Street Lighting Control System Research Articles

Metode Simple Additive Weighting (SAW) pada Pemilihan Jenis Lampu Penerang Jalan Berbasis Photovoltaic

The simple additive weighting method is a decision support system method for various decision selection problems. Many research topics use the SAW method as a reference method in a decision support system. The street lighting control system is very useful for residents of the village of Karanganyar, Paiton, Probolinggo. This lighting is the main spotlight for residents' activities at the village office. Such as August competitions, routine monthly recitations, competitions to commemorate Isra' Mi'raj and the Prophet's birthday. There are many types of lamps in stores. The criteria for lamps are that they have high light illumination, long-lasting light, large bulb size, so that they can help village residents carry out activities at night. This lamp also uses photovoltaic as an additional source of electrical energy so it can save electricity costs to PLN. The solar panel measures 550 x 360 x 25 mm, 20 volts and has a peak power of 20 watts

Intelligent Control of Solar LED Street Lamp Based on Adaptive Fuzzy PI Control

As road traffic develops, energy-saving and efficient street lights have become a key research field for relevant professionals. To reduce street lights energy consumption, a fireworks algorithm is used to optimize the membership function parameters of fuzzy control and the initial parameters of PI control. A fireworks algorithm improved adaptive fuzzy PI solar LED street light control system is designed. The results showed that in the calculation of Root-mean-square deviation and Mean absolute error, the Root-mean-square deviation of the adaptive fuzzy PI control system improved by the fireworks algorithm was 0.213, 0.258, 0.243, 0.220, and the Mean absolute error was 0.143, 0.152, 0.154, 0.139, respectively, which proved that the prediction accuracy was high and the stability was good. In the calculation of the 1-day power consumption of the solar LED intelligent control system, the average power consumption of the designed solar LED intelligent control system was about 2000W, which was 25.9%, 47.4%, and 42.9% lower than the other three control methods, respectively. This proves that its energy consumption is low, and its heat generation is low, and the battery service life is long. The research and design of an adaptive fuzzy PI control solar LED street light intelligent control system has good performance, which can effectively achieve intelligent management and energy conservation and emission reduction in smart cities.

Modern Smart Street Light Monitoring Systems

Abstract: This study highlights the importance of Modern Street light control systems over traditional ones, with LED lamps emerging as the most suitable choice due to their advantagessuch as reduced heat production, lower electricity consumption, and extended lifespan. The main goal is to enhance system efficiency by minimizing unnecessary electricity loss during daylight and when lighting is not required. Automating street lights using LDR and PIR sensorsin conjunction with Arduino Uno offers a costeffective and secure solution, eliminating the drawbacks of manual switching and simplifying cost reduction and maintenance. Additionally,applying a ZnO coating to the street light casings provides effective protection against dust and moisture, resulting in efficient lighting. The process involves sol-gel deposition of ZnO nanoparticles on silica glass substrates, followed by preannealing and repeated dip coating. Annealing at temperatures between 450°C and 600°C further improves the results. The uniformand defect-free coatings are confirmed by SEM images, while transmission spectra reveal over80% penetration of visible light (400 nm to 900 nm). Lower precursor concentrations lead to better penetration of light below 300 nm wavelength.

Research on a fuzzy algorithm for intelligent power-saving control of urban street lamps

Urbanisation has increased the demand for energy-efficient and environmentally friendly street lighting systems. However, traditional urban lighting uses time interval control and cannot be intelligently controlled according to the environment. Therefore, an intelligent urban street lighting control system based on advanced fuzzy control technology was developed. The system uses a fuzzy control algorithm based on ZigBee technology to study the street lighting system. The fuzzy control system determines input and output variables and obtains demand instructions for intelligent control of street lights through fuzzy operation. The number of node visits and node degree were optimised to complete the construction of the street lamp intelligent control system. Experimental simulations showed that the proposed scheme could reasonably control the brightness of the street lighting according to ambient light. At 5.00 p.m., the proposed scheme adjusts the street lighting to 80 W. The system is illuminated at the rated power, and the current power consumption is 100 W. A test was carried out under a street lighting system, and the proposed scheme dynamically adjusted the lighting brightness reasonably considering various factors such as light intensity, noise intensity and vehicle speed. The proposed street lamp fuzzy control algorithm has good control performance and significantly reduces the system energy consumption. The research has important reference value for energy saving and intelligent control of urban lighting.

