Lighting System Research Articles

Energy Performance Analysis of the Renovation Process in an Italian Cultural Heritage Building

Renovating buildings with cultural heritage significance is an important step toward achieving sustainability in our cities. The benefits are not only energy-related but also encompass social aspects that make these renovations a high apriority. The present work investigates the renovation process of a cultural heritage building in the Municipality of Trento in Italy, specifically focusing on achieving energy savings and renewable energy integration by implementing various renovation actions. These renovation actions include improvements to the building envelope, such as roof insulation and window replacements. Additionally, the renovation actions for active systems involve the installation of a ground-source heat pump for heating/cooling coupled with a borehole thermal energy storage system, which is an innovative technology for the renovation of cultural heritage buildings. The electrical systems of the building are upgraded through the addition of standard rooftop photovoltaics, innovative building-integrated photovoltaics (shingles), and the installation of an LED lighting system. The baseline and the renovation scenarios are studied using the dynamic simulation tool INTEMA.building, written in the programming language Modelica. This tool simulates both the building envelope and the energy systems with a high level of detail, using advanced control systems and adjustable time steps. According to the simulation analysis, the primary energy demand is reduced by 30.49%, the final energy demand by 36.74%, and the net electricity demand by 8.72%. Results from this study can be useful to interested stakeholders (e.g., building owners, architects, construction companies, public agents, and urban planners) dealing with the renovation of cultural heritage and protected buildings. Also, the results can be exploited for estimating energy savings by applying advanced renovation strategies for cultural heritage buildings.

An active-bending sheltered pathway based on bamboo strips for indoor temporary applications: Design and construction

This study explores the feasibility of employing bamboo strips to create an innovative sheltered pathway designed for indoor temporary applications. The primary design objectives encompass the development of a lightweight structure to conserve materials, ease of installation, and the use of sustainable, environmentally friendly materials. Additionally, the study places a significant emphasis on creating a structural system that can be conveniently disassembled, occupying minimal space for easy transport. The research initiative commences by investigating the mechanical properties of bamboo strips under active bending conditions, employing both bending and cantilever tests to evaluate their performance. Subsequent numerical analyses are conducted using OpenSeesPy, utilizing elastic beam elements with a corotational geometric transformation to simulate the mechanical behavior of bamboo strips. These numerical simulations are then compared with experimental results, contributing to the validation of a mechanical model for the full active bending structure. This validated model is further employed to predict deformation status and stress distribution during the substantial deformations of bamboo strips. The Employing a Particle-Spring Assembly (PSA) model, the preliminary design seamlessly evolves from a 2D bamboo strips configuration to 3D structures, showcasing the final curved form inspired by the remarkable large deformation performance of bamboo strips. Finally, the validated model guides the design of three distinct prototypes of an active-bending sheltered pathway, progressively increasing in scale and complexity. The prototypes address challenges such as lateral stiffness and employ aluminum connections for enhanced performance. The stiffness of the final sheltered pathway prototype is simulated and validated through Finite Element Modeling (FEM) simulations in ABAQUS under diverse loading conditions. The ultimate prototype represents a full-scale module of the sheltered pathway, featuring a walkway, a shelter system constructed from transparent waterproof PVC fabric, and an LED strip-based lighting system. These initial designs and prototypes demonstrate promising performance and hold considerable potential for real-world applications, establishing them as a compelling subject of study.

Design of Intelligent Home Lighting System Based on Digital Twin Technology

This article proposes an innovative design concept for lighting systems using digital twin technology. The proposed system utilizes digital twins to construct virtual models and rapidly develop and improve lighting solutions in simulated environments. In addition, digital twin technology can monitor and predict the operational status of analysis systems in real time, thereby improving reliability and security. This article provides an overview of the architecture design of a digital twin lighting system, detailing the design of each module, and providing insights into the experimental results of optimizing system performance. The experimental results clearly emphasize the significant improvement in efficiency and overall performance of smart homes through the application of digital twin technology in lighting systems.

