Intelligent Lighting Research Articles

An Intelligent Lighting Control System for Urban Street Lamps Using Internet of Things

With the rapid development of the city, the city’s intelligent lighting control system has gradually replaced the traditional lighting control system. But at present, there are still some problems in urban street lamp lighting control, such as a low level of intelligence, a huge waste of electric energy, improper maintenance, and so on. Firstly, aiming at the problem of untimely detection of street lamp faults, this paper adds GIS technology to the intelligent lighting system and uses GIS to locate the faulty street lamp. To improve the accuracy of intelligent dimming, an improved intelligent dimming algorithm based on a support vector machine is proposed. To verify the effectiveness of the proposed algorithm, an intelligent lighting control system based on an improved algorithm and GIS technology is designed in this paper. It can control the street light switch in real-time and monitor the working condition of the street light in real-time. The performance of the improved system is verified by experiments. The experimental results show that the system achieves automatic dimming function through an improved dimming algorithm; the system can alarm and locate the fault lamp position quickly; the system can achieve a greater energy-saving effect.

A smart tablet-phone-based system using dynamic light modulation for highly sensitive colorimetric biosensing

Facile, efficient, and inexpensive biosensing systems are in high demand for biomedical test. In recent years, numerous smartphone-based biosensing systems have been developed to match demand for biomedical test in source-limited environment. However, application of these smartphone-based biosensing systems was limited because of performance gap between the smartphone-based systems and commercial plate readers. In this study, we have developed a smart tablet–phone-based colorimetric plate reader (STPCPR) with intelligent and dynamic light modulation for broad-range colorimetric assays. The STPCPR allows controllable modulation of exciting light in three different color channels that is lack in conventional smartphone-based system. Using optimized exciting modulation, the STPCPR shows higher sensitivities, lower detection limits, and broader detection ranges in test of pigments, proteins, and cells when compared to conventional plate readers and smartphone-based system. Therefore, the developed STPCPR can serve as an ideal next-generation smartphone-based biosensing system for point-of-care colorimetric test in diverse biomedical applications in source-limited environment.

Sensing Lights: The Challenges of Transforming Street Lights into an Urban Intelligence Platform

ABSTRACT The technological transformation behind intelligent infrastructure systems requires institutional and stakeholder realignment in their development. In this article, we evaluate the challenges for the production of smart infrastructure through an in-depth analysis of the development of smart street lighting strategies. We conduct surveys and semi-structured interviews with key stakeholders and industry leaders in public illumination, as well with public officials from cities in three continents to understand the related challenges they face, the strategies being developed to meet those challenges, and reflect on the lessons provided for the design, creation, and operation of public smart infrastructure systems. We find that there are key barriers. First, differences in vision that reflect a lack of fit between operators of the current infrastructure and the new possibilities afforded by digital technologies. Second, lack of policies that would help facilitate the adoption of these new technologies particularly in regards to privacy and data operationalization. Third, difficulties in public engagement. These barriers to innovation hinder the capacity of cities to maximize the possibilities as well as the social value of intelligent street lights as a future-proof platform for urban knowledge and urban applications.

An intelligent lighting control system for individual visual comfort and energy savings in buildings

An intelligent lighting control system for individual visual comfort and energy savings in buildings

Intelligent Traffic Light via Policy-based Deep Reinforcement Learning

Intelligent traffic lights in smart cities can optimally reduce traffic congestion. In this study, we employ reinforcement learning to train the control agent of a traffic light on a simulator of urban mobility. As a difference from existing works, a policy-based deep reinforcement learning method, Proximal Policy Optimization (PPO), is utilized rather than value-based methods such as Deep Q Network (DQN) and Double DQN (DDQN). First, the obtained optimal policy from PPO is compared to those from DQN and DDQN. It is found that the policy from PPO performs better than the others. Next, instead of fixed-interval traffic light phases, we adopt light phases with variable time intervals, which result in a better policy to pass the traffic flow. Then, the effects of environment and action disturbances are studied to demonstrate that the learning-based controller is robust. Finally, we consider unbalanced traffic flows and find that an intelligent traffic light can perform moderately well for the unbalanced traffic scenarios, although it learns the optimal policy from the balanced traffic scenarios only.

Office intelligent lighting system based on the natural lighting and the ZigBee wireless network.

