Smart Lighting System Research Articles

Innovative Lighting Systems: Opportunities for Energy Savings

This paper analyses, from an energy flow perspective, the implementation of smart lighting systems in street lighting, where lights are dimmed to adapt to the flow of objects passing in a street. The research focus on the sustainability perspective of implementing a transition to smart lighting systems when compared to regular LED lighting. To account for externalities, the energy flow was addressed considering the extra electronic devices used in a smart lighting system (controllers, motion sensors, radars, and computers).
 
 To compare both traditional LED street lighting and smart lighting the paper started with a model of a 2.5-kilometre street, scaling up scenarios of the commune Ecublens, in the Swiss canton of Vaud, and then to half and all residential streets of Switzerland were examined to understand if the gains in energy savings are scalable. 
 
 The research shows that, even with the additional electronic devices, the smart lighting system reduces the energy consumption of street lighting, even when considering the production of the extra components used. Financially, the extra costs of implementing smart lighting systems are offset by the savings in electricity consumption. Therefore, smart lighting systems for street lighting can be an environmentally and economically beneficial project to implement.

Assessing smart light enabled cyber-physical attack paths on urban infrastructures and services

Internet-of-Things (IoT) extends the provision of remotely managed services across different domains. At the same time, IoT devices primarily designed for home environments may also be installed within the premises of critical urban environments, such as government, banking and corporate domains, without proper risk evaluation. In this paper, we examine the effect of cascading attacks triggered by the integration of vulnerable smart lighting systems in critical domains. In particular, we utilise known vulnerabilities of smart lighting systems to demonstrate the potential risk propagation on popular installation domains found in smart cities and urban infrastructures and services. Based on validated vulnerabilities on popular off-the-shelf smart lighting systems, we set up realistic proof-of-concept connectivity scenarios for various urban infrastructures and domains. Using these scenarios, we evaluate the risk of cascading attacks, by applying a targeted risk assessment methodology for identifying and assessing IoT-enabled attacks.

A Review of Automatic Irradiation Adjustment Based LED Street Light with Vehicle Movement Detection

Abstract: In present day, the maintenance of streetlight is one of the major problem for electricity boards in India. Also, there is scope for saving power during off peak time i.e. in from around midnight 12AM to 04AM in the morning. The methods that are currently used to maintain and control the street light is more complex and uneconomical. In this paper a new technique is proposed to control the intensity of LED Street lights using LDR, and to automate street lights using PIR sensors, and LDRs, resulting in power saving. Implementation is done using PIC controller. This paper presents a smart street lighting system which provides a safe night time environment for all road users and pedestrian. The main objectives are to build an automation system of street lighting using a low-cost microcontroller which is PIC and to achieve energy-saving. Light Emitting Diode (LED) is represented as the light module. This system is controlled according to the specific mode. These modes are controlled by two sensors which are Light Dependent Resistor (LDR) and Passive Infrared (PIR) sensor. This system can automatically turn on and off the lights according to traffic flow. This system operates during the night and the focus is only for the one-way road at a junction. Street light will be on when only there is road user otherwise, it will turn off. This design can save a great amount of electricity or energy consumption compared to conventional street lights that keep alight during nights. Moreover, the maintenance cost can be reduced and lifespan of the system will increase. As the result, the system has been successfully designed and implemented as a model system Keywords: PIR, LDR, Streetlights, Power supply, microcontroller

