Smart Lighting Control System Research Articles

AUTOMATIC LABORATORY LIGHTING SYSTEM WITH AN INFRARED BASE

The "Infrared-Based Automatic Laboratory Lighting System" represents a novel way to improve energy efficiency and stoner comfort in lab environments. Conventional laboratory lighting systems often warrant rigidity and efficacy, leading to unnecessary energy usage and inadequate lighting. In order to overcome these obstacles, this design incorporates a smart lighting control system that uses infrared (IR) detectors to identify the presence of mortals inside the laboratory. The primary operation of the system entails placing IR detectors in strategic locations across the lab space. These detectors monitor individuals continuously and relay the data they find to a central control unit that is based on a microcontroller platform. The control unit initiates the activation or adaptation of lighting institutions in the vicinity of detected movement upon detection of a mortal presence. This guarantees that the lighting is optimized for continuous conditioning, providing suitable lighting while reducing energy waste during periods of unoccupied occupancy. Crucial features of the proposed system include real-time responsiveness and rigidity to varying residency patterns. The integration of IR detectors with the microcontroller-grounded control unit enables a nippy and accurate discovery of mortal presence, allowing the system to acclimate lighting situations instantly as individuals enter or leave the laboratory space. Additionally, the system can be configured to generate lighting configurations based on particular circumstances, including ambient lighting for common spaces or task lighting for lab workstations. Apart from enhancing energy efficiency, the method places emphasis on the safety and experience of stoners. The technology lowers the risk of accidents or crimes related to dim illumination by providing appropriate and safe lighting conditions that are tailored to the functional needs of the laboratory. Similarly, the automation of lighting control eliminates the need for handcrafted solutions, allowing laboratory workers to focus on research or experimentation. All things considered, the "Infrared-Based Automatic Laboratory Lighting System" provides stoner-friendly and environmentally friendly outcomes to improve lighting operations in laboratory settings. By promoting energy conservation, perfecting the stoner experience, and ensuring safety, this system contributes to the advancement of effective and sustainable practices in laboratory operations. Keywords: LED (light emitting diode), microcontroller, Internet of Things, sensors, relay mechanism, and LCD (liquid crystal display).

Advancing Smart Lighting: A Developmental Approach to Energy Efficiency through Brightness Adjustment Strategies

Smart lighting control systems represent an advanced approach to reducing energy use. These systems leverage advanced technology to provide users with better control over their lighting, allowing them to manually, remotely, and automatically modify the brightness, color, and timing of their lights. In this study, we aimed to enhance the energy efficiency of smart lighting systems by using light source data. A multifaceted approach was employed, involving the following three scenarios: sensing device, daylight data, and a combination of both. A low-cost sensor and third-party API were used for data collection, and a prototype application was developed for real-time monitoring. The results showed that combining sensor and daylight data effectively reduced energy consumption, and the rule-based algorithm further optimized energy usage. The prototype application provided real-time monitoring and actionable insights, thus contributing to overall energy optimization.

Long-Term Monitoring Campaign of LED Street Lighting Systems: Focus on Photometric Performances, Maintenance and Energy Savings

The renovation of public lighting installations by replacing the traditional systems with LED technologies and introducing smart lighting control systems is a policy widely adopted to contain energy consumption and expenditure. Additionally, the long-term monitoring of the depreciation of the new lighting systems is a crucial issue. The aim of this study is to report the results of in-field measurements of new LED lighting systems in the city of Turin (Italy). A method was defined to assess: (i) energy performance (through data from the remote-control system); (ii) photometric performance (through in-field measurement campaigns); and (iii) depreciation of the photometric performance over a period of approximately 5 years. Results demonstrated that the new LED systems allow us to achieve an average energy saving of 51% compared to the ex-ante condition, improving the photometric performances and compiling the standard requirements by lowering the over-illumination levels. Moreover, the measured depreciation of the LED systems over time was compared with the predicted depreciation, estimated based on the calculation method proposed in Standards BS 5489-1:2020 and ISO/CIE TS 22012:2019. The results obtained showed that the measured depreciation of the photometric performance was closer to the predicted depreciation trend according to BS 5489-1:2020 (variations between 0% and 4%), while greater variations (between 17% and 23%) emerged considering the ISO/CIE TS 22012:2019.

