Street Lighting System Research Articles

IoT Based Smart Traffic Management System using Image Processing and Automated Street Lighting System

Through the integration of image processing, IoT, and automatic street lighting, this study presents a novel solution to urban traffic management. Real-time traffic data, such as vehicle counts and congestion levels, are continuously collected by smart cameras positioned at strategic intersections. A central control unit receives this data and uses sophisticated algorithms to dynamically modify traffic signal timings. Additionally, by including sensors to identify surrounding cars and pedestrians, an automatic street lighting system improves sustainability. This system helps save energy and money by optimizing energy consumption through the ability to change lighting intensity levels as needed. In general, this Internet of Things (IoT)-based smart traffic management system improves efficiency and safety for both commuters and locals by addressing congestion and fostering sustainable urban development

Analisis Efektivitas Sistem Kendali Otomatis PJU Berbasis IoT Menggunakan Mikrokontroler ESP32 dengan Metode Regresi Linier

Public street lighting (PJU) is essential infrastructure for nighttime security. This research develops an automatic PJU control system based on IoT using light and motion sensors with an ESP32 microcontroller. The system allows for PJU lamp control via a website, providing high flexibility for users. The ESP32 microcontroller is connected to a PIR sensor to detect motion. When the sensor detects movement, the intensity of the PJU lamps is increased, and when no movement is detected, the light intensity is reduced to save energy. Users can control the PJU lamps from any internet-connected device. Testing results show an increase in energy efficiency, with an average power consumption reduction of 13.77 watts and an efficiency increase of 42.67%. An R-squared value of 0.629 indicates that the model is quite good at explaining the variability in power consumption data. This system can automatically turn on street lights and be monitored in real-time, And hopes to contribute to the development of smarter and more efficient street lighting systems.

An IoT-Based Smart Street Lighting System to Lower Energy Consumption

Smart Lighting System is an automated and intelligent lighting control system that can be deployed across multiple locations or in one location, utilizing various IoT connection protocols, devices, and sensors. The system is able to intelligently adjust to changes in ambient light conditions, traffic patterns, and pedestrian activity through the integration of Internet of Things (IoT) technologies. IoT-enabled sensors are installed in every street light, creating a network that connects to a central control unit. Using real-time data, this system dynamically modifies street light brightness to maximize energy efficiency and improve safety. It provides a simulation and optimization tool for street light placement, considering factors such as street length, light distance, and the number of lights ahead. This tool aids in visualizing the power consumption implications of different configurations, promoting efficient urban planning. Demonstrates the energy-saving potential of the proposed system. As the street light intervals and the number of lights ahead decreases, the optimal street light power significantly reduces, leading to substantial energy savings. The system's ability to dim or turn off lights during low-traffic or well-lit periods contributes to reduced operational costs and enhanced sustainability.

Harnessing Solar Energy for Sustainable Urban Street Lighting

Public street lighting plays an important role in enhancing safety and comfort in urban areas. However, the use of conventional energy for public street lighting significantly contributes to greenhouse gas emissions. This research aims to study the optimization of solar energy usage in public street lighting systems to reduce urban emissions. The methods used include energy efficiency analysis, case studies of solar energy-based public street lighting implementation, and environmental impact evaluation. The results of the study show that the application of solar energy technology in public street lighting can increase energy efficiency by up to 30% and reduce CO2 emissions by 25% compared to conventional systems. In the case study of public street lighting in the city of Binjai, the reduction in carbon emissions reached 99.96%. Additionally, this study also identifies key factors affecting the success of implementation, such as technical design, initial costs, and government policy support. Therefore, optimizing solar energy-based public street lighting not only has the potential to reduce negative environmental impacts but also supports sustainable urban development.