A comfortable and healthy lighting environment cannot only make people comfortable and improve work efficiency, but also avoid visual fatigue caused by the discomfortable lighting environment. In order to solve these problems, this paper proposes an intelligent lighting system that takes natural lighting and the occupancy situation as input and dimming factor K (0<K<1) as output. The linear function between illuminance of the working surface and natural lighting, the occupancy situation, illuminance components of adjacent luminaires, and dimming factor K is obtained through the control algorithm. The simplex method is one of the most commonly used and effective algorithms for solving linear programming problems, so the optimal dimming factor K of each luminaire is obtained. The intelligent lighting system uses the ZigBee tree network structure to transmit the dimming factor to each lamp, making the office lighting environment reach the target value. Opnet is used as a network simulation software to verify system information, such as delay, throughput, and load. The results show that the network transmission delay is only 0.011 s, and the load and throughput are both above 3.0×104bits/s. As an optical software, DIAlux simulates the lighting environment under the control system in two modes: day and night. The results show that the illuminance of the occupied working surface under the system reaches 500l×, and the illuminance of the unoccupied working surface reaches 300l×. The uniformity of illuminance is greater than 0.7. In the day mode, the uniformity of illuminance is improved compared to without any control system. Finally, the energy-saving efficiency of the control system reached 34% and 25% during the day and night, respectively.

Optimization of Road Traffic Using Intelligent Traffic Light Systems

If we consider road traffic in urban areas, one of its major problems encountered nowadays is that of traffic congestion. The paper aims to provide an improvement, in terms of reducing traffic congestion, by analyzing different traffic light cycles. A traffic light cycle is determined by the red and green duration of the traffic lights. Traditionally these two have a fixed duration and controlling road traffic can be achieved by modifying it, resulting in a congestion reduction. We present a comparison between the fixed and an improved fixed situation, as well as a QL algorithm to further reduce the congestion at an intersection. Urban traffic can thus be optimized, in terms of reducing congestion, on an existing traffic light system. A study case validates the results, based on road traffic data obtained from the city of Bucharest.

Traffic Safety Improvement via Optimizing Light Environment in Highway Tunnels

Driving in tunnel areas depends more heavily on light conditions than that on open roadways. Traditional lighting systems in highway tunnels adjust lighting parameters only caring about outside light luminance, and focus is usually on energy conservation; however, little concern is about drivers’ actual physical and psychological needs. How to leverage the enormous research progress of traffic safety, light environment, human factors engineering, and modern lighting sources to create an ideal tunnel light environment that aids with ensuring driving safety and lower interference effects caused by the change of light environment will greatly improve safety level and reduce adverse influence on drivers’ visual health in a tunnel area. An intelligent lighting control system designed with multiple influence factors are systematically considered. Based on sensor data from outside natural light conditions, target lighting parameters are determined per each lighting zone requires; then, lighting commands will be transferred and parsed by adaptive lighting controllers and modules, eventually LED lighting properties are altered step by step. This system helps a lot with optimizing tunnel lighting quality and improving drivers’ visual performance; as a result, it contributes to lower the fluctuation of drivers’ workload and get a smooth traffic flow, and ultimately this technically ensures physical and mental health of drivers in a tunnel area.

Intelligent Traffic Light Control System with Priority Lane Intervention

The current traffic light system uses a lot of fixed time signals. Fixed time signals cause traffic jams in one or several lanes due to traffic congestion. On the other hand, emergency vehicles cannot get their rights to the maximum due to the density of these vehicles. This study aims to build an intelligent traffic light with a vehicle density sensor device and a smartphone application to increase the accuracy of light timing and parse traffic density. Furthermore, in an emergency, they can still overcome and accelerate the speed of passing vehicles by manually intervening with the traffic light through a smartphone application connected wirelessly to the traffic light. The intelligent traffic light is made with Arduino Bluetooth Control (ABC), Bluetooth HC-05, Arduino Mega 2560, and infrared (IR) sensor E18-D80NK. The results show that the green light setting is based on the input from the IR sensor both near sensor (NS) and far sensor (FS) work well. When NS detects a vehicle with a green light, it increases Y seconds from the default X seconds. If FS detects a vehicle with a green light, it increases by Z seconds. Settings with the ABC application can randomly turn on the green light in four lanes according to the will of the smartphone operator.

