purity. However, their poor light conversion efficiency (LCE) leads to greater film thickness and thus high cost. Herein, this study proposes a local light field control strategy to enhance the LCE of QD‐CCFs using high‐refractive BN nanosheets. The LCEs of the green and red QD‐CCFs can increase from 29.9% and 34.8% to 67.4% and 91.0% after adding BN nanosheets, respectively. Combining the experimental data with the finite‐difference time domain (FDTD) simulations, the enhanced LCEs can be attributed to observably increased blue light absorption and improved light extraction efficiency of the light emitted from QDs. The white Mini‐LEDs, prepared by integrating the optimized QD‐CCFs containing BN nanosheets with blue Mini‐LED chips, show a high luminous efficiency of 70.2 lm W−1, a high external quantum efficiency of 36.2%, and a wide color gamut of 96.3% Rec. 2020 standards. This work provides an interesting idea for designing high‐efficiency QD‐CCFs toward low‐cost UHD Mini‐LED backlit displays.

A verified low-level implementation and visualization of the adaptive exterior light and speed control system

In this article, we present an approach to the ABZ 2020 case study that differs from those usually presented at ABZ: Rather than using a (correct-by-construction) approach following a formal method, we use C for a low-level implementation instead. We strictly adhere to test-driven development for validation, and only afterwards apply model checking using CBMC for verification. While the approach has several benefits compared to the more rigorous approaches, it also provides less mathematical clarity and overall less thorough verification. In consequence, our realization of the ABZ case study serves as a baseline reference for comparison, allowing to assess the benefit provided by the various formal modeling languages, methods and tools.

Optimal growth conditions to enhance Chlorella vulgaris biomass production in indoor phyto tank and quality assessment of feed and culture stock

Commercial microalgae cultivation is a dynamic field with ongoing efforts to improve efficiency, reduce costs, and explore new applications. We conducted a study to examine how different light exposure periods affect Chlorella vulgaris's growth. We employed a Phyto tank batch system of approximately 3.5 L with LED light control, controlled airflow, and sterilized bags, maintained at 22.0 ± 2.0 °C indoors. Various methods, including spectrophotometry, and cell counter were employed to monitor Chlorella vulgaris growth under different light exposure cycles. Additionally, quality analysis as feed source was employed by proximate, amino acid, beta-glucan, and microbial content analysis. The results revealed significant variations in C. vulgaris biomass production based on light exposure duration. Notably, the 16:8-h light-dark photoperiod exhibited the highest biomass concentration, reaching 6.48 × 107 ± 0.50 cells/mL with an optical density (OD) of 1.165 absorbance at 682 nm. The 12:12-h light-dark photoperiod produced the second-highest biomass concentration, with 2.305 × 106 ± 0.60 cells/mL at an OD of 0.489. Proximate analysis of dry algae powder revealed low lipid content (0.48 %), high protein content (37.61 %), variable ash concentration (average 10.75 %), and a significant carbohydrate fraction (51.16 %) during extended daylight and shorter dark periods. Amino acid analysis identified nine essential amino acids, with glutamic acid being the most abundant (17.7 %) and methionine the least (0.4 %). Furthermore, quality analysis and microbiological assays demonstrated that the C. vulgaris biomass is well-suited for fish and livestock use as a feed source and possibility as human nutraceuticals. These findings can be considered more environmentally friendly and ethically sound due to the absence of genetic modification.

Application Strategies of Automatic Addressable Single-Lamp Control Technology in Tunnel Lighting

The article mainly studies the application strategy of automatic addressable single-lamp control technology in tunnel lighting. It encompasses an introduction to this technology, an analysis of the tunnel lighting system using automatic addressable single-lamp control technology, and outlines the main development direction for this technology in modern tunnel lighting. The aim is to offer insights that can inform the rational deployment of this technology, thereby enhancing the lighting control effectiveness in modern tunnels and meeting their specific lighting requirements more effectively.