A comprehensive survey on an IoT-based smart public street lighting system application for smart cities

The swift advancement and updating of urban lighting systems, along with the incorporation of smart and Internet of Things (IoT) infrastructure, have opened up numerous opportunities for technological progress across various facets of life. This paper offers a comprehensive overview on the development of smart public street lighting infrastructure tailored for IoT applications in smart cities. Initially, the focus lies on transitioning from conventional lighting to Light-Emitting Diodes (LEDs) technology in street lighting. Complementing this transition, the incorporation of the wireless networked sensors and controllers ensures dynamic brightness control in operational zones, envisioning substantial energy savings. Furthermore, the notion characterizing smart cities denotes incorporating modern digital infrastructures to develop innovative functionalities and connect various application, following the IoT paradigm. The key findings from the proposed study have enhanced knowledge regarding smart public street lighting application. This system integrates smart poles equipped with LEDs lamps technology, smart sensors, communication network and monitoring unit, leveraging current technological advancements in IoT applications. The implementation of IoT-based smart public street lighting systems presents several challenges, including integrating diverse sensors and actuators ensuring robust device communication, secure data management, and effective system scaling and maintenance. Despite these challenges, this system significantly advances smart city infrastructure by enhancing energy efficiency, safety, and sustainability. However, addressing their high initial costs, data privacy and security concerns, and ongoing maintenance are crucial in future studies to realize their full potential in smart cities.

MOVEMENT-CONTROLLED STREET LIGHTING SYSTEM WITH MINIMAL POWER CONSUMPTION

Energy consumption in the public lighting system represents the largest part of the energy usage of a community, while the maintenance and operation of the system are a considerable expense for every city. This paper focuses on products and innovative components for street lighting, proposing a consumption-reducing solution based on an intelligent system for remote measurements and control with dimming technologies for high-intensity discharge (HID) lamps. The results indicate that considerable energy savings are achieved and the service life of the lamps is extended. A movement-controlled street light system is controlled according to the specific mode. The modes are controlled by two sensors, which are the light-dependent resistor (LDR) and the infrared (IR) sensor. This system can automatically turn on and off the lights according to traffic flow. It operates at night, and the focus is only on the one-way road at a junction. The street light will be on when there is at least one road user; otherwise, it will turn off. This design can save a great deal of energy compared to conventional street lights that keep a light throughout the night. Moreover, the maintenance cost can be reduced, and the lifespan of the system will increase. As a result, the system has been successfully designed and implemented as a model system.

The Influence of Commercial Activities and Tourism Activities on the Development of Public Facilities of the Simpang Barelang Boundar

This research aims to evaluate the influence of commercial activities and tourism activities on the development of public facilities at the Simpang Barelang Roundabout, a strategic area that connects several areas in the Batam region. The method used in this research is a quantitative method with a descriptive approach. Primary data was collected through surveys involving business actors, tourists and local communities. The survey was designed to identify their needs and perceptions of available public facilities. In addition, secondary data was obtained from local government reports and other related institutions.The analysis results show that commercial activities, which include trade, services and small industry, significantly influence the need for adequate infrastructure. The increase in the number of businesses around the Simpang Barelang roundabout encourages the government to provide facilities such as better roads, street lighting and adequate drainage systems. On the other hand, increasing tourism activities in this area also contribute to the development of public facilities. Tourists who visit, both domestic and international, expect adequate facilities such as a large parking area, tourist information center, cleaning facilities and recreation areas. This research concludes that synergy between commercial and tourism activities is very important in the planning and development of sustainable public facilities.

An Electronic Economic Controller for automatically adjusting the intensity of Solar-Powered LED Street Lightning Systems in rural areas

Using photovoltaic energy for street lighting systems is increasing rapidly in rural areas. An economic and smart controller design for automatic intensity control of LED-based street lights is the main challenge. In this work, an electronic-based controller is proposed for controlling the LED light intensity automatically, considering vehicle movement and atmospheric conditions. A HC-SR501 PIR sensor is used for detection of vehicle movements and to assist the controller in making decisions regarding the brightness of the LED. The proposed LED is operated at three different energy levels, such as 0 W, 10 W, and 30 W. In the daytime, the load will remain off, and at night, the LED will operate at two power levels, 33% and 100%, based on the vehicle occupancy rate. In addition, the proposed controller will enhance the battery lifetime. Furthermore, the proposed work ensures significant savings in energy and operating costs and also favors environmental responsibility. GUB JOURNAL OF SCIENCE AND ENGINEERING, Vol 9(1), 2022 P 58-65

