Reliable Integration of Neural Network and Internet of Things for Forecasting, Controlling, and Monitoring of Experimental Building Management System

In this paper, Internet of Things (IoT) and artificial intelligence (AI) are employed to solve the issue energy consumption in a case study an education laboratory. IoT enables deployment AI approaches establish smart systems manage sensor signals between different equipment based on decisions. As result, paper introduces design investigation experimental building management system (BMS)-based approach monitor status sensors control operation loads reduce consumption. The proposed BMS is built integration programmable logic controller (PLC), Node MCU ESP8266, Arduino Mega 2560 perform roles transferring processing data as well decision-making. employs variety sensors, including DHT11 sensor, IR smoke ultrasonic sensor. collected from temperature used build neural network (ANN) model forecast inside platform created by ThingSpeak platform, Bylink dashboard, mobile application. results show that can publish platforms. addition, demonstrate air-conditioning, lighting, firefighting, ventilation could be optimally monitored managed for with architectural design. Furthermore, prove ANN distinct forecasting process data.