Automatic Street Light Control System

Abstract: Automatic Street Light Control System is a simple yet powerful concept, which uses transistor as a switch. By using this system manual works are 100% removed. It automatically switches ON lights when the sunlight goes below the visible region of our eyes. This is done by a sensor called infrared sensor (IR) which senses the light actually like our eyes. It automatically switches OFF lights whenever the sunlight comes, visible to our eyes. By using this system energy consumption is also reduced because nowadays the manually operated street lights are not switched off even the sunlight comes and also switched on earlier before sunset. In this project, no need of manual operation like ON time and OFF time setting. This project clearly demonstrates the working of transistor in saturation region and cut-off region.

Automatic Street Light On and Off Using LDR

Abstract: Automatic Street Light Control System is a simple yet powerful concept, which uses transistor as a switch. By using this system manual works are 100% removed. It automatically switches ON lights when the sunlight goes below the visible region of our eyes. This is done by a sensor called Light Dependant Resistor (LDR) which senses the light actually like our eyes. It automatically switches OFF lights whenever the sunlight comes, visible to our eyes. By using this system energy consumption is also reduced because nowadays the manually operated street lights are not switched off even the sunlight comes and also switched on earlier before sunset. In this project, no need of manual operation like ON time and OFF time setting. This project clearly demonstrates the working of transistor in saturation region and cut-off region. The working of relay is also known.

AUTOMATED STREET LIGHT CONTROL AND MANHOLE MONITORING WITH FAULT DETECTION & REPORTING SYSTEM FOR MUNICIPAL DEPARTMENT

This project involves the design and implementation of an automated street light control system and an underground drainage monitoring system using GSM technology. Besides this, it can also check the status of the manhole lid. The system's low maintenance and low cost are some of its main advantages. This system can monitor the status of the street lights and manholes in real time. It can also notify the officials through a text message. KEYWORDS: ARDUINO, IOT, STREET LIGHT MANAGEMENT, MANHOLES MONITORING.

Design and Fabrication of Street Light Management and Control System

In India, most of the streets within the habitations are illuminated from evening until morning, averaging roughly 12 hours per day. Throughout the night, some streets may not have automobiles or even pedestrians travelling through them which results in power loss. In addition, the number of vehicles on the road is increasing every day, and traditional traffic management is still in use, road accidents are one of our country's key issues. Many important lives are lost as a result of these accidents, which occur when emergency assistance is unavailable. So, our proposed solution for this problem is that we are designing a model that first detects the traffic and examine then based on situation it controls the lightening system and send traffic intensity data to internet hour wise. For accident detection we used the SOS button to get help immediately and crewman get the exact location of accident. According to the results obtained from the proposed method, energy usage is greatly reduced, and we can receive a very quick alarm when something unpleasant occurs.

Street Light Control System

Abstract: Automatic Street light systems require less maintenance than traditional street lights because they do not have any moving parts. Because the autonomous street light system is self-contained, it does not require any external wiring or grid connection. When the sunlight falls below the visible region of our eyes, the lights in this Street Light Control System will automatically turn on, and when the sunshine returns, the lights will immediately turn off.There is no requirement for manual operation in this project, such as setting the ON and OFF times. This system uses a motion detection sensor which helps to automatically increase the intensity of the street light when a car or pedestrian is noticed in the area. If there is no activity in the area, the light is automatically changed to a minimum light level that is optimum.

Adaptive Control of Streetlights Using Deep Learning for the Optimization of Energy Consumption during Late Hours

This paper presents an adaptive control scheme for streetlights by optimizing the energy consumed using deep learning during late hours at night. A city’s infrastructure is not complete without a proper lightening system for streets and roads. The streetlight systems often consume up to 50% of the electricity utilized by the city. Due to this reason, it has a huge financial impact on the electricity generation of the city. Furthermore, continuous luminosity of the streetlights contributes to the environmental pollution as well. Economists and ecologists around the globe are working hard to reduce the global impact of continued utilization of streetlights at night. In regard to a developing country which is already struggling to produce enough electrical energy to fulfill its industry requirements, proposing a system to lessen the load of the energy utilization by the streetlights should be beneficial. Therefore, an innovative and novel energy efficient streetlight control system is presented based on embedded video processing. The proposed system uses deep learning for the optimization of energy consumption during the later hours. Conventional street lighting systems consume enormous amounts of electricity, even when there is no need for the light, i.e., during off-peak hours and late at night when there is reduced or no traffic on the roads. The proposed system was designed, and implemented and tested at two different sites in Karachi, Pakistan. The system is capable of detecting vehicles and pedestrians and is able to track their movements. The YOLOv5 deep-learning based algorithm was trained according to the local requirements and implemented on the NVIDIA standalone multimedia processing unit “Jetson Nano”. The output of the YOLOv5 is then used to control the intensity of the streetlights through intensity control unit. This intensity control unit also considers the area, object and time for the switching of streetlights. The experimental results are promising, and the proposed system significantly reduces the energy consumption of streetlights.