A study of the impact of traffic investment on traffic fatalities in China, 2004–2020

PurposeRoad traffic injuries (RTIs) have been one of the most serious public health problems in China. The purpose of this study was to investigate the extent to which traffic investment affects traffic fatalities in China as well as regional differences. MethodsThe study analyzed the correlation between traffic investment and traffic fatalities, incorporating additional factors such as economic conditions, road infrastructure, population density, and lighting. The selected variables included the number of traffic fatalities, traffic investment, urban per capita road area, urban road length, road mileage, urban road lighting, population size, and per capita gross domestic product. Relevant data between 2004 and 2020 were collected for an analysis using a fixed effect regression model. A p < 0.05 is considered statistically significant. To reduce the heterogeneity caused by regional differences, the provinces were divided into 6 groups according to administrative districts, and the clustering standard error analysis was carried out. ResultsOverall, there has been a significant improvement in road safety in China from 2004 to 2020, but some regions show an increase in traffic fatalities. The model reveals that traffic investment is significantly and positively correlated with the number of traffic fatalities. Holding all other factors constant, each 10,000 yuan increase in transport investment was associated with an average increase of 0.22 road traffic fatalities. In the analysis of regional differences, there was a significant positive correlation between traffic investment and traffic fatalities in the Northwest region and an increase of 10,000 yuan leads to an increase of 0.47. There was a significant negative correlation between road mileage, urban road lighting system, and population and traffic fatalities. For example, holding other factors constant, a 10,000 km reduction in road length would increase the number of traffic deaths by 45.56. The model results of urban per capita road area, urban road length, per capita gross domestic product, and the explained variables showed that p > 0.100, which was not statistically significant. ConclusionsTherefore, traffic investments are essential for governments to develop measures to enhance road safety and reduce the risk of road fatalities. Adjusting traffic road investment and other covariates is conducive to improving traffic safety and reducing the risk of road fatalities. The road safety situation in different regions of China varies greatly. Local governments should consider the actual conditions to provide better road safety configuration policies.

Development Of Trainer Learning Media Kit Solar Cell Public Road Lighting System in Electrical Light Installation

This research studies to develop instructors of electric lighting installation instructor media learns the feasibility of learning media for electrical installations trainers, learns the feasibility of worksheets for electric lighting installation learning media, and studies the effectiveness of learning media for electrical installations. Development (R&amp;D) using the ADDIE model (analysis, design, development, implementation, evaluation). By citing: (1) Analyzing (containing: analysis of design and needs, analysis of learning, analysis of students and obtaining difficulties there is no learning media for electrical installations), (2) Design (includes: large component trainers of electric contents, electricity, and trainer design), (3) Development (including making learning media broadcast by media experts and material experts), (4) Implementation (including conducted in class XI TL 2 SMK Negeri 2 Kota Serang starting with a pretest to find out where to find students IPL and then apply the learning media that has been developed) and (5) Evaluation (provided: done by providing a post-test to determine the effectiveness of the media that has been made). Based on the results of research that has been done, obtained data on the feasibility of instructional media with an average score of 82 categories "Very Eligible" and a learning media worksheet with an average score of 78 in the category of "Very Eligible". Both of these learning media get a value of "Very Effective" for learning with an average n-gain calculation score of 0.76.