Development of public lighting system with smart lighting control systems and internet of thing (IoT) technologies for smart city

This study proposes the design and development of public light systems integrated with Internet of Things (IoT) applications for smart cities. Smart public lighting systems are designed using LED light sources in combination with a controller based on light intensity and motion sensors to control the brightness in working areas as per standard requirements. The control of smart public lighting systems is designed to operate in three modes: manual, scheduled, and auto modes, which are tested and compared in terms of lighting and power quality. Other functions of IoT, such as air pollution detection, security system-based video surveillance, and warning systems for flood disasters, are integrated into smart public lighting systems. A prototype of the designed smart public lighting system is presented in this paper. The parameters of average illuminance, overall uniformity, and threshold increment were implemented using DIALux software to optimise the luminaire spacing. The results showed that the goal of energy saving could be achieved using the auto mode. Although the automatic mode caused current harmonic distortion to the electrical grid, the harmonic value was less than the specified standard. Furthermore, the precision of IoT system operation was dependent on environmental variations and the reliability of wireless network technology.

Performance Appraisal of Urban Street-Lighting System: Drivers’ Opinion-Based Fuzzy Synthetic Evaluation

Saudi Arabian urban roads and highways have witnessed a large number of traffic crashes. Road lighting is one of the most important factors influencing drivers’ safety during the nighttime. Street-lighting design (e.g., spacing and height), visibility (e.g., lane marking and oncoming vehicles), and drivers’ satisfaction (e.g., glare effect on eyes and overall ambiance) are primary criteria affecting the performance of an urban street-lighting system (USLS). The present study presents a methodology for the performance appraisal of USLS in Qassim, Saudi Arabia. An online questionnaire survey was developed to obtain drivers’ opinions on nine sub-criteria (three under each primary criterion). The responses were translated into a five-scale subjective rating system from very low to very high. Fuzzy synthetic evaluation (FSE) effectively aggregated the statistically diverse (p-value < 0.001) responses obtained on the three primary criteria. The study found that electronic billboards’ positioning, oncoming vehicle lights, and poor lighting in the course of bad weather (mainly dust) are mainly affecting the performance of USLS in the view of road users. The performance levels ranged between “medium” and “high”, with no criteria or sub-criteria achieving a “very high” level, suggesting a need for upgrades, such as conversion to LED lights and smart lighting control systems. The proposed methodology benefits the transportation ministries to identify lacking components of USLSs in different regions of Saudi Arabia. The methodology provides the opportunity to include additional or site-specific factors for appraising the performance of USLS before (during planning and design) or after the implementation of improvement actions.

Smart lighting control system based on fusion of monocular depth estimation and multi-object detection

Smart lighting systems can reduce energy consumption by controlling lights according to the distribution of personnel. Most of the current smart lighting systems using vision-based indoor personnel positioning method suffer from difficulties in calibration and deployment. A smart lighting control system based on fusion of monocular depth estimation and multi-object detection is proposed in this paper. The system automatically recognizes the relative positions of people and lights from the video and controls the lights, thereby reducing the complexity of calibration and deployment. In order detect the relative positions, a multi-object relative position detection algorithm (Deep-YOLO) is proposed. Deep-YOLO fuses and optimizes Scaled-YOLOv4 and AdaBins, and it detects the relative positions of people and lights by performing simultaneous multi-object detection and depth estimation on videos. A dedicated image dataset (PL) and deep transfer learning are utilized to improve the object detection accuracy of Deep-YOLO. In order to control lights according to the relative positions, a K-Means-based lighting control algorithm is proposed, and a smart lighting control system verification platform is developed. The experimental results show that the mAP of Deep-YOLO is 98.16% and the control average error of the system is less than 1 m.