Analisa Analisa Pencahayaan dan Penghawaan Alami Pada Tourist Information Center (TIC) dan Market Ekonomi Kreatif

Abstract: Natural lighting and ventilation are seen as key elements in supporting environmental sustainability and enhancing occupants’ physical and psychological comfort. The analysis involved measuring light intensity, light distribution and natural ventilation strategies to achieve optimal indoor conditions. The use of natural energy source such as the sun and outside air supports the principle of sustainability in building design. This journal examines natural lighting and ventilation in Tourist Information Center (TIC) and Creative Economy Market buildings which is expected to provide in-depth insight into the effectiveness of natural lighting and ventilation systems. Recommendations for design improvements or enhancements are presented to improve energy efficiency, environmental quality, and user comfort at these locations. Keywords: natural lighting, natural ventilation

Fundamentals, Algorithms, and Technologies of Occupancy Detection for Smart Buildings Using IoT Sensors.

Smart buildings use advanced technologies to automate building functions. One important function is occupancy detection using Internet of Things (IoT) sensors for smart buildings. Occupancy information is useful information to reduce energy consumption by automating building functions such as lighting, heating, ventilation, and air conditioning systems. The information is useful to improve indoor air quality by ensuring that ventilation systems are used only when and where they are needed. Additionally, it is useful to enhance building security by detecting unusual or unexpected occupancy levels and triggering appropriate responses, such as alarms or alerts. Occupancy information is useful for many other applications, such as emergency response, plug load energy management, point-of-interest identification, etc. However, the accuracy of occupancy detection is limited by factors such as real-time occupancy data, sensor placement, privacy concerns, and the presence of pets or objects that can interfere with sensor reading. With the rapid development of IoT sensor technologies and the increasing need for smart building solutions, there is a growing interest in occupancy detection techniques. There is a need to provide a comprehensive survey of these technologies. Although there are some exciting survey papers, they all have limited scopes with different focuses. Therefore, this paper provides a comprehensive overview of the current state-of-the-art occupancy detection methods (including both traditional algorithms and machine learning algorithms) and devices with their advantages and limitations. It surveys and compares fundamental technologies (such as sensors, algorithms, etc.) for smart buildings. Furthermore, the survey provides insights and discussions, which can help researchers, practitioners, and stakeholders develop more effective occupancy detection solutions for smart buildings.

Retraction Note: evaluating the environmental impact and economic practicability of solar home lighting systems: a roadmap towards clean energy for ecological sustainability.

Retraction Note: evaluating the environmental impact and economic practicability of solar home lighting systems: a roadmap towards clean energy for ecological sustainability.

Pencahayaan Penghawaaan Buatan di Restoran

Heritage Restaurant is one of the eating places in Wonosobo Regency which is often visited by Wonosobo people from many groups, both families and young people. One of the things that makes this restaurant popular with many people is its strategic location and its cozy atmosphere. The influence that creates a cozzy atmosphere at the Heritage restaurant is by using lighting and ventilation which can influence the atmosphere and comfort of the restaurant users themselves. The activities of visitors and managers in restaurants, eating, gathering and serving food, are greatly influenced by the existing lighting. Lighting can give different impressions and effects according to the type and application of the existing lights. Lighting can also provide its own characteristics following the theme and style applied to the interior. With descriptive analysis, this research was carried out to see the influence of the lighting system on certain effects or impressions in accordance with existing comfort standards at the Heritage restaurant, using observation and data collection (measurement) methods, so that researchers can obtain the results of a study of the application of artificial lighting in the interior of the Heritage restaurant. which is on Jl. A. Yani No.127, East Wonosobo, Wonosobo Tim., Kec. Wonosobo, Wonosobo Regency, Central Java 56317.

The optimal algorithm for eliminating nonlinear error in phase measurement profilometry based on global statistical phase feature function