Energy Efficiency in Public Lighting Systems Friendly to the Environment and Protected Areas

Solid-state lighting technology, such as LED devices, is critical to improving energy efficiency in street lighting systems. In Ecuador, government policies have established the obligation to exclusively use LED systems starting in 2023, except in special projects. Ecuador, known for its vast biodiversity, protects its national parks, which are rich in flora, fauna and natural resources, through international institutions and agreements such as UNESCO, CBD and CITES. Although reducing electrical consumption usually measures energy efficiency, this article goes further. It considers aspects such as the correlated color temperature in the lighting design of protected areas, light pollution and the decrease in energy quality due to harmonic distortion. Measurements of the electromagnetic spectrum of the light sources were made in an area in the Galápagos National Park of Ecuador, revealing highly correlated color temperatures that can affect ecosystem cycles. In addition, the investigation detected levels of light pollution increasing the night sky brightness and a notable presence of harmonic distortion in the electrical grid. Using simulations to predict the behavior of these variables offers an efficient option to help preserve protected environments and the quality of energy supply while promoting energy savings.

Microcontroller Based Automatic Street Light Control by Using LDR &amp; 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

Intelligent Ambient Light-Controlled Street Lighting System for Power Optimization

Intelligent Ambient Light-Controlled Street Lighting System for Power Optimization

Experimental Study on Automated Controller of Street Light Management System using IoT

In order to ensure public safety and support nighttime activities, street lighting is crucial to the urban landscape, and this study starts by contextualizing its importance. It then goes on to analyze the shortcomings of the current street lighting systems, which are typified by their static control methods and poor environmental response.These shortcomings underscore the urgent need for a paradigm shift towards more intelligent and adaptive solutions. The core proposition of this project lies in the design and implementation of an advanced street light management system empowered by IoT technology. At its heart, the system comprises a sophisticated network of interconnected devices, including sensors, actuators, and a central control unit. These components collaborate synergistically to capture, analyze, and act upon real-time data gleaned from the surrounding environment. Through the application of cutting-edge data analytics and machine learning algorithms, the system autonomously adjusts lighting levels in accordance with fluctuating parameters such as ambient light levels, traffic density, weather conditions, and pedestrian activity. By dynamically optimizing energy usage while ensuring adequate illumination, the system not only enhances operational efficiency but also contributes to cost reduction and environmental sustainability. Moreover, the proposed system incorporates proactive maintenance features, enabling early fault detection and remote diagnostics. This capability minimizes downtime and enhances system reliability, thereby mitigating the operational challenges associated with traditional street lighting infrastructure. The project further explores the conceptual framework of IoT, elucidating its transformative potential in revolutionizing urban infrastructure management. By seamlessly integrating physical devices with digital intelligence, IoT facilitates the creation of interconnected ecosystems wherein data-driven decision-making and automation converge to drive unprecedented efficiency and innovation

Smart and Intelligent Weather Adaptive Street Lighting System Using IoT

In this paper, an Internet of Things (IoT)- based smart and intelligent weather-adaptive street lighting system containing an Arduino UNO, an ESP 8266, an LDR, a voltage sensor, a current sensor, a PIR, a relay, and a mobile or web application is designed and implemented. This project's primary goal is to create an intelligent and adaptable street lighting system that will guarantee constant lighting for rural residents. This project is to minimize the electricity losses, reduce the manpower used in manually switching on-off the street lights and &amp; energy cost. There are three primary parts to the system: An Arduino NANO, ESP 8266 is a Wi-Fi module for signal transfer and a smart phone that can operate web page servers. These days, consumers are searching for smart systems that require less maintenance and use less energy. This intelligent street light only turns on when needed, and it continues to run on its own subsequent evenings even in the absence of sunlight. Furthermore, an Arduino NANO was used to include a PIR sensor, which detects motion and turns on the lights to bright mode by turning on more lights. Taking those factors into account, these smart streetlights are equipped with an Internet of Things (IoT) powered adaptive system that can detect malfunctions and send message to parent system.