Simulation Study of a Smart Factory Lighting and Shading System

Insufficient and uneven light distribution in the workplace affect the quality of work that requires high precision. In addition, inadequate lighting not only affects the health of workers but is also linked with a condition called 'Sick Building Syndrome'. The artificial light in factories is commonly manually controlled, resulting in energy wastage. Hence this paper presents a smart lighting and shading system to create both comfort lighting and energy-efficient factory environment. Three-dimensional modelling simulations were built using Tinkercad and Revit. The control system built utilizes the motorized skylight solar shades and the artificial high LED Bay, which able to adapt with the fluctuating factory lighting condition. If the light enters the factory through the motorized shade on the factory ceiling is insufficient or uneven, the artificial light will be switched on. The implementation of both mechanisms managed to improve the light distribution evenness and keep the light intensity level in the factory in the range between 885 lux and 1306 Lux from 9am to 6pm, while from 6pm onwards at average of about 900 lux. Furthermore, the electrical energy consumption is reduced significantly during the daytime as the control system has utilized the sunlight as part of the light source for the factory. The smart system can save as much as 22.39%, or 55.2128kWh from 9am to 7pm. In conclusion, the smart lighting and shading control system has proven the effectiveness theoretically, and the objectives were achieved.

An Anonymous Authentication and Key Update Mechanism for IoT Devices Based on EnOcean Protocol.

EnOcean, a commonly used control protocol in smart lighting systems, provides authentication, as well as message integrity verification services, and can resist replay attack and tamper attack. However, since the device identity information transmitted between sensors in smart lighting control systems is easily accessible by malicious attackers, attackers can analyze users’ habits based on the intercepted information. This paper analyzed the security of the EnOcean protocol using a formal analysis method based on the colored Petri net (CPN) theory and the Dolev–Yao attacker model and found that the protocol did not anonymize the device identity information and did not have a communication key update mechanism, so an attacker could easily initiate a key compromise impersonation attack (KCIA) after breaking the pre-shared communication key. To address the above security issues, this paper proposed an EnOcean-A protocol with higher security based on the EnOcean protocol. The EnOcean-A protocol introduced a trusted third-party server to send communication keys to communication devices because devices must obtain different communication keys from the trusted third-party server each time they communicated. Thus, this protocol could resist a KCIA and achieve forward security. Meanwhile, the device identity information was anonymized using a homomorphic hash function in the EnOcean-A protocol, and the dynamic update mechanism of the device identity information was added so that an attacker could not obtain the real identity information of the device. Finally, the formal analysis of the EnOcean-A protocol showed that the new protocol could resist a KCIA and ensure the anonymity and untraceability of the communication device, which had higher security compared with the EnOcean protocol.

Cloud-based lighting control systems: Fatigue analysis and recommended luminous environments

The development of Internet of Things (IoT) and the spread of various smart devices has made it easy to collect customized occupant information, and such smart devices and information have been applied to smart lighting control systems. Information on the personal characteristics of occupants can be utilized to create personalized luminous environment. This study focused on fatigue accompanying the activities of individuals and developed personalized smart lighting solutions to assist occupants in recovering their psycho-physiological state once they return home after performing daily activities. To this end, occupant activity information was analyzed in real time using an easily accessible mobile application and transmitted to a cloud-based platform, built using IBM Node-RED. Further, all daily activities and the number of steps taken from mobile application before returning home were used to quantify the fatigue level using the concept of Metabolic Equivalent Tasks (METs). Multiple regression analysis was employed to verify the accuracy between quantified fatigue level and subjective evaluation and to suggest resultant fatigue-level calculation formulas. From the calculated fatigue levels, the proposed luminous environment solution, such as appropriate illuminance and Correlated Color Temperature (CCT) values, was developed based on the results of previous relevant studies. Different luminous environments were implemented in a mock-up space as three case studies of different activity and fatigue levels. The proposed solutions are relevant to future intelligent and personalized building technologies to adapt from building-centric to human-centric environments by providing customized and automated indoor luminous environments.

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.

Efficient photodetector placement for daylight-responsive smart indoor lighting control systems

With continuous increase in energy consumption worldwide, design of smart lighting system to reduce electricity consumption have been a pressing issue. This research focuses on design of smart indoor lighting system analyzing multiple zones with variable desired lighting conditions, to enhance user comfort and energy consumption. The accuracy of such system significantly benefits from large number of photodetectors, which increases the energy consumption and complexity. In this paper, a novel efficient control mechanism which reduces the number of photodetectors with no significant loss in accuracy is presented. A linear optimization method and a clustering algorithm are applied to select the least number and appropriate locations of photodetectors. A neural network is also employed to set the dimming level of luminaires. Furthermore, few auxiliary photodetectors are mounted and additional neural network is trained to find the relation between the output (measured illuminance) of these auxiliary photodetectors and that of zone-mount ones. In order to maintain user comfort, all zone-mount photodetectors are then removed. The added auxiliary photodetectors are used by the controller to analyze the daylight variation. The experimental results show that up to 82% of the maximum number of photodetectors can be removed with zero error in the calculated maintained illuminance. Additionally, the Mean Absolute Error (ERMeanAb) of providing the desired maintained illuminance for the entire control system is lower than 23.6lx, when there are no photodetectors on zone surfaces. This research provides a novel platform of designing a smart indoor lighting system with application to different working environments.