Smart Voice Controlled Farm House Automation, Plant Watering and Street Light Control System

Adopting an optimized irrigation system has become a necessity due to the lack of the world water resource. The system has a soil-moisture sensor. This project focuses on a smart irrigation system which is cost effective. Automation allows us to control various appliances automatically. The objective of this project is to control the water supply to each plant automatically depending on values of soil moisture sensors. Mechanism is done such that soil moisture sensor electrodes are inserted in soil. Automatic irrigation scheduling consistently has shown to be valuable in water use efficiency with respect to manual irrigation based on direct soil water measurements. The aim of the implementation is to demonstrate that the automatic irrigation can be used to reduce water use. The implementation is an automated irrigation system that consists of a soil moisture sensor which senses the soil humidity and automatically waters the field. Therefore, the object of this review study was to provide significant knowledge about early fault detection and diagnosis in aeroponics using intelligent techniques (wireless sensors). So, the farmer could monitor several paraments without using laboratory instruments, and the farmer could control the entire system remotely. Moreover, the technique also provides a wide range of information which could be essential for plant researchers and provides a greater understanding of how the key parameters of aeroponics correlate with plant growth in the system.

Smarter and Safer City Using Internet of Things

Internet of Things (IoT) can make a significant contribution in making cities greener, more secure, and more viable. This paper proposes 4 subsystems that help make cities smarter. First is a Smart Super Market, which enables customers to acquire product information with smart storage details and also makes the checkout process hassle-free. A waste collection system, in light of offering intelligence to garbage canisters, using IoT is also introduced. A Smart Streetlight and Traffic Signals Control System is presented which has two parts. The first part automates streetlight control using sensors that detect daylighting and other weather conditions. The second part presents traffic signals controlled by sensing the real-time congestion on the roads. A Women Safety System which helps women feel safer by notifying the local authorities in alarming situations is also introduced.

Intelligent Street Light Control System Based on Fuzzy Control Technology

Aiming at the problem of low intelligence and single control mode of traditional street lights in the city, which causes serious power waste, we design an intelligent street light control system based on fuzzy control technology, use fuzzy control algorithm to control the street light system, design the light fuzzy controller and vehicle speed fuzzy controller respectively, and conduct simulation experiments by Matlab software. The experiments show that the system has a good effect of saving electric energy, and to a certain extent, it improves the intelligence of street lights and saves management and maintenance costs.

Measures to Improve the Energy Efficiency of Street Lighting Systems in the Kharkiv City

High-quality street lighting improves visual perception of the road and provides for a significant decrease in the number of road accidents. It has been established that the total number of accidents can be reduced by 30% for national roads and by 45% for especially hazard areas (e.g., at intersections). Doubling of the average luminance of the road surface significantly reduces the number of accidents in the dark and twilight. Sufficient street lighting contributes to: reducing electricity consumption; decreasing operating costs; improving the environmental situation; promoting business, tourism and investment activity; decreasing the number of criminal offenses. The analysis of recent research and publications helped choose the best European practices which can be used to improve the outdoor lighting in Ukraine. The street lighting network is continuously growing and being modernized. Different types of light sources are being used in the network to illuminate the city. Today, high-pressure lamps (HPS) are leading. They are increasingly replaced by LED light sources. Not a small share is accounted for by metal-halide lamps. The smallest number of light sources in the street lighting system, high-pressure mercury and compact fluorescent lamps (CFLs). To increase the efficiency of the street lighting system and reduce energy consumption for its operation, measures for its reconstruction and modernization are required. For this purpose, it is necessary to address the following problems: high level of obsolescence and physical wear and tear of system elements; inefficient use and high losses of electricity at the stages of transportation and consumption, due to the use of obsolete and worn-out equipment; suboptimal distribution of the utility capacity, which leads to ineffective use of the existing lighting system; low efficiency of the street lighting control system, due to the lack of electric meters and remote monitoring and control of the street lighting. Introduction of energy-saving types of light sources is one of the ways to modernize the existing street lighting system. It is necessary to replace old lighting fixtures, which have already exhausted their life span, by new energy-saving light sources (replace CFLs by LEDs), use automatic control systems. All this in turn will help reduce energy costs by 60%. To improve energy efficiency of the street lighting system, it is also recommended to carryout the replacement of electromagnetic ballasts by electronic ones. The employment of electronic ballasts, e.g., in case of using HPS 250 lamps, allows to save approximately 255 kWh/year. Considering that the price per kW of electric energy is UAH 2.68, one luminaire helps save the amount of UAH 683.4 per year.