Review of Various Technology Automatic Dimming Control of LED Street Light

Abstract: In present day, the maintenance of streetlight is one of the major problem for electricity boards in India. Also, there is scope for saving power during off peak time i.e. in from around midnight 12AM to 04AM in the morning. The methods that are currently used to maintain and control the street light is more complex and uneconomical. In this paper a new technique is proposed to control the intensity of LED Street lights using LDR, and to automate street lights using PIR sensors, and LDRs, resulting in power saving. Implementation is done using PIC controller. This paper presents a smart street lighting system which provides a safe night time environment for all road users and pedestrian. The main objectives are to build an automation system of street lighting using a low-cost microcontroller which is PIC and to achieve energy-saving. Light Emitting Diode (LED) is represented as the light module. This system is controlled according to the specific mode. These modes are controlled by two sensors which are Light Dependent Resistor (LDR) and Passive Infrared (PIR) sensor. This system can automatically turn on and off the lights according to traffic flow. This system operates during the night and the focus is only for the one-way road at a junction. Street light will be on when only there is road user otherwise, it will turn off. This design can save a great amount of electricity or energy consumption compared to conventional street lights that keep alight during nights. Moreover, the maintenance cost can be reduced and lifespan of the system will increase. As the result, the system has been successfully designed and implemented as a model system. Keywords: PIR, LDR, Streetlights, Power supply, microcontroller

Review of Various Technology Automatic Dimming Control of LED Street Light

In present day, the maintenance of streetlight is one of the major problem for electricity boards in India. Also, there is scope for saving power during off peak time i.e. in from around midnight 12AM to 04AM in the morning. The methods that are currently used to maintain and control the street light is more complex and uneconomical. In this paper a new technique is proposed to control the intensity of LED Street lights using LDR, and to automate street lights using PIR sensors, and LDRs, resulting in power saving. Implementation is done using PIC controller. This paper presents a smart street lighting system which provides a safe night time environment for all road users and pedestrian. The main objectives are to build an automation system of street lighting using a low-cost microcontroller which is PIC and to achieve energy-saving. Light Emitting Diode (LED) is represented as the light module. This system is controlled according to the specific mode. These modes are controlled by two sensors which are Light Dependent Resistor (LDR) and Passive Infrared (PIR) sensor. This system can automatically turn on and off the lights according to traffic flow. This system operates during the night and the focus is only for the one-way road at a junction. Street light will be on when only there is road user otherwise, it will turn off. This design can save a great amount of electricity or energy consumption compared to conventional street lights that keep alight during nights. Moreover, the maintenance cost can be reduced and lifespan of the system will increase. As the result, the system has been successfully designed and implemented as a model system. Key Words: PIR, LDR, Streetlights, Power supply, microcontroller

A Review of Automatic Irradiation Adjustment Based LED Street Light with Vehicle Movement Detection

In present day, the maintenance of streetlight is one of the major problem for electricity boards in India. Also, there is scope for saving power during off peak time i.e. in from around midnight 12AM to 04AM in the morning. The methods that are currently used to maintain and control the street light is more complex and uneconomical. In this paper a new technique is proposed to control the intensity of LED Street lights using LDR, and to automate street lights using PIR sensors, and LDRs, resulting in power saving. Implementation is done using PIC controller. This paper presents a smart street lighting system which provides a safe night time environment for all road users and pedestrian. The main objectives are to build an automation system of street lighting using a low-cost microcontroller which is PIC and to achieve energy-saving. Light Emitting Diode (LED) is represented as the light module. This system is controlled according to the specific mode. These modes are controlled by two sensors which are Light Dependent Resistor (LDR) and Passive Infrared (PIR) sensor. This system can automatically turn on and off the lights according to traffic flow. This system operates during the night and the focus is only for the one-way road at a junction. Street light will be on when only there is road user otherwise, it will turn off. This design can save a great amount of electricity or energy consumption compared to conventional street lights that keep alight during nights. Moreover, the maintenance cost can be reduced and lifespan of the system will increase. As the result, the system has been successfully designed and implemented as a model system Key Words: PIR, LDR, Streetlights, Power supply, microcontroller

Multi-hop ESP-Mesh Network and MQTT Protocol for Smart Light Systems in High-Rise Buildings