Flexible terahertz phase shifter for optically controlled polydimethylsiloxane-vanadium dioxide composite film

In the terahertz (THz) band, modulation research has become a focal point, with precise control of the phase shift of THz waves playing a pivotal role. In this study, we investigate the optical control of THz phase shift modulation in a polydimethylsiloxane (PDMS)-vanadium dioxide (VO2) flexible material using THz time-domain spectroscopy. Under the influence of an 808-nm continuous wave (CW) laser with power densities ranging from 0 to 2.74 W/cm2, the PDMS-VO2 flexible material exhibits significant phase shift modulation in the frequency range of 0.2 to 1.0 THz. The maximum optical-pumping phase shift reaches 0.27π rad at 1.0 THz in a composite material with a VO2 mass fraction of 5% and a thickness of 360 µm, and the amplitude transmittance from 0.2 THz to 1.0 THz exceeds 70%. Furthermore, the composite material exhibits good stability under at least 640 switching cycle times, as confirmed through repeatability tests. The proposed composite devices offer a new approach for more flexible phase shift modulation owing to the flexibility of the composite material and the non-contact and precise modulation of light control. Additionally, the stress-adjustable characteristics of flexible materials make them highly suitable for use in wearable THz modulators, highlighting their significant application potential.

Broadband wavelength designable achromatic grating based on a cholesteric liquid crystal template

Liquid crystal (LC) gratings have played important roles in light field control due to the advantages of being lightweight, low cost, having no moving parts, and low power consumption. However, the chromatic aberration limits the bandwidth of the LC device and affects the efficiency of the grating. To solve the chromatic aberration issue, a broadband wavelength designable achromatic grating is proposed. Different grating structures are integrated into a single-layer templated cholesteric liquid crystal (CLC) device, and the achromatic diffraction wavelength of the grating can be freely designed from the visible spectral region to the infrared range within the Bragg reflection band of the CLCs. The diffraction intensity of different orders can be changed with the electric field applied to meet the need for dynamic modulation. This grating shows suitable potential applications in optical communication and displays.

Light control ofthree-dimensional chromatin organization in soybean.

Higher-order chromatin structure is critical for regulation of gene expression. In plants, light profoundly affects the morphogenesis of emerging seedlings as well as global gene expression to ensure optimal adaptation to environmental conditions. However, the changes and functional significance of chromatin organization in response to light during seedling development are not well documented. We constructed Hi-C contact maps for the cotyledon, apical hook and hypocotyl of soybean subjected to dark and light conditions. The resulting high-resolution Hi-C contact maps identified chromosome territories, A/B compartments, A/B sub-compartments, TADs (Topologically Associated Domains) and chromatin loops in each organ. We observed increased chromatin compaction under light and we found that domains that switched from B sub-compartments in darkness to A sub-compartments under light contained genes that were activated during photomorphogenesis. At the local scale, we identified a group of TADs constructed by gene clusters consisting of different numbers of Small Auxin-Upregulated RNAs (SAURs), which exhibited strict co-expression in the hook and hypocotyl in response to light stimulation. In the hypocotyl, RNA polymerase II (RNAPII) regulated the transcription of a SAURs cluster under light via TAD condensation. Our results suggest that the 3D genome is involved in the regulation of light-related gene expression in a tissue-specific manner.

Photon-Dipole-Spin Interactions in M(TCNE)x/P(VDF-TrFE) Multiferroic Heterostructure Available for Bimodal Control of Multistate Data-Storage.

Organic multiferroic heterostructure is one of the most promising structures for the future design of high-density flexible energy-efficient data storage. Here, organic ferromagnetic metal(tetracyanoethylene) (M(TCNE))x/ferroelectric poly(vinylidene fluoride-co-trifluoroethylene) (P(VDF-TrFE)) multiferroic heterostructures are fabricated, where the excited state in M(TCNE)x interacted with localized dipole in P(VDF-TrFE) provides a key link for the interfacial coupling. Thus, aligned dipoles in P(VDF-TrFE) by external electric field can affect the magnetization of Fe(TCNE)x effectively to result in a pronounced magnetization-voltage (M-V) hysteresis loop. Moreover, light-induced electron-hole pairs in Fe(TCNE)x with long lifetime effectively interact with the dipoles in P(VDF-TrFE) to lead to an effect in external light control of electric polarization of P(VDF-TrFE). Overall, the organic multiferroic heterostructure provides the possibility of realizing two storage modes, light control of dipole as well as electric field control of spin, which can broaden multifunctional applications of organic multiferroic materials in the area of multistate storage.