Design and Implementation on Industrial Automation with the help of Renewable Energy Sources

Abstract: In the quest for a sustainable future, we’ve identified that traditional street lighting consumes more electricity than necessary. To address this, we’ve conceptualized an energy-efficient street lighting system. Our prototype leverages a Light Detecting Resistor (LDR) to optimize power usage, paving the way for an eco-friendly world. Fire alarms are crucial for timely fire detection, safeguarding lives and property. Our simplified circuit design enhances reliability, forming an integral part of a comprehensive security system that relies on sensor technology for prompt fire detection. The demand for automation is surging in both industrial and domestic spheres. This paper aims to minimize manual intervention by introducing self-operating systems powered by renewable energy sources. We’re integrating solar technology and piezoelectric sensors to harness electricity. This approach not only fuels industrial automation but also contributes to the global shift from finite conventional energy to renewable sources. By employing sensors, we ensure safety and efficiency in industrial zones while generating clean energy.

Smart Streetlight Energy Saving System Based on mmWave Radar

Streetlights serve as fundamental infrastructure to meet the lighting needs of people on every road. However, their extensive deployment often results in unnecessary energy waste, with many streetlights maintaining high brightness despite minimal usage during the night. This study aims to develop a smart energy-efficient streetlight system that automatically adjusts lighting levels based on the absence of vehicles and pedestrians, detected after a 3-minute countdown. Specifically, the study utilizes mmWave radar to collect point cloud data, which undergoes denoising through Doppler, DBSCAN, and XYZ techniques. Additionally, the mmWave radar assists in training an LSTM model to identify pedestrian pathways. The implementation of the proposed system significantly reduces energy consumption and annual costs by automatically dimming or turning off streetlights in areas with minimal pedestrian activity during nighttime.

Solar Powered Street Light with Sensor and Auto Intensity Control

The goal of this work is to predict solar panel power output by utilizing machine learning techniques, such as neural networks and regression, and by examining variables such as panel orientation, temperature, and sun irradiation. Models with high forecast accuracy help with grid integration and solar energy management. The article also outlines an innovative LED street light system that runs on solar power and uses Internet of Things (IoT) technology for intelligent control. By adjusting brightness in response to motion detection and current conditions, the device improves both urban safety and energy economy. For continuous operation, it runs on a backup battery, encouraging intelligent and sustainable street lighting

Optimizing the Energy Efficiency of a Lighting Network using Graph Theory

In this paper, we discuss how to make electric street lighting systems more energy efficient by creating an algorithm and mathematical model for optimizing parameters, minimizing active power losses, and finding the best topology for the lighting network when it is being designed or updated. Scientific and technological progress has led to an increase in the complexity of every human being's daily life. Companies, institutions, and countries constantly need to find modern tools to help them make the best decisions. Graph theory has numerous applications to many everyday problems. It can resolve and simplify them. An algorithm was developed to determine the shortest length in the form of a modified Dijkstra graph, with nodes supporting the street lights and ribs being the wires connecting them.

Enterprise Architecture for Efficient Integration of IoT Lighting System in Smart City Framework

This research investigates the influence of enterprise architecture design in integrating Internet of Things (IoT)-based street lighting systems into an innovative city framework, emphasizing the importance of efficient lighting infrastructure as a fundamental component of a creative urban ecosystem. With a focus on building an architectural model that supports the integration of IoT street lighting with other components of a smart city, this research addresses the knowledge gap in optimizing enterprise architecture design for integration efficiency, considering technological complexity and interoperability needs between systems. The methodology applied involved an in-depth analysis of the architectural components essential to facilitate the integration of IoT-based street lighting within the more extensive intelligent city infrastructure. The findings of this study show that a well-structured enterprise architecture model can significantly improve operational efficiency, reduce energy consumption, and provide a rich source of data for strategic decision-making regarding the management and maintenance of city infrastructure. Furthermore, these results emphasize the importance of an adaptive and unified architecture design, which not only improves the functionality of the lighting system but also strengthens the synergy between IoT technologies and innovative city operations. These discoveries have a wide range of repercussions and implications, offering new insights into designing enterprise architectures that can support the transition to more efficient and sustainable smart cities, thereby improving the quality of service for citizens.