In a digital fringe projection structured light system, the nonlinear phase error is generated by the gamma effect of both the projector, camera, and other electronic devices. One of the existing nonlinear correction methods is active correction by projecting ideal fringes as far as possible, and the other is passive compensation after capturing aberrant fringes. The former has higher accuracy but needs to capture a large number of fringe patterns, while the latter does not need many fringe patterns, but is not only greatly affected by random noise and out-of-focus effects, but also has poor accuracy. In this paper, an optimal algorithm for eliminating nonlinear error based on global statistical phase feature function (GSPF) is proposed. The phase distribution can be estimated from the difference between the global cumulative distribution function (CDF) and the normalized (CDF). For an ideal fringe pattern without nonlinear error and a fringe pattern with nonlinear error, the region wrapped by the x-axis normalized CDF is much smaller than the region wrapped by the x-axis global CDF, and the larger the nonlinear error is, the larger the difference between the two is. Therefore, the GSPF can be used for nonlinear error correction. Then the optimal nonlinear error correction is performed based on the minimum difference between the compensated phase entropy and the ideal phase entropy. The method does not require too many steps of phase-shifting, and only three fringe patterns are needed to realize accurate and robust correction. Experimental results show that the method is fast, highly accurate and robust. Using this technique, high accuracy measurements can be achieved with the traditional three-step phase-shifting algorithm.

Pixelwise calibration method for a telecentric structured light system.

This paper introduces a pixelwise calibration method designed for a structured light system utilizing a camera attached with a telecentric lens. In the calibration process, a white flat surface and a flat surface with circle dots serve as the calibration targets. After deriving the properties of the pinhole projector through a conventional camera calibration method using circle dots and determining the camera's attributes via 3D feature points estimation through iterative optimizations, the white surface calibration target was positioned at various poses and reconstructed with initial camera and projector calibration data. Each 3D reconstruction was fitted with a virtual ideal plane that was further used to create the pixelwise phase-to-coordinate mapping. To optimize the calibration accuracy, various angled poses of the calibration target are employed to refine the initial results. Experimental findings show that the proposed approach offers high calibration accuracy for a structured light system using a telecentric lens.

Firmware Updates over the Air via LoRa: Unicast and Broadcast Combination for Boosting Update Speed.

The capacity to update firmware is a vital component in the lifecycle of Internet of Things (IoT) devices, even those with restricted hardware resources. This paper explores the best way to wirelessly (Over The Air, OTA) update low-end IoT nodes with difficult access, combining the use of unicast and broadcast communications. The devices under consideration correspond to a recent industrial IoT project that focuses on the installation of intelligent lighting systems within ATEX (potentially explosive atmospheres) zones, connected via LoRa to a gateway. As energy consumption is not limited in this use case, the main figure of merit is the total time required for updating a project. Therefore, the objective is to deliver all the fragments of the firmware to each and all the nodes in a safe way, in the least amount of time. Three different methods, combining unicast and broadcast transmissions in different ways, are explored analytically, with the aim of obtaining the expected update time. The methods are also tested via extensive simulations, modifying different parameters such as the size of the scenario, the number of bytes of each firmware chunk, the number of nodes, and the number of initial broadcast rounds. The simulations show that the update time of a project can be significant, considering the limitations posed by regulations, in terms of the percentage of airtime consumption. However, significant time reductions can be achieved by using the proper method: in some cases, when the number of nodes is high, the update time can be reduced by two orders of magnitude if the correct method is chosen. Moreover, one of the proposed methods is implemented using actual hardware. This real implementation is used to perform firmware update experiments in a lab environment. Overall, the article illustrates the advantage of broadcast approaches in this kind of technology, in which the transmission rate is constant despite the distance between the gateway and the node. However, the advantage of these broadcast methods with respect to the unicast one could be mitigated if the nodes do not run exactly the same firmware version, since the control of the broadcast update would be more difficult and the total update time would increase.

A Fuzzy Based Intelligent Traffic Light Control (ITLC) Method: An Implementation in Ankara City

The escalating global population and increased vehicle usage have worsened traffic congestion in metropolitan areas, a significant urban challenge. Addressing this, adaptive traffic light control methods, especially at intersections, are being developed to improve traffic flow and reduce waiting times. This study significantly contributes to this field by implementing Fuzzy Logic in intelligent traffic light systems, focusing on Ankara's Polatlı Refik Cesur intersection. Using the SUMO simulation platform and Python programming, it analyzed waiting times and queue lengths. The initial phase used queue length for each intersection arm as an input. Fuzzy logic rules then determined the output, prioritizing street or phase order for optimal flow. The study further proposed an Adaptive Neuro-Fuzzy Inference System (ANFIS)-based control plan. ANFIS merges neural network capabilities with fuzzy logic, using waiting time and queue length as inputs to regulate the green light duration. Compared to existing traffic systems, this model showed a substantial improvement. It achieved a 36.5% reduction in waiting times, underlining the efficiency of the Fuzzy Logic-based method. This approach not only enhances traffic management but also contributes significantly to the literature on intelligent traffic light control systems. By addressing key urban traffic issues, the study paves the way for future advancements in traffic management technologies. The findings highlight the potential of combining advanced computational methods, like ANFIS, with traditional traffic control techniques to optimize urban traffic flow, offering a blueprint for similar challenges in other metropolitan areas.