Automatic Tunnel Lighting System for Road Traffic with Auto Exhaust Fan

Abstract: The main objective of this project work is to provide intelligent lighting scheme for the tunnels of hill station roads. Tunnel means tubular passage cut through the hill or underground, these tunnels remain in dark always and inside the tunnels proper lighting system are essential to avoid the accidents. In this regard our government is arranging lights and they are glowing continuously irrespective of traffic and lot of energy is wasted. To avoid energy losses at these places, this efficient and intelligent lighting scheme is developed, which works automatically depending up on the road traffic and minimizes the energy consumption. In addition, all the vehicles release the waste (exhaust) gases that may be stagnated in the tunnel, due to lack of circulation with the outside environment. So, a gas detector/sensor is used for sensing these exhaust gases released from the automobiles and pump them outside the tunnel through an exhaust fan automatically. The process begins from the sensors; optical sensors are used for sensing the vehicles and depending up on the traffic density, inside lights of tunnel are controlled automatically. For example, many vehicles entered in to the tunnel from both the sides, all the lights are energized and as the traffic moving forward depending up on the clearance, required lights are energized, during the clearance means no vehicle is inside, all the lights remain in off condition automatically. The system is designed with Microcontroller, four sets of Infra Red sensors are used and they can be arranged either side of the tunnel in by directional mode. All the sensors are interfaced with Microcontroller and the program is prepared such that, depending up on the interrupted signals obtained from the sensors. The sensor used in the project work can detect all types of petroleum gases; in addition, it can detect smoke also. The sensor interfaced with the controller can energize exhaust fan automatically when it detects any type of gas or smoke.

Digital Twin-driven approach to improving energy efficiency of indoor lighting based on computer vision and dynamic BIM

Intelligent lighting systems and surveillance systems have become an important part of intelligent buildings. However, the current intelligent lighting system generally adopts independent sensor control and does not perform multi-source heterogeneous data fusion with other digital systems. This paper fully considers the linkage between the lighting system and the surveillance system and proposes a digital twin lighting (DTL) system that mainly consists of three parts. Firstly, a visualized operation and maintenance (VO&M) platform for a DTL system was established based on dynamic BIM. Secondly, the environment perception, key-frame similarity judgment, and multi-channel key-frame cut and merge mechanism were utilized to preprocess the video stream of the surveillance system in real-time. Lastly, pedestrians detected using YOLOv4 and the ambient brightness perceived by the environment perception mechanism were transmitted to the cloud database and were continuously read by the VO&M platform. The intent here was to aid timely adaptive adjustment of the digital twin and realistic lighting through the internet. The effectiveness of the proposed method was verified by experimenting with a surveillance video stream for 14 days. The key results of the experiments are as follows: (1) the accuracy rate of intelligent decision control reached 95.15%; (2) energy consumption and electricity costs were reduced by approximately 79%; and (3) the hardware cost and energy consumption of detection equipment and the time and cost of operation and maintenance (O&M) were greatly reduced.

Eğitim Kurumu Binalarında Akıllı Aydınlatma Kontrol Sistemleriyle Gün Işığını Yönlendiren Sistemlerin İncelenmesi

In this study, intelligent lighting control systems and daylight directing systems within the framework of methods that maximize daylight in educational institution buildings were examined. The effective use of innovative, advanced daylight and intelligent lighting systems that improve the use of daylight in its function in lighting has been explained. In this context, motods that maximize the effective use of daylight by using intelligent lighting control systems in sustainable educational institution buildings have been examined in parallel with innovative and entrepreneurial perspectives. In this way, this study is aimed to provide a better understanding of intelligent lighting systems and to be a source to help determine the basic concepts and design criteria related to the systems. Key Words: Anidolic System, Prismatic Panel, Laser Cutting Panel, Holographic Optics

Eğitim Kurumu Binalarında Akıllı Aydınlatma Kontrol Sistemleriyle Gün Işığını Taşıyan Sistemlerin İncelenmesi

In this study, intelligent lighting control systems and daylight-carrying systems within the framework of methods that maximize daylight in educational institution buildings were examined. The purpose of these functions, known as intelligent lighting control systems, is to ensure the construction of sustainable educational institution buildings in the process that continues from the construction stage of educational institution buildings to the conduct of daily educational work. The main issues of attention in the buildings of this educational institution are intelligent lighting, high technology, daylight saving as much as possible, insulation and energy efficiency. In this way, intelligent lighting systems aim to minimize the installation load and usage times of energy-consuming systems of educational institution buildings and maximize the use of daylight without compromising the comfort conditions required by active users of buildings. Key Words: Heliostatic System, Lighting Guide, Lighting Tube, Fiber Optic