Multi-Source Collaborative Control Technology of Photovoltaic Power Generation Based on Differential Evolution-Gray Wolf Optimization Algorithm

The existing photovoltaic power generation multi-source collaborative control technology cannot improve the control effect of microgrid, resulting in high peak load balancing cost of microgrid. Therefore, the photovoltaic power generation multi-source collaborative control technology based on differential evolution (DE)-gray wolf optimization (GWO) algorithm is adopted. The main components of the microgrid system, such as photovoltaic power generation equipment, hydroelectric power generation equipment, and battery pack, are modeled. With the goal of minimum peak cost and maximum transmission power, collaborative control of water, light and energy storage is carried out. The gray Wolf algorithm is used to solve the multi-objective problem of water and light storage in microgrid, and the gray Wolf algorithm is optimized by DE algorithm. Experiments show that the convergence speed of the optimized DEVOLU-Gray Wolf algorithm is obviously accelerated, and the problem of falling into the local optimal solution is completely avoided. After the application of this method, the photovoltaic, hydraulic, and battery of the microgrid run in order, ensure the smooth operation of the microgrid, and improve the economic benefit of the microgrid.

Improving traffic light systems using Deep Q-networks

As our cities become more complex and traffic demand grows, managing such traffic efficiently becomes challenging. Hence, solutions that allow building upon the current traffic light systems and that can be readily deployed are of global interest. In this work, we address the challenge of improving traffic light management at intersections. We propose an agent-based traffic light control system where an agent, one per intersection, dynamically regulates the light’s phase cycle depending on the current traffic conditions. To this end, we will rely on Deep Networks to adequately train agents to make good decisions. Simulation results in a realistic scenario using SUMO show that our proposed approach can significantly reduce waiting times, improving transit times by 44% compared to the standard fixed-timing method. Additionally, to assess the effectiveness and reliability of our control algorithm, we introduce new performance metrics.

Optimizing Ambiance: Intelligent RGB Lighting Control in Structures Using Fuzzy Logic

Managing red–green–blue (RGB) lighting conditions within structures may evoke emotions and positively influence behavior. Intelligent RGB lighting systems based on environmental data measurements can substantially enhance the perception of comfort. This study presents a challenge that requires a holistic and integrated approach to implement an automatic RGB artificial lighting control system that can be utilized in various structures and indoor environments. Initially, the challenge spans the identification of environmental variables directly impacting comfort up to the careful selection of suitable sensors. The result is the development of a sophisticated and autonomous system that can adjust RGB lighting in real time, creating environments that are both comfortable and energy-efficient. This automated system fosters the creation of appropriate atmospheres across different contexts. The identification and monitoring of environmental variables are achieved through a neuro-fuzzy control mechanism, where fuzzy rules and membership functions are defined based on late positive potential timings and the influence of artificial lighting on human emotions. The outcomes from this study are an interconnected system capable of performing both online and offline operations to enable the monitoring of environmental variables and the efficient management of artificial lighting based on these metrics. A pilot study, with reference to an EEG wave registry system, yielded significant results. These tests had a statistically relevant result with an average frequency of approximately 9.8 Hz, indicative of a state of comfort among people. Despite a 10% deviation margin, 87% of measurements during the test remained consistent. This research study contributes to human behavior by fostering a relaxing environment and enabling a reduction in energy consumption through the use of efficient lighting. Moreover, the environment intention enables the creation of stimuli in three emotional states: activation, relaxation, and neutral, allowing behavioral adaptation to an intention to occur automatically in fluctuating environmental conditions.

Harnessing Green Electricity from Food: A Split Black Gram-Based Triboelectric Nanogenerator for a Self-Powered Autonomous Lighting System and Portable Electronics.