The system of headlights operation recognition using the digital twin method

Virtual digital representation of a physical object or system, created with precision through computer simulations, data analysis, and various digital technologies can be used as training set for real life situations. The principal aim behind creating a virtual representation is to furnish a dynamic, data-fueled, and digital doppelgänger of the physical asset. This digital counterpart serves multifaceted purposes, including the optimization of performance, the continuous monitoring of its well-being, and the augmentation of informed decision-making processes. Main advantage of employing a digital twin is its capacity to facilitate experimentation and assessment of diverse scenarios and conditions, all without impinging upon the actual physical entity. This capability translates into substantial cost savings and superior outcomes, as it allows for the early identification and mitigation of issues before they escalate into significant problems in the tangible world. Within our research endeavors, we've meticulously constructed a digital twin utilizing the Unity3D software. This digital replica faithfully mimics vehicles, complete with functioning headlamp toggles. Our lighting system employs polygons and normal vectors, strategically harnessed to generate an array of dispersed and reflected light effects. To ensure realism, we've meticulously prepared the scene to emulate authentic road conditions. For validation and testing, we integrated our model with the YOLO (You Only Look Once) neural network. A specifically trained compact YOLO model demonstrated impressive capabilities by accurately discerning the status of real vehicle headlamps. On average, it achieved an impressive recognition probability of 80%, affirming the robustness of our digital twin.

Enhancing spectral efficiency with low complexity filtered‐orthogonal frequency division multiplexing in visible light communication system

AbstractThe filtered‐orthogonal frequency division multiplexing (F‐OFDM) scheme has gained attention as a promising solution in the field of visible light communication (VLC) systems. One crucial aspect in VLC is the conversion of the complex F‐OFDM signal into a real signal that corresponds with direct detection and intensity modulation. Traditionally, achieving a real F‐OFDM signal has involved imposing Hermitian symmetry (HS) on the samples of the Inverse Fast Fourier transform (IFFT), which requires 2N‐point IFFT and obtains an N‐point FFT, thus adding complexity. In this study, a novel approach is presented and implemented, aiming to enhance spectral efficiency and reduce system complexity by generating a real F‐OFDM signal without relying on HS. This approach is then compared with HS‐free (HSF)‐OFDM, direct current biased optical OFDM, and asymmetrically clipped optical OFDM. The suggested method offers a remarkable improvement of ~50% in the required IFFT/FFT volume. Consequently, this method reduces hardware complexity and power usage compared with the traditional F‐OFDM method. Moreover, regarding error rates, the proposed method demonstrates better spectral efficiency than HSF‐OFDM.

Combining multi-agent deep deterministic policy gradient and rerouting technique to improve traffic network performance under mixed traffic conditions

In the future, mixed traffic flow will include two types of vehicles: connected autonomous vehicles (CAVs) and human-driven vehicles (HDVs). CAVs emerge as new solutions to disrupt the traditional transportation system. This new solution shares real-time data with each other and the roadside units (RSU) for network management. Reinforcement learning (RL) is a promising approach for traffic signal management in complex urban areas by leveraging information gathered from CAVs. In particular, coordinating signal management at many intersections is a critical challenge in multi-agent reinforcement learning (MARL). According to this vision, we propose an approach that combines an actor–critic network–based multi-agent deep deterministic policy gradient (MADDPG) model and a rerouting technique (RT) to increase traffic performance in vehicular networks. This algorithm overcomes the inherent non-stationary of Q-learning and the high variance of policy gradient (PG) algorithms. Based on centralized learning with decentralized execution, the MADDPG model employs one actor and one critic for each agent. The actor network uses local information to execute actions, while the critic network is trained with extra information, including the states and actions of other agents. Through a centralized learning process, agents can coordinate with each other, diminishing the influence of an unstable environment. Unlike previous studies, we not only manage traffic light systems but also consider the effect of platooning vehicles on increasing throughput. Experimental results show that our model outperforms other models in terms of traffic performance in different scenarios.