Smart lighting system based on Bluetooth

A smart lighting system uses the concept of green, low-carbon, energy-saving and environmental protection to change people’s lifestyle and bring about high-quality life. This paper designs a smart lighting control system based on Bluetooth and Android. When the system is in automatic mode, the pyroelectric infrared sensor can be used to detect whether anyone is passing by to control the LED light on or off. The LED light can be also controlled by the Android app through Bluetooth communication when the system is in manual mode. The testing results show that the system is energy-saving, efficient and easy-to-use, and it can be widely used in various lighting scenes.

Performance analysis of smart lighting control system for sustainable campus operation

Performance analysis of smart lighting control system for sustainable campus operation

Control of Smart house sensors using Google Assistant

As a result of the research, a working model was created by smart home devices and the Internet of Things using a voice interface. Integrated Google Assistant, Dialogflow, PHP and MQTT. Voice interfaces are closely related not only to the use of smartphones, but also to wearable electronics, autonomous control, speaker speakers and even games. In turn, the Internet of Things today is not only a concept, but also a real movement with its technologies and protocols. Their variety and use of open technologies allows you to flexibly choose the tools for the project you need, taking into account its specifics. Smart lighting control systems are very popular because of the convenience of such solutions (remote on and off, increase and decrease brightness), the ability to collect and analyze data, the ability to make decisions depending on the ratio of external sensors and events. Google Assistant is an artificial intelligence-powered virtual assistant developed by Google that is primarily available on mobile and smart home devices. Unlike the company’s previous virtual assistant, Google Now, the Google Assistant can engage in two-way conversations. Dialogflow is a natural language understanding platform used to design and integrate a conversational user interface into mobile apps, web applications, devices, bots, interactive voice response systems and related uses. The ESP8266 is a low-cost Wi-Fi microchip, with a full TCP/IP stack and microcontroller capability, produced by Espressif Systems in Shanghai, China. The Message Queuing Telemetry Transport (MQTT) is a lightweight, publish-subscribe network protocol that transports messages between devices. The protocol usually runs over TCP/IP; however, any network protocol that provides ordered, lossless, bi-directional connections can support MQTT. It is designed for connections with remote locations where a «small code footprint» is required or the network bandwidth is limited.

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.

Development of Wireless Control System for Smart Street Lighting using ESP8266

In this paper, we report a smart street lighting control system using the ESP8266 which is a low-cost Wi-Fi chip with full TCP/IP stack and microcontroller capability. Our system is equipped with a web server developed in HTML code. Hence, our smart street lighting system can be controlled wirelessly to turn ON or turn OFF, and it can be monitored its environmental condition (i.e., temperature and humidity around the system). All sensors used in this system are pure digitally-outputted sensor: DHT11 to monitor the ambient temperature and humidity and BH1750 to adjust the street light intensity automatically. The dimming technique was applied in the control system by using Pulse Width Modulation (PWM). The system was divided into two main parts: Gateway and Node in which these two parts employ the ESP8266. The Gateway as a coordinator will send a message to the node as an end device (in this work, the streetlight act as a Node). Later, the node will send the ACK to the Gateway. As results, each node can send a message to other nodes.

Development and implementation of smart street lighting system based on LoRa Technology

This paper concerned with the development and implementation of smart street lighting control system based using Led lamp and Lora Wireless communication. Smart street lamps have been developed for over several years. These technologies have played an important role in urban safety, energy conservation. Currently, a traditional street lights are automatically turn on or off based on timer or day/night sensor. LEDs are now the standard replacement for legacy lighting in most cities around the world. At the same time, smart controls are becoming more mainstream and are increasingly installed alongside LED deployments. Recently, the conventional light sources are replaced by Led, which have so many advantages such as: energy savings, long lifetime, high reliability, pure light color, fast response, and friendliness to the environment. Furthermore, the intensity of the LED can be controlled easily. In this paper, the smart lighting system is designed to control and monitor devices via wireless transmission frequencies below 1 GHz. The system will include many types of devices connected to each other by a gateway. The transmit distance is about 2km in the urban area and up to 5km in rural area. The proposed smart street public lighting provides some advantages features such as: Automatic mode, Remote control mode, Connection disconnection mode, Manual direct operation mode. The smart lighting system has been built at Ho Chi Minh City University of Technology to meet the standards for data transmission. And some experimental resutls are provided to show the effectiveness of the porposed system.

