Urban Street Lighting Infrastructure Monitoring using a Mobile Sensor Platform (original) (raw)

Movement Sensing Street Lighting

This project aims at reducing energy consumption by minimizing the unnecessary use of energy consumed by street lights. Based on low cost microcontroller, this project incorporates a Solar power module, a Light Emitting Diode (LED) module, Light Detecting Resistors (LDR), and Infrared (IR) Sensors.The street lights are simulated using LED-based lamps, and the intensity of their illumination is varied depending upon the light in the external environment, where the changes are detected using the LDRs. The LEDs will glow the brightest when the environment is the darkest and only when there is movement detected on the street (using the IR sensors), is turned off when the environment is the brightest, and isdim otherwise. As the detected object is on the move, the leading lights are turned on, and the trailing lights are turned off, one-by-one. The solar power unit collects the solar energy during the day, and powers the project system during dark hours. As this system does not keep the street lights glowed continuously, it is an energy efficient system.

Advanced Street Lights

International Journal of Engineering Research and, 2016

This paper is an endeavor to ensure energy saving and accident identification through Smart Street Lights. This paper strives towards mitigating the manual error of not being able to switch ON the lights in the evening and switching it off in the morning. In this paper usage of automated Solar Voltaic is suggested which can not only conserve energy but also maximizes efficiency through LED lights. The GPRS/GSM module is used in this project to establish a wireless communication between the poles and main server. It will send information about the faulty lamps in the form of SMS. Our smart street lights can be used to identify the accident and can alert the nearest fire station with the help of Fire detector and GPRS/GSM module.

Intelligent Street Lighting Energy-Saving System Based on Climate Conditions and Vehicle’s Movements

Jurnal Kejuruteraan

The huge amount of electric power and cost associated with street lighting has raised the need to investigate both cost issues and environmental concerns. Cities worldwide are increasingly investing in energy-efficient street lighting systems. Modern street lighting technology can lower energy consumption as well as operation and maintenance costs significantly. In addition, bright street lighting can reduce accidents and crime rate in the area. Street lighting is an essential public service that provides a significant factor contributing to the quality of life and productivity of people workforces. This paper proposes an intelligent and energy-efficient traffic sensing system based on the widely distributed street lights. It is intended to observe vehicle’s movement on the road and turn ON a block of street lights ahead of vehicle whenever needed. As the vehicle passes by, the system turns OFF the trailing lights. The brightness (intensity of light) of the street light is adjusted ...

Playing in traffic: an investigation of low-cost, non-invasive traffic sensors for street light luminaire deployments

International Journal of Grid and Utility Computing, 2018

Real-time traffic monitoring is essential to the development of smart cities as well as its potential for energy savings. However, real-time traffic monitoring is a task that requires sophisticated and expensive hardware. Owing to the prohibitive cost of specialised sensors, accurate traffic counts are typically limited to intersections where traffic information is used for signalling purposes. The sparse arrangement of traffic detection points does not provide adequate information for intelligent lighting applications, such as adaptive dimming. This paper investigates the low-cost and off-the-shelf sensors to be installed inside street lighting luminaires for traffic sensing. A luminaire-mounted sensor test-bed installed on a moderately-busy road trialled three non-invasive presence-detection sensors: Passive Infrared (PIR), Sonar (UVD) and lidar. The proof-of-concept study revealed that a HC-SR501 PIR motion detector could count traffic with 73% accuracy at a low cost and may be suitable for intelligent lighting applications if accuracy can be further improved.

Survey on Street Lighting System Based On Vehicle Movements

Street Light Control System which operates automatically is not only easiest but also the intelligent system. This system can be set to operate in automatic mode, which regulates the streetlight according to brightness and dimness Algorithm and light intensity. This control can make a reasonable adjustment according to the seasonal variation. we can take the initiative to control streetlights through PC monitor terminal. This street light system also includes a time cut-out function, and an automatic control pattern for even more electricity conserving, when vehicles pass by, the light will turn on automatically, later turn off. This design can save a great amount of electricity compared to streetlamps that keep alight during nights. The design implements traffic flow magnitude statistics without adding any hardware, facilitating transportation condition information collecting. Furthermore, this system has auto-alarm function which will set off if any light is damaged and will show the serial number of the damaged light, thus it is easy to be found and repair the damaged light. The system can be widely applied in all places which need timely control such as streets, stations, mining, schools, and electricity sectors and so on. In addition, the system integrates a digital temperature and humidity sensor, not only monitoring the streetlight but also temperature and humidity. The core of the system is constructed based on the Microchip's PIC18F microcontroller. IEEE802.15.4 standard Microchip Wireless (MiWi) communication protocol is used here for implanting the wireless communication between street light unit and PC