When a high-rise building's lights are not required because they are frequently left on, electrical energy is wasted as a result of this. The smart light is one of the effective ways to energy saving in a building. This study aims to create a smart light system using the ESP-Mesh network and the MQTT protocol to control the turn on/off of all lights in all rooms of a high-rise building. The ESP-Mesh network is a mesh of ESP8266 devices that are designed for multi-hop transmission. The MQTT is one of the widely used IoT protocols that allows a smartphone to control the lights in every room in a mesh topology via the internet remotely. The performance evaluation shows that a multi-hop ESP-Mesh is better than that a Single-hop ESP8266 in signal strength. The signal strength of the ESP8266 single-hop is bad. Meanwhile, the signal strength of the multi-hop ESP-Mesh is good in all rooms. Furthermore, The functional tests of the multi-hop ESP-Mesh show that although there are various broken paths caused by several disconnected nodes, all lights can be turned on or off suitably through the command from the smartphone switch. Turning off the not-required lights by smart light systems can help save energy.

Wireless fieldbus networking with precision time synchronization for a low-power WSAN

A wireless sensor actuator network (WSAN) is an essential part of the industrial Internet of things (IIoT) with a cyber-physical system (CPS). However, the lack of time synchronization support for WSANs to date means that losses in synchronization accuracy have not been overcome. In this manuscript, we design a real-time kernel to resolve the precision time synchronization (PTS) problem and achieve dynamic automatic synthesis and rapid deployment in a complex WSAN system. Furthermore, tight coupling between wireless control and time synchronization motivates a Modbus-based precision time protocol (PTP) codesign that integrates industrial fieldbus networks and a PTS design. The experimental results indicate that our proposed PTP performance can far exceed the time synchronization requirement of an industrial real-time system. Finally, the proposed solution is successfully applied to an IoT-based smart lighting system.

A power-efficient self-calibrating smart lighting system

Lighting load accounts for a significant portion of overall energy consumption in office buildings. To reduce this load, we have designed and built a smart self-calibrating lighting control system that minimizes power consumption that automatically responds to changes in daylight and occupancy, while simultaneously providing personalized lighting comfort to each occupant. The system measures illuminance and occupancy from sensors located at each work station. Using an unobtrusive self-calibration process, it estimates the relationship between the dimming level of each bulb and the illuminance at each work station. Subsequently, an adaptive control algorithm maintains the desired illuminance at work surfaces despite environmental fluctuations by periodically recalculating the power-efficient and comfort-preserving dimming level for each bulb. Based on a realistic deployment of our system, we find that our system quickly responds to changes in occupancy, daylight and user preferences. We also show, through extensive simulations using 7 months of collected daylight and occupancy data, that our system reduces energy consumption by about 40% compared to conventional LED lighting systems.

Development of a BIM and IoT-Based Smart Lighting Maintenance System Prototype for Universities’ FM Sector

Reactive maintenance (RM) is a core service of the operation and maintenance (O&M) phase, the most prolonged and costly within the building lifecycle. RM is characterised by inefficient asset information and communication management, impacting critical FM problems and users’ experience. Building information modelling (BIM) and Internet of things (IoT) has enabled the development of digital twins, moving facilities management (FM) from a reactive approach towards a predictive one. Although previous studies have investigated the application of such technologies to FM, there is a lack of understanding on procedural issues related to its implementation in FM and RM. This research aimed to characterise strategies and decisions involved in prototyping a BIM and IoT-based smart-lighting maintenance system and identify its potential impacts on universities’ maintenance processes. The adopted research strategy and data collection methods involved prototyping, questionnaires, and interviews. The results show a high level of complexity in converging maintenance needs and technological abilities for FM and the importance of procedures and standards at organisational and industry levels. Moreover, it evidenced that the automation of functions and the centralisation of information enabled by BIM and IoT can optimise service provision, generate environmental and efficiency gains, and improve users’ safety and satisfaction.