Economical and Safe Design for Low-Traffic Long-Roads Illumination Control System by Using Image Recognition Technique

The paper covers analysis and investigation of lighting automation system in low traffic roads. The main objective is to provide optimal solution between expensive safe design utilizes continuous lighting at night for the complete road, or sacrifice the safety to minimize the cost of energy consumption by relying on using vehicles lighting in low traffic road designed without lighting systems. Each of these two scenarios is extremely significant issue and contradicting to each other from economic point of view. By taking into account both of these factors, smart lighting control system is proposed using Image Recognition Technique. In this proposal, the road is sectionalized into zones. By using motion sensors and Infra-Red cameras distributed and installed in each zone, any moving object can be detected and its image can be captured and analyzed using Image Recognition Technique to check whether the object is a vehicle or not. Matlab code is written and tested using different images to validate the code output. In case a vehicle is detected, the control system of the road lighting illuminates only the zone that the vehicle passes through. Economic analysis is provided in this paper to support the value of using this design of lighting control system. “Saving Norm” of $1,171.19/km/Year is calculated for the proposed system. This “Saving Norm” is a good index to supports project management for both project decision makers and for cash-flow controllers.

Sustainable Lighting-Retrofit Versus Dedicated Luminaires-Light Versus Power Quality

For the next few years millions of fluorescent luminaires will become waste and will be replaced by light-emitting diodes—LED luminaires. According to the Cost European Cooperation in Science & Technology Program, the next step will be shifting from sustainability to regeneration (enabling social and ecological systems to maintain a healthy state and to evolve); to reach this point, a is circular economy becomes necessary. The Technical University of Cluj-Napoca’s Lighting Engineering Laboratory—LEL—is the main lighting independent consultant in Transylvania (the north-west region of Romania). For the Building Services Faculty, LEL adopted different energy efficient lighting solutions to replace existing fluorescent T8 luminaires. The best available techniques were evaluated over the last few years. Out of a range of different smart lighting control systems, LED were chosen and used for retrofitting the existing T8 luminaires or simply replacing them with new dedicated LED luminaires. The study analyzed five different lighting setups for upgrading the existing fluorescent T8 2*36W luminaires. One setup used T5 lamps and the others used retrofitted or dedicated LED lighting solutions. First the lighting quantities of each setup were evaluated under real and experimental conditions. Second, a programable power source was used for measuring power quality indicators corelated with the provided lighting outputs, under different voltage values and waveforms. For each lighting setup, an even and odd current harmonic limit check was performed in line with class C—lighting equipment, IEC 61000-3-2 requirements. A new energy efficiency and power quality indicator was proposed—the lighting apparent power density [VA/sq.m/100lx].

Daylight and occupancy adaptive lighting control system: An iterative optimization approach

We consider a smart lighting control system for daylight and occupancy adaptation with illumination and dimming constraints. The lighting system has multiple luminaires, with co-located light and occupancy sensors, and a central controller. The sensors communicate local occupancy state and illuminance measurements to the central controller where dimming levels for the luminaires are optimized. We consider an optimization framework wherein the objective is to minimize the power consumption subject to illumination and dimming constraints. The illumination constraint is to achieve an illumination value at the light sensor that is above a specified set-point, depending on the occupancy state. The dimming constraints are to achieve a level of spatial uniformity in dimming levels of the luminaires within a neighbourhood, with the dimming levels being within physical limits. We propose an iterative method for optimization to determine the dimming levels that (i) does not require explicit daylight knowledge for every iteration, and (ii) induces smoother dimming level changes in luminaires. The proposed method and optimization framework is compared with existing approaches, in terms of achieved illumination and dimming values, in an open-plan office lighting model.