Computer vision System for Public Illumination Management

International Journal of Computer Applications, 2020

The present work proposes the management of street lighting through a computer vision approach, for which algorithms are used to detect pedestrians. The current scenario of demand for electricity, has rates that constantly increase, due to taxes, urban expansion, among others. Therefore, it is extremely important to look for alternative ways to minimize costs. One of the segments to be explored with great economic potential is the management of street lighting, in recent times changes have been taking place in this area, where governments are replacing sodium vapor lighting by LEDs lamps, which are already capable of dramatically reduce energy consumption. In this context, computer vision systems can help to reduce this consumption even further, controlling the power of these LED lamps according to the flow of people on the road. The computer vision system proposed in this work was implemented in C ++ using the OpenCV library, applied in a Raspberry Pi 3. It was also used the Fuzzy Logic to calculate the power that the LEDs must be adjusted due to the number of people on the road as well as the ambient lighting. For the execution of the validation tests of this proposal, images were acquired on public roads with pedestrians, as well as simulations of these environments were carried out, thus being possible to test all the proposed possibilities. With the real application of this project, it is possible to observe a savings of approximately 44% in the consumption of public lighting, this compared to the use of LED lighting.

Design of Intelligent Street Lighting System (ISLS)

Irish Interdisciplinary Journal of Science & Research (IIJSR) , 2023

This paper outlines the development and execution of a sophisticated street lighting system with the purpose of improving urban environments. Traditional street lighting systems often lack energy efficiency and control. The system we propose uses cutting-edge technologies like IoT and AI to create an intelligent infrastructure that adapts lighting levels to environmental conditions, traffic flow, and pedestrian movement. Using sensors, data analytics, and adaptive algorithms, our system optimizes energy consumption while ensuring adequate lighting for safety and visibility. Furthermore, we analyze the structure, elements, and factors to consider when implementing the intelligent street lighting system, emphasizing its potential advantages in terms of energy conservation, ecological sustainability, and urban visual appeal. Our approach has been proven effective and feasible in various urban settings through the use of case studies and simulations. In summary, this research adds to the current endeavors of developing intelligent and environmentally-friendly urban areas by introducing inventive lighting solutions.

Lighting Prediction and Simulation in Large Nighttime Urban Scenes

Night vision goggles (NVGs) are widely used by helicopter pilots for flight missions at night, but the equipment can present visually confusing images especially in urban areas. A simulation tool with realistic nighttime urban images would help pilots practice and train for flight with NVGs. However, there is a lack of tools for visualizing urban areas at night. This is mainly due to difficulties in gathering the light system data, placing the light systems at suitable locations, and rendering millions of lights with complex light intensity distributions (LID). Unlike daytime images, a city can have millions of light sources at night, including street lights, illuminated signs, and light shed from building interiors through windows. In this paper, a Procedural Lighting tool (PL), which predicts the positions and properties of street lights, is presented. The PL tool is used to accomplish three aims: (1) to generate vector data layers for geographic information systems (GIS) with statistically estimated information on lighting designs for streets, as well as the locations, orientations, and models for millions of streetlights; (2) to generate geo-referenced raster data to suitable for use as light maps that cover a large scale urban area so that the effect of millions of street light can be accurately rendered at real time, and (3) to extend existing 3D models by generating detailed light-maps that can be used as UV-mapped textures to render the model. An interactive graphical user interface (GUI) for configuring and previewing lights from a Light System Database (LDB) is also presented. The GUI includes physically accurate information about LID and also the lights' spectral power distributions (SPDs) so that a light-map can be generated for use with any sensor if the sensors luminosity function is known. Finally, for areas where more detail is required, a tool has been developed for editing and visualizing light effects over a 3D building from many light sources including area lights and windows. The above components are integrated in the PL tool to produce a night time urban view for not only a large-scale area but also a detail of a city building. iii

Modeling Urban Street Lighting Infrastructure Using Open Source Datasets

2021

Streetlights in urban settings have been increasingly ubiquitous assets in cities worldwide. The illumination of street networks accounts for a major and growing burden on the environment, municipalities's budgets and power supply systems. The global demand for street lighting is expected to increase by 80% by 2030 compared to 2005. This paper introduces an open source GIS-based tool to simulate urban street infrastructures and calculate the electricity demand for streetlights. Furthermore, different scenarios of operating street lighting systems using local available renewable energy resources and flexibilization technologies are investigated. Using solely open source data sets, this research confirms the possibility of replicating realistic urban street infrastructures. The extracted OpenStreetMap geospatial road networks for the case study of the city of Berlin is validated against available public data sets. It is found that, a self sufficient streetlight system, 100% renewa...