The Intelligent Street Light Control System for Preventing Heavy Fog of Expressway Based on ZigBee

The Intelligent Street Light Control System for Preventing Heavy Fog of Expressway Based on ZigBee

Internet of things and fuzzy logic for smart street lighting prototypes

Internet of things (IoT) and fuzzy logic are very useful in increasing the efficiency and effectiveness of a system; this study applies both to the street lighting systems. The prototype of a street lighting control and monitoring system has been completed. The status of lights that are on or off and the value of the light intensity can be monitored by using IoT. The intensity of the light is fuzzy controlled by utilizing the presence of vehicles and pedestrians around the lights. The prototype is made with a scale against real conditions. Data is processed and transmitted using a microcontroller and Wi-Fi on the IoT module. Mobile applications have been used on smartphone interfaces to monitor and control lamps wherever they are connected to the Internet. Changes in the status of lights to turn on or off are done by the relay module. The fuzzy light intensity control system uses sensors and microcontrollers by utilizing the presence of vehicles and pedestrians around the lights. Performance evaluation has been carried out on a miniature street lighting with the results of monitoring and control following its function. An analysis of the resulting energy savings has been demonstrated.

Cloud based automatic street lighting control system

Conventional street lighting control systems is manual control, light sensitive control, and simple timing control while energy consumption and operators are unable to monitor street lights, that significantly disrupts management and maintenance. This work is based on the idea of maximize the maintaining and minimize an energy loss. Much of the energy produced daytime is saved in a solar cell and then will use to glow street lights throughout the night. The system also provides an energy-efficient operation mode by adapting the automated method. The lights switch on/off automatically according to vehicle movement or day/night sensor as well as to reduce management cost and monitor status information for each street lighting unit. In this paper two sensors are utilized that are Light Dependent Resistor (LDR) sensor to signalize a day/night time and Infrared Obstacle (IR) sensors to discover the movement on the street. Arduino microcontroller is utilized as a brain to control the street lighting system. In the other hand sensors data are analyzed and stored in Thingspeak cloud after are sent by Arduino UNO. Experimental results show that the system is stable and reliable as it can be applied as a model system.

Using a production-type expert system in the street lighting control system

The problem of outdoor lighting control is investigated. The analysis of the evolution of lighting control is carried out. An approach to the construction of an automated control system for outdoor lighting based on a production-type expert system is proposed.

Use of Receiver Operating Characteristic Curve to Evaluate a Street Lighting Control System

Intelligent control of public lighting is nowadays one of the most challenging issues in smart city deployment. Lighting optimization entails a compromise between comfort, safety, and power consumption, affecting both vehicles and pedestrians. Smart solutions must estimate their characteristics to trade-off users’ needs and energy requirements. This paper proposes an intelligent street lighting control system and the Receiver Operating Characteristic (ROC) curve method to evaluate the best number of street lamps to achieve a balance between public road user comfort and system power consumption. The control system is based on the detection of users, mainly pedestrians, using presence sensors. From the detection of a pedestrian by two or more consecutive street lamps it is possible to determine their speed. Knowing the pedestrian speed, allows the system to anticipate and adjust the light intensity of the remaining street lamps, and provide a comfortable view of the street. Using the ROC curve, we evaluate the control algorithm in terms of the number of previous street lamps used. We have tested the system and the method in a model of pedestrians walking down a street. The obtained results show that ROC analysis used to control street lighting allows measuring the whole control system’s efficiency by providing a concrete number of previous street lamps.

A low-cost web-based smart street lighting geographical information system for smaller towns and villages

AbstractThe use of LED lights in smart street lighting to save energy is efficient and very common in many developed cities. However, such a system results in higher initial costs, which may discourage smaller towns and villages from its purchasing. This paper therefore deals with the design and development of a smart street lighting control system for smaller cities and villages. Such a system is required to be economical from the perspective of development and production. Considering other requirements such as platform independence, high availability and broad support, we proposed to build a system as a web application using a custom light control service component. The result is a web application that consists of a user interface served by a web server and an application server used to communicate with light control service. In addition, the system is designed as a geographical information system to be easy to use for managing street lights in groups or individually, while displaying them on the map. The system allows automatic sensor-based light intensity modulation by default with the possibility of manual adjustment or override of the illumination. It also includes a device error notification system with a tool to navigate faulty devices. The presented system is a low-cost solution for intelligent street lighting control designed for smaller cities or villages. They can apply the designed architecture of the system and the specific technologies suitable because of their low-cost implementation.