IoT BASED ENERGY EFFICIENCY and FAULT DETECTION SMART STREET LIGHT USING GSM

-Automation plays an increasingly very important role in the world economy and in daily life. Automatic systems are being preferred over any kind of manual system. We can also call it an “SMART STREET LIGHT SYSTEM”. Intelligent light sensing refers to public street lighting and traffic control that adapts to movement by pedestrians, cyclists and cars. Intelligent street lighting and traffic control, also referred to as adaptive street lighting, dims when no activity is detected, but brightens when movement is detected. This type of lighting is different from traditional, stationery and illumination, or dimmable street lighting that dims at predetermined times. The proposed work shows automatic control of streetlights and traffic light control as a result of which power is saved and can control traffic cognition to some extent. In the scope of industrialization, automation is a step beyond mechanization. Whereas mechanization provided human operators with machinery to assist the users with muscular requirements of work, automation greatly decreases the need for human sensory and mental requirements as well. Basically, street lighting is one of the important parts. Therefore, the street lamps are relatively simple but with the development of urbanization, the number of streets increases rapidly with high traffic density. Key Words: Arduino UNO, GSM, Power supply, LED, IR Sensor, LDR Sensor.

Integrated tripartite modules for intelligent traffic light system

&lt;span&gt;The traffic in urban areas is primarily controlled by traffic lights, contributing to the excessive, if not properly installed, long waiting times for vehicles. The condition is compounded by the increasing number of road accidents involving pedestrians in cities across the world. Thus, this work presents an integrated tripartite module for an intelligent traffic light system. This system has enough ingredients for success that can solve the above challenges. The proposed system has three modules: the intelligent visual monitoring module, intelligent traffic light control module, and the intelligent recommendation module for emergency vehicles. The monitor module is a visual module capable of identifying the conditions of traffic in the streets. The intelligent traffic light control module configures many intersections in a city to improve the flow of vehicles. Finally, the intelligent recommendation module for emergency vehicles offers an optimal path for emergency vehicles. The evaluation of the proposed system has been carried out in Al-Sader city/Bagdad/Iraq. The intelligent recommendation module for the emergency vehicles module shows that the optimization rate average for the optimal path was in range 67.13% to 92%, where the intelligent traffic light control module shows that the optimization ratio was in range 86% to 91.8%.&lt;/span&gt;

Intelligent Traffic Light Control by Exploring Strategies in an Optimised Space of Deep Q-Learning

Intelligent traffic light control is one of the modern approaches to solve traffic congestion, where reinforcement learning is a widely used method. Conventionally, reinforcement learning is used to determine whether to change the current phase (or choose a traffic phase) after each small interval. One major drawback of these approaches is that it makes the current traffic light phase duration uncertain before the current phase terminates. Directly determining the duration of the traffic light phase can effectively avoid this shortcoming. An adaptive traffic light timing system is proposed in this paper which can directly control the phase duration. In the proposed system, the Q-learning algorithm is employed and the action space is defined as all possible phase durations. In addition, the reward function is redefined to guide the agent to balance more traffic metrics, and the state is redefined to reduce the state space. Finally, the proposed system is evaluated by equal, unequal, and complex traffic scenarios. Results show that the proposed system has a better performance compared with other methods in controlling traffic lights, even on complex traffic scenarios.

STMARL: A Spatio-Temporal Multi-Agent Reinforcement Learning Approach for Cooperative Traffic Light Control

The development of intelligent traffic light control systems is essential for smart transportation management. While some efforts have been made to optimize the use of individual traffic lights in an isolated way, related studies have largely ignored the fact that the use of multi-intersection traffic lights is spatially influenced, as well as the temporal dependency of historical traffic status for current traffic light control. To that end, in this article, we propose a novel Spatio-Temporal Multi-Agent Reinforcement Learning (STMARL) framework for effectively capturing the spatio-temporal dependency of multiple related traffic lights and control these traffic lights in a coordinating way. Specifically, we first construct the traffic light adjacency graph based on the spatial structure among traffic lights. Then, historical traffic records will be integrated with current traffic status via Recurrent Neural Network structure. Moreover, based on the temporally-dependent traffic information, we design a Graph Neural Network based model to represent relationships among multiple traffic lights, and the decision for each traffic light will be made in a distributed way by the deep Q-learning method. Finally, the experimental results on both synthetic and real-world data have demonstrated the effectiveness of our STMARL framework, which also provides an insightful understanding of the influence mechanism among multi-intersection traffic lights.

