Fuzzy logic controller for energy savings in a smart LED lighting system considering lighting comfort and daylight

A Review of the Recent Developments in Integrating Machine Learning Models with Sensor Devices in the Smart Buildings Sector with a View to Attaining Enhanced Sensing, Energy Efficiency, and Optimal Building Management

“…With respect to the publication year, 63% of the identified articles were published during the last 5 years. The authors of these scientific articles made use in their analyses of different types of sensors, including sensors and actuators related to the primary heating circuits and power generation systems [24]; telecare medicine information systems (TMIS) comprising specialized sensors that provide key health data parameters [99]; distributed sensors [100]; temperature, humidity and flame sensors [101]; string-type strain gauges [49]; temperature and occupancy sensors [54]; wireless sensors [47,102]; environment sensors for measuring indoor illuminance, temperature-humidity, carbon dioxide concentration and outdoor rain and wind direction [103]; sensors for measuring the indoor and outdoor temperature and the humidity [39]; vision sensors [55]; sensor networks [56,104]; binary infrared sensors [83]; motion detectors, light sensors, meteorological sensors for the wind and solar radiation data [105]; light and motion sensors [106]; environmental sensors [107]; in-house and city sensors [108]; meteorological stations [46]; smart home sensors, remote monitoring systems, and data and video review systems [102]; temperature and infrared sensors [109]; temperature sensors [110]; inside and outside home sensors [111]; different sensors and effectors [112]; smart systems for controlling the vibration of building structures by means of smart dampers [113]; virtual sensor based on a fisheye video camera [48]; and indoor and outdoor light sensors [114]. In these papers, the reasons for using the Fuzzy C-Means with the sensor devices in smart buildings were mainly related to monitoring and controlling energy management processes [24,39,46,47,…”

“…The performance metrics considered in the scientific papers that use the Fuzzy C-Means integrated with sensor devices in smart buildings were evaluated based on experiments and simulations [46,47,103,[107][108][109]111,114]; Root Mean Square Error (RMSE) [24]; computational cost, user anonymity, mutual authentication, off-line password guessing attacks, impersonation attacks, replay attacks, and the assurance of formal security [99]; Inaccuracy Rate, experiment environment dimension and Root-Mean-Square Error (RMSE), and the dependency of the localization approach on the number of wireless nodes (topology) employed to locate the objects [100]; Accuracy [101,110]; Coefficient of Determination (R 2 ) [49]; energy consumption, Electricity Cost, Peak-to-Average Ratio (PAR) [54]; energy saving percentage in different working scenarios [39]; Standard Error of Mean (SEM), Horizontal Illuminance, Daylight Glare Probability, paper-based Landolt test, Freiburg Visual Acuity Test (FrACT), Electric Lighting Energy Consumption, total number of shading and lighting commands [55]; turbulence intensity, draught rates, operative temperature, Predicted Mean Vote (PMV) and Percentage of People Dissatisfied (PPD) [56]; Identification Rate [83]; Energy Consumption and illumination level [105]; energy savings [106]; Detection Accuracy, Energy Consumption, Memory Consumption, Processing Time Estimation [104]; True Positive, False Positive, True Negative, False Negative, and Accuracy [102]; Accuracy and a comparison with the results presented in related works (based on Ultrasonic, Ultrasonic/RFID, ZigBee, Active RFID, Passive RFID) [112]; Fault Detection Index values for certain fault magnitudes, residual values for individual sensors corresponding to different fault magnitudes [113]; and comfort level [48].…”

A uniform lighting system using a webcam

“…В настоящее время существует несколько направлений по обеспечению качественного освещения. Первый подход -оптимизация размещения светодиодных светильников [10,11], второй подход -управление осветительных приборов [12][13][14][15]. При этом классическая схема управления основана на использовании датчиков освещенности, расположенных на рабочей поверхности [16].…”

A Group Approach of Smart Hybrid Poles with Renewable Energy, Street Lighting and EV Charging Based on DC Micro-Grid

“…Nowadays, energy crisis and environment pollution have become the global problem, and the increasing use of energy caused climate change. However, the renewable energy, clean energy, other distributed generation such as solar-based photovoltaic (PV) and wind generation, the use of light-emitting diode (LED) lighting [1][2][3], and new transport electric vehicle (EV) [4][5][6][7][8][9][10][11][12], positively contribute to the reduction of the carbon footprint of electricity generation.…”