Triboelectric nanogenerators (TENGs) represent a promising solution to mounting environmental concerns associated with battery disposal amid the escalating demand for portable electronics. However, prevailing TENG fabrication predominantly relies on nonbiodegradable, nonbiocompatible, and synthetic materials, posing a grave ecological threat. To mitigate this, there is a pressing need to develop eco-friendly and green TENGs leveraging sustainable, naturally occurring materials. This study pioneers the use of split black gram (SBG) as a tribo-positive material for TENGs. SBG's effectiveness as a tribo-positive material stems from its abundance of oxygen-containing functional groups, as confirmed by FTIR analysis, facilitating electron donation during the triboelectric process. SBG offers compelling advantages, including widespread availability, cost-effectiveness, biodegradability, and hydrophobic and adhesive properties due to its richness in starch and protein, positioning it as an optimal choice for eco-conscious TENG manufacturing. The fabrication process of an SBG-TENG is not only economical and facile but also solvent-free, requiring no specialized tools. Demonstrating commendable performance, the SBG-TENG achieves a maximum power density of 15.36 μW/cm2 at 1 MΩ, with an open circuit voltage of 84 V and short circuit current of 28 μA, comparable to recent studies. In practical applications, the SBG-TENG seamlessly integrates with LEDs and portable electronic devices via a full bridge rectifier, successfully powering them postcapacitor charging. Moreover, an autonomous lighting system is developed by embedding the SBG-TENG in a foot mat, enabling wireless light control through human stepping on the mat, introducing power-saving functionality for residential and office environments. In essence, the introduction of the SBG-TENG not only delivers cost-effectiveness but also minimizes the environmental impact by harnessing sustainable energy from food sources.

Investigation of an LED Strip Controller Based on a PWM Driver and a PIC Series Microcontroller

Investigation of an LED Strip Controller Based on a PWM Driver and a PIC Series Microcontroller

Photocurrent Ambipolar Behavior in Phase Junction of a Ga2O3 Porous Nanostructure for Solar-Blind Light Control Logic Devices.

Photoelectrochemical (PEC) devices are the most similar artificial devices to the nervous system, which is expected to solve the problem of complex computer/nervous system interface (solid-liquid interface) and multifunctional integration (photoelectric fusion) required in the post-Moore era. Based on the different photocurrent ambipolar behavior and different deep ultraviolet solar-blind spectral photoresponse characteristics of α-Ga2O3 and β-Ga2O3, we designed and constructed the Ga2O3 porous nanostructure PEC device with an adjustable photocurrent bipolar behavior through constructing an α/β phase junction core-shell structure by adjusting the thickness and the surface state of the shell layer. The switching point of the α/β-Ga2O3 ambipolar photocurrent shifts toward negative values with the increase of β-Ga2O3 shell layer thicknesses, and adjustable Boolean logic gates are prepared using the voltage as the input source with a high accuracy manipulated by solar-blind deep ultraviolet light. The controllable solar-blind logic gates based on the ambipolar photocurrent behavior of α/β-Ga2O3 presented in this study offer a new path for the photoelectric device multifunctional integration needed in the post-Moore era, which can be used in the creation of Ga2O3 half adders and full adders, as well as in the construction of four-input OR gates.

Intelligent adaptive lighting algorithm: Integrating reinforcement learning and fuzzy logic for personalized interior lighting

The lighting requirements are subjective and one light setting cannot work for all. However, there is little work on developing smart lighting algorithms that can adapt to user preferences. To address this gap, this paper uses fuzzy logic and reinforcement learning to develop an adaptive lighting algorithm. In particular, we develop a baseline fuzzy inference system (FIS) using the domain knowledge, generating light recommendation based on a set of intuitive rules. These rules, derived from existing literature, are based on environmental conditions i.e. daily glare index, and user information including age, activity, and chronotype. Through a feedback mechanism, the user interacts with the algorithm, correcting the algorithm output to their preferences. We interpret these corrections as rewards to a Q-learning algorithm, which tunes the FIS parameters online to match the user preferences. The Q-learning is a model-free learning algorithm that learns to act optimally by interacting with the user and the rewards it receives. This allows the proposed algorithm to work in a model-free manner, effectively handling the uncertainties that might arise from the individualistic preferences of users. To the authors’ best knowledge, this algorithm is pioneering work in designing intelligent algorithms for personalized lighting control, featuring several elements of novelty, including the number of environmental and user-related inputs, the continuous control of light intensity as opposed to common on/off control, and the ability to learn user preferences. The algorithm is implemented in a real aircraft cabin and is evaluated in an extensive user study. The implementation results demonstrate that the developed algorithm possesses the capability to learn user preferences while successfully adapting to a wide range of environmental conditions and user characteristics. This underscores its viability as a potent solution for intelligent light management, featuring advanced learning capabilities.