Recent Progress in AC-Driven Organic and Perovskite Electroluminescent Devices

AC-driven EL devices have always been the focus of attention because of their great value in the field of intelligent lighting and multifunctional display. AC-driven EL devices based on various materials and optimization methods have been continuously developed. However, the important luminescent semiconductor materials have rarely been systematically studied. Herein, the development of efficient and stable organic and perovskite EL devices, including the optimization of light-emitting materials, and the device structures are comprehensively studied. The different frequency-dependent characteristics of AC-driven EL devices based on organic semiconductors and perovskite semiconductors are mainly introduced due to the discrepancy in the characteristics of the materials themselves. In addition, approaches to reduce the driving voltage and enhance the luminescence performance of AC-driven organic EL devices are also presented. For AC-driven perovskite EL devices, the bias voltage with frequent switching of the electric field direction can alleviate the thermal degradation and charge accumulation of the material to improve the stability of the devices and also effectively suppress the phenomenon of ion migration. The unique advantages of the AC driving mode in the realization of color tunable EL devices are revealed. The application potential and challenges of AC-driven EL devices are discussed.

To the Question of Updating the Educational Programs of the Light and Engineering Profile at Ogarev Mordovia State University Taking into Account Professional Standards

Light and engineering education in Russia is now bringing forward new priorities, which are reflected in the updated major professional educational programs both bachelor’s and master’s degree. The modern labour market in the field of light and engineering today requires the training of highly qualified specialists who possess modern information technologies, are technically literate, who know regulatory regulations and environmental requirements.This trend is observed not only in Russia, but also noted by European researchers. In the labour market, the most in demand are engineering and technical workers with knowledge of intelligent lighting control systems, the Internet of Things technologies, with ability to implement energy saving measures, as well as specialists who are able to develop and implement lighting design projects, both indoor and outdoor. The analysis of the major professional educational programs implemented in Ogarev Mordovia State University showed that the timely release of professional standards (PS) 29.013 and 29.014 allowed us to formulate professional competencies (PC) of graduates of the lighting profile, which are relevant today and will contribute to the successful career building of young professionals. Much attention is paid to the formation and development of digital competencies of specialists in the lighting industry when updating major professional educational programs. Disciplines that allow engineering and technical specialists to develop artistic and aesthetic skills and imaginative thinking are introduced. Students learn through a project-based approach, consider multi-variant solutions, getting acquainted with the current nomenclature and databases of lighting devices (LD) from various manufacturers. By creating projects, they not only learn to develop lighting installations (LI) in accordance with the regulatory quantitative and qualitative parameters, but also gain practical design skills, taking into account the visual light and colour comfort, style design. They learn to implement intelligent lighting control systems, design LD based on LED light sources. In order to further improve the educational process, it is necessary to involve more practitioners, to involve students in the implementation of real projects. Strengthening the interdisciplinary nature of graduate training, whose planned activities are related to the development of lighting design projects, requires the preparation of educational and methodological support.

Energy Conservation By Street Light Control

In day-to -day life, electricity use has been an area of concern worldwide. Most of the power stations are based on the fuels that are conventional with not having many non-renewable sources available. Solar and wind are the new and renewable power sources that we should proceed on to. As we should not run into the power shortage of electricity, effective use of the available conventional and non- renewable sources should be done. The essential part of day-to-day life is Street lights that consume large amounts of electricity. The large amount of power consumption takes place by the manual operated street lighting system as they work on the given condition of from evening to early morning and heavy installation cost play the role of great disadvantage as we are in one of the developing countries. By using on/off mechanism and targeted dimming we can reduce the power consumption by 35%. The overall consumption of the energy can be reduced by 42% by doing the proper maintenance of the system. The proposed approach is the utilization of energy in an effective way that controls the automatically operating street lights when there are vehicles on the road at the evening and night time. This system is flexible and consists of different types of sensors and a controller which makes it the intelligent street lighting system and thus overcomes disadvantage [1] Key Words: Energy Conservation, Street Lighting System, ON/OFF Mechanism, Sensors and a Controller Light Dependent Resistor (LDR), Infrared Sensor (IR). 1.INTRODUCTION Energy efficiency is the key factor while designing the street lighting system. To utilize the limited power resources efficiently, an energy efficient light system is needed which can manage the usage of energy efficiently. The old lighting standards and inefficient devices the traditional lighting system is not much more reliable as it results in energy losses, automation and fault problems. In the traditional street lighting system, all the street lights are switched on at the exact time in the evening and switched off early in the morning manually which is causing Human errors and excessive energy consumption. Introduction of Automation in the street lighting system can reduce energy consumption and eliminate human errors to a great extent. To overcome these challenges, the energy consumption efficiently is done by introducing a type of automation in this system. Type of sensors such as Light Dependent Resistor (LDR), Infrared sensors (IR), Relays, Arduino uno r3, LEDs are used in this Street lighting system.