Spatial efficiency: An outset of lighting application efficacy for indoor lighting

Electric lighting plays a critical role in buildings, not only impacting the well-being, satisfaction, and performance of building occupants but also accounting for a significant portion of energy consumption. The commonly used efficiency metrics for lighting, such as luminous efficacy or lighting power density, fall short of quantifying the effective light in architectural spaces. To address the shortcomings of existing efficiency measures, lighting application efficacy that characterizes the efficient delivery of light from the source to the target should be utilized. Lighting application efficacy can account for efficiencies in temporal, electrical, sensory, and spatial dimensions. This study outlines a method to quantify the spatial efficiency of electric lighting in buildings. As proof of concept, simulated spatial efficiency data are analyzed for two targets (horizontal work plane level and occupant field of view) based on the primary characteristics of the built environment and lighting systems. The findings indicate that design variables (e.g., room size, luminaire distribution type, reflectance of the surfaces, and field of view) can significantly affect the spatial efficiency of lighting in the specified settings. Therefore, spatial efficiency values can exhibit considerable variation among distinct lighting systems and architectural spaces and should be customized to suit the unique requirements of each design setting. Future research will investigate and establish the complementary components of the lighting application efficacy framework.

Anomaly detection in Smart Traffic Light system using blockchain: Securing through proof of stake and machine learning

<p>The Smart Traffic Light system plays a crucial role in smart cities, contributing significantly to enhancing the overall urban living standards, supporting sustainable practices, assuring public safety, and optimizing operational efficiency. Smart lighting systems leverage advanced technology such as the Internet of Things (IoT), data analytics, and networking to construct a complex and flexible lighting infrastructure. Anomalies within the context of a Smart Light system’s data pertain to patterns, events, or behaviors that are unexpected or uncommon, displaying a considerable deviation from the system’s typical operational state. The distributed and tamper-resistant ledger of blockchain technology renders it well-suited for maintaining an open and immutable record of data and events pertaining to smart lighting systems. The integration of blockchain technology and anomaly detection techniques enables the establishment of a resilient and reliable smart lighting system. The primary objective of this study is to investigate the application of the Isolation Forest algorithm for anomaly detection and its enhancement through the implementation of Proof of Stake for enhanced security measures. The Isolation Forest algorithm is utilized for anomaly prediction and evaluation of accuracy and precision. This is achieved by employing synthetic ground truth labels. Subsequently, the non-anomalous data is incorporated into the system as blocks using blockchain technology. The experimentation involves the use of synthetic numerical data derived from a dataset accessible on Kaggle. This process is conducted in two distinct phases. The first phase focuses on the analysis of synthetic numerical data, specifically targeting the identification of anomalies, prior to the implementation of blockchain technology. In the second phase, the same technique is applied to the synthetic numerical data following the integration of blockchain technology. Various machine learning (ML) models were utilized to analyze the data, resulting in improved accuracy from 48% to 94%, as evidenced by the validation of the obtained results. The empirical results indicate that the utilization of blockchain technology in data processing leads to an improvement in accuracy. Furthermore, the random forest algorithm exhibits robust performance when integrated with blockchain technology.</p>

Optimizing SNR for indoor visible light communication by using TLBO algorithm

This article explores the selection of Communication Light-Emitting Diodes (C-LEDs) in a multiuser indoor visible light communication system. It is aimed to obtain uninterrupted and quality communication by selecting appropriate communication LEDs depending on the location of the users. In indoor visible light communication, the data from a group of C-LEDs reach the receiver through multiple transmission paths directly or as a result of reflections. Inter-symbol interference occurs due to these multiple transmission paths. As a result, the signal-to-noise ratio and the communication quality decrease. In this study, to guarantee a low bit error rate and high enough signal-to-noise ratio values for all users, a Teaching-Learning Based Optimization algorithm based on a valid rate threshold was used for selecting communication LEDs for the first time. The simulation results showed that the Teaching-Learning Based Optimization algorithm is suitable to improve the signal-to-noise ratio. Also, the time required to select the communication LEDs was shortened by determining the appropriate valid rate threshold value. When the Teaching-Learning Based Optimization algorithm was compared with other metaheuristic optimization algorithms used in the literature, it was seen that a better signal-to-noise ratio was obtained with lower iteration and population number.