CIMA: A Novel Classification‐Integrated Moving Average Model for Smart Lighting Intelligent Control Based on Human Presence

Smart lighting systems utilize advanced data, control, and communication technologies and allow users to control lights in new ways. However, achieving user comfort, which should be the focus of smart lighting research, is challenging. One cause is the passive infrared (PIR) sensor that inaccurately detects human presence to control artificial lighting. We propose a novel classification‐integrated moving average (CIMA) model method to solve the problem. The moving average (MA) increases the Pearson correlation (PC) coefficient of motion sensor features to human presence. The classification model is for a smart lighting intelligent control based on these features. Several classification models are proposed and compared, namely, k‐nearest neighbor (KNN), support vector machine (SVM), decision tree (DT), näive Bayes (NB), and ensemble voting (EV). We build an Internet of things (IoT) system to collect movement data. It consists of a PIR sensor, a NodeMCU microcontroller, a Raspberry Pi‐based platform, a relay, and LED lighting. With a sampling rate of 10 seconds and a collection period of 7 days, the system achieved 56852 data records. In the PC test, movement data from the PIR sensor has a correlation coefficient of 0.36 to attendance, while the MA correlation to attendance can reach 0.56. In an exhaustive search of an optimum classification model, KNN has the best and the most robust performance, with an accuracy of 99.8%. It is more accurate than direct light control decisions based on motion sensors, which are 67.6%. Our proposed method can increase the correlation value of movement features on attendance. At the same time, an accurate and robust KNN classification model is applicable for human presence‐based smart lighting control.

Toward the Energy Optimization of Smart Lighting Systems Through the Luminous Potential of Photoluminescence

Toward the Energy Optimization of Smart Lighting Systems Through the Luminous Potential of Photoluminescence

Adaptability Attribute for Smart City: Advanced Adaptive Street Lighting Systems

“Smart City Advanced Adaptive Street Lighting Systems” that aimed to build all hardware/software components of an adaptive urban smart lighting architecture that allows municipalities to manage and control public street lighting lamps. To save energy, the system can automatically modify the brightness of street lamps based on the presence of vehicles (buses/trucks, cars, motorbikes, and bikes) and/or pedestrians in specified locations or segments of the streets/roads of interest. The fundamental contribution of this research is to build a low-cost smart lighting system while also defining an IoT infrastructure in which each lighting pole is a component of a network that can improve the amplitude of the system. In a broader sense, the suggested smart infrastructure can be seen as the foundation for a larger technology architecture aiming at providing value-added services for sustainable cities. The smart architecture consists of a number of subsystems (local controllers, motion sensors, video cameras, and weather sensors) and electronic devices, each of which is responsible for performing certain tasks: Video processing for vehicle motion detection and classification, remote street segment lamp management, single street lamp brightness control, wireless and wired data exchanges, power consumptions analysis and traffic evaluation.

Smart City Street Lighting System Quality and Control Issues To Increase Energy Efficiency and Safety

According to standards, the lighting system is one of the key elements to provide safety on city roads, defined by quality parameters. LED technology and movement detection sensor interaction bring about new regulation techniques, creating an energy-efficient smart LED lighting system concept. This paper reveals extensive comparative data analysis of Dialux simulation results before the project implementation phase and in-situ quality parameter measurements for various street profiles and LED luminary power types. After the project implementation phase, more than 1000 measurement points are reached. Further, energy efficiency increase issues in smart lighting systems are described in terms of LED luminary dimming profile analysis and future dynamic control application modes. The first findings clearly show that in most cases light output in simulation results is lower than in real situations; therefore, LED luminary power can be decreased, allowing for higher energy savings in first luminary maintenance years, keeping the same defined ME class or safety level. Let us suppose that the traffic intensity data are obtained from smart system sensors. In that case, the ME class can be dynamically selected during different night times, thus increasing safety and providing extra energy savings using the same system elements, as well as leading to better ROI values.