A Coupled Calibration Method for Dual Cameras-Projector System with Sub-Pixel Accuracy Feature Extraction.

Binocular structured light systems are widely used in 3D measurements. In the condition of complex and local highly reflective scenes, to obtain more 3D information, binocular systems are usually divided into two pairs of devices, each having a Single Camera and a Projector (SCP). In this case, the binocular system can be seen as Dual Cameras-Projector (DCP) system. In the DCP calibration, the Left-SCP and Right-SCP need to be calibrated separately, which leads to inconsistent parameters for the same projector, thus reducing the measurement accuracy. To solve this problem and improve manoeuvrability, a coupled calibration method using an orthogonal phase target is proposed. The 3D coordinates on a phase target are uniquely determined by the binocular camera in DCP, rather than being calculated separately in each SCP. This ensures the consistency of the projector parameters. The coordinates of the projector image plane are calculated through the unwrapped phase, while the parameters are calibrated by the plane calibration method. In order to extract sub-pixel accuracy feature points, a method based on polynomial fitting using an orthogonal phase target is exploited. The experimental results show that the reprojection error of our method is less than 0.033 pixels, which improves the calibration accuracy.

Insights from a single centre implementation of a digitally-enabled atrial fibrillation virtual ward.

Atrial fibrillation (AF) is the most prevalent cardiac arrhythmia and poses a significant public health burden. Virtual wards are a novel approach utilising digital solutions to provide hospital-level care remotely; their rollout has become a key priority for the UK National Health Service to expand acute care capacity. We devised and implemented a digitally-enabled AF virtual ward to monitor patients being established onto medical therapy following an AF diagnosis or an AF-related hospitalisation. Patients were onboarded either as outpatients to avoid admission or on discharge after an acute AF hospitalisation. Remote monitoring was undertaken using a clinically validated photoplethysmography-based smartphone app. Over a 1-2 week period, patients performed twice daily measurements of heart rate and rhythm and provided corresponding symptoms. A traffic light system guided frequency of telephone assessments by specialist practitioners. Red flag symptoms or abnormal heart rate parameters prompted an urgent care escalation. We report our experience of the first 73 patients onboarded to the AF virtual ward from October 2022 to June 2023 (mean age 65 years, median 68 years, IQR range 27-101 years; 33 females). Thirty-nine (53%) patients had red flag features requiring care escalation, of whom 9 (23%) were advised to attend ED (emergency department) for urgent assessment, 10 (26%) attended for expedited review and 14 (36%) required medication changes. By 3 months post-monitoring, only 3 patients (4%) had re-attended ED with an arrhythmia-related presentation. Virtual ward patients had an average 3-day shorter inpatient stay (mean duration 4 days) compared with AF patients hospitalised prior to virtual ward implementation (mean duration 7 days). Overall, 22 arrhythmia-related readmissions were prevented via the virtual ward model. In this study, we present a novel implementation of a digitally-enabled virtual ward for the acute management of patients with newly diagnosed or poorly controlled AF. Our pilot data indicate that this model is feasible and is potentially cost-effective. Further longitudinal study is needed to definitively evaluate long-term clinical utility and safety.

Traffic Light Control System

The traffic light control system is a key component of urban traffic management, and its performance directly impacts the smooth flow of traffic and traffic safety. Based on some issues existing in the current traffic signal control systems, this paper proposes a novel traffic light control system based on intelligent algorithms. This system combines artificial intelligence technology with traditional traffic signal control methods to achieve intelligent control of traffic signals, thereby enhancing traffic efficiency and road safety. The paper provides a detailed explanation of the system's design principles, algorithm implementation, and experimental results. Comparative experiments demonstrate that the system has significant advantages in reducing traffic congestion and improving vehicle passage efficiency. Finally, the paper discusses possible future improvement directions and application scenarios, envisioning the development prospects of traffic light control systems in the future.