Smart vehicle lighting system based on a-SiCH technology

In this paper the use of Visible Light Communication (VLC) in Vehicle Communication Systems is analyzed. The system aims to ensure communication between LED based emitters and SiC based receivers located at the vehicles. The proposed smart lighting system combines the functions of lighting, positioning, and communications. The SiC receivers is used as a encoder/decoder device. This photosensitive element features active filter properties, it multiplexes the modulated polychromatic signal coming from the LEDs in an electrical signal, performs multiplexing/demultiplexing techniques and decode the received information. A traffic scenario is established and two connected vehicular communications simulated. Infrastructure-to-Vehicle (I2V) follow by Vehicle-to-Vehicle (V2V) communications are analyzed. In the V2V communication, the emitter is based on the front headlights of the vehicle, while for the study of the I2V communication system, the emitter was built on the streetlights. The VLC receiver acts as a Wavelength Division Multiplexer (WDM) and increases the signal conditioning capability to decode the transmitted information. Each receiver is a two terminal p-i'(a-SiC:H)-n/p-i(a-Si:H)-n heterostructure located on both the tails and on the top roof of vehicles. The spectral sensitivity of the receiver and its optical gain are analyzed. For message transmission, the individual chips of the white trichromatic RGB LEDs are modulated acting, for data transfer, as individual VLC channels. A violet LED is used for error control and to identify the ID position of the transmitter. Free space is the medium of transmission. An on-off modulation scheme (OOK) is used to transmit data. An algorithm for decoding information is established. The connected I2V2V system was tested. The experimental results show that using white modulated LEDs for lighting and data transmission and a SiC WDM device to decode the information is possible to build a VLC vehicular system that ensures de communication between the outside infrastructures and the cars. Copyright © 2018 VBRI Press.

IoT based smart and intelligent smart city energy optimization

With the effective result of IoT architecture in all research areas, we propose IoT framework based energy efficient smart and intelligent street road lighting system that consist of IoT sensor bases smart electric pole with controller for tuning LED lamps. In our work we replace traditional metal halide lamps with mesophic design LED lamps based on human eye sensitivity and it provides significant saving of energy too. Based on the sensor unit information about traffic flow and presence and absence of occupant smart and intelligent decision making module compute intensity level that generate different width pulse using PWM dimming system which triggers LED power switch via DALI controller mounted inside LED Light Controller. For efficient use of sustainable energy resources we use sustainable power systems that consist of PV solar panel units, Battery storage systems and smart electric power grids. For the charging battery system we use MPPT based dynamic battery charging algorithm. From experiment and simulated result, we observe that proposed energy efficient Smart Street lighting saves considerable amount of energy during peak and off peak hours not only at highway roads but at residential and sub-urban pedestrian areas also. It will finally decrease the consumption of energy and carbon emission. We perform comparative result analysis of proposed systems with existing lighting systems based on energy consumption. Our experimentation result also represents the effectiveness of the proposed dynamic battery charging algorithm based on the battery storage PV solar panel system performance.

A low-power and low cost smart streetlight system based on Internet of Things technology

Street lighting, as the most essential and universal component of the urban lighting system, accounts for a large portion of public electricity usage. Therefore, improving street lamps working efficiency is vital for energy savings. This paper demonstrates the design of a smart street lighting system supported by the combination of NB-IoT and LoRa communication technology. By adopting an optimized street lamp control algorithm, the system can realize the automatic control of street lights according to the real-time traffic flow information. This system has been installed on Luyang Avenue, Lucheng City, Shanxi Province, China in May 2019. It managed to reduce the electricity consumption in this region significantly in June 2019, which was 18% lower than that in April 2019 and 19.7% lower than that in June 2018. By illustrating the unique advantages of this system in energy savings and cost reduction, this paper displays its potential for further application in the construction of smart cities on a large scale.

IoT Enabled Smart Lighting System for Smart Cities

The pace of urbanisation has risen tremendously during the last few decades. To provide a higher quality of life, urban dwellers will require a greater variety of improved services and apps. The term “smart city” refers to integrating contemporary digital technology in the setting of a city to improve urban services. There are possibilities to create new services and connect disparate application areas with each other as a result of the use of information and communication technologies in the smart city. However, to make sure the services in an IoT-enabled smart city environment remain running without depleting valuable energy resources, all of the apps have to be maintained using energy resources that are kept at a minimum. IoT can enhance a city’s lighting system since it uses more energy than other municipal systems. An intelligent city integrates lighting system sensors and communication channels with enhanced intelligence features for a Smart Lighting System (SLS). To control lighting more efficiently, SLS systems are built to be autonomous and efficient. We cover the SLS and evaluate several IoT-enabled communication protocols in this article. Furthermore, we evaluated several use scenarios for IoT enabled indoor and outdoor SLS and generated a report detailing the energy consumption in different use cases. By using IoT-enabled smart lighting systems, our research has shown that energy savings are possible in both indoor and outdoor settings, which is equivalent to a forty percent reduction in energy usage. Finally, we went through the SLS in the smart city research plans.

Energy saving potential through artificial lighting system in PV integrated smart buildings

Artificial lighting in buildings is accountable for a remarkable portion of overall energy consumption. It is thus necessary to reduce especially for zero energy buildings (ZEBs). Daylight harvesting holds the immense potential of reducing energy consumption but it can disturb the occupants' optical preferences if harvested in excess. A semi-transparent building integrated photovoltaic (BIPV) module which can generate clean energy at the building site and allows the reduced daylight harvesting through, has been proposed as the envelope of the building facade . Hence, to minimize energy consumption and enhancing occupants' visual preferences, a smart lighting system with daylight harvesting through BIPV for an office building is proposed in this paper. The advantages associated with a low-voltage DC (LVDC) distribution system for the proposed system in ZEB is highlighted. Moreover, the opportunity of energy-saving across the proposed artificial lighting system with BIPV as the envelope of the building is investigated with occupants’ visual preference levels in different sky conditions. Results show that the proposed lighting system can be fully energized by the energy generated from the BIPV module. Moreover, a significant amount of surplus energy was also reported. Further, the economic and environmental footprint analysis of the BIPV as a building envelope is presented. The result indicates a competent levelized cost of energy (LCOE) when comparing with the existing utility grid. • Building-integrated photovoltaic module is proposed as an envelope of the building. • Low voltage DC distribution system for the building is highlighted with BIPV. • Coupled energy analysis of smart lighting systems and BIPV are addressed. • The economic and environmental footprint analysis of the BIPV is also included. • Smart lighting system is energized by the energy generated from the BIPV module.

LiFi Positioning for Industry 4.0

Precise position information is considered as the main enabler for the implementation of smart manufacturing systems in Industry 4.0. In this article, a time-of-flight based indoor positioning system for LiFi is presented based on the ITU - T recommendation G.9991. Our objective is to realize positioning by reusing already existing functions of the LiFi communication protocol which has been adopted by several vendors. Our positioning algorithm is based on a coarse timing measurement using the frame synchronization preamble, similar to the ranging, and a fine timing measurement using the channel estimation preamble. This approach works in various environments and it requires neither knowledge about the beam characteristics of transmitters and receivers nor the use of fingerprinting. The new algorithm is validated through both, simulations and experiments. Results in an <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$\text{1}\;{\rm{m}} \times \text{1}\;{\rm{m}} \times \text{2}\;{\rm{m}}$</tex-math></inline-formula> area indicate that G.9991-based positioning can reach an average distance error of a few centimeters in three dimension. Considering the common use of lighting in indoor environments and the availability of a mature optical wireless communication system using G.9991, the proposed LiFi positioning is a promising new feature that can be added to the existing protocols and enhance the capabilities of smart lighting systems further for the benefit of Industry 4.0.