A Review on Internet of Things Solutions for Intelligent Energy Control in Buildings for Smart City Applications

A smart city exploits sustainable information and communication technologies to improve the quality and the performance of urban services for citizens and government, while reducing resources consumption. Intelligent energy control in buildings is an important aspect in this. The Internet of Things can provide a solution. It aims to connect numerous heterogeneous devices through the internet, for which it needs a flexible layered architecture in which the things, the people and the cloud services are combined to facilitate an application task. Such flexible IoT hierarchical architecture model will be introduced in this paper with an overview of each key component for intelligent energy control in buildings for smart cities

A Review on Internet of Things Solutions for Intelligent Energy Control in Buildings for Smart City Applications

© 2017 The Authors. A smart city exploits sustainable information and communication technologies to improve the quality and the performance of urban services for citizens and government, while reducing resources consumption. Intelligent energy control in buildings is an important aspect in this. The Internet of Things can provide a solution. It aims to connect numerous heterogeneous devices through the internet, for which it needs a flexible layered architecture where the things, the people and the cloud services are combined to facilitate an application task. Such flexible IoT hierarchical architecture model will be introduced in this paper with an overview of each key component for intelligent energy control in buildings for smart cities

The design of an indirect method for the human presence monitoring in the intelligent building

This article describes the design and verification of the indirect method of predicting the course of CO2 concentration (ppm) from the measured temperature variables Tindoor (degrees C) and the relative humidity rH(indoor) (%) and the temperature T-outdoor (degrees C) using the Artificial Neural Network (ANN) with the Bayesian Regulation Method (BRM) for monitoring the presence of people in the individual premises in the Intelligent Administrative Building (IAB) using the PI System SW Tool (PI-Plant Information enterprise information system). The CA (Correlation Analysis), the MSE (Root Mean Squared Error) and the DTW (Dynamic Time Warping) criteria were used to verify and classify the results obtained. Within the proposed method, the LMS adaptive filter algorithm was used to remove the noise of the resulting predicted course. In order to verify the method, two long-term experiments were performed, specifically from February 1 to February 28, 2015, from June 1 to June 28, 2015 and from February 8 to February 14, 2015. For the best results of the trained ANN BRM within the prediction of CO2, the correlation coefficient R for the proposed method was up to 92%. The verification of the proposed method confirmed the possibility to use the presence of people of the monitored IAB premises for monitoring. The designed indirect method of CO2 prediction has potential for reducing the investment and operating costs of the IAB in relation to the reduction of the number of implemented sensors in the IAB within the process of management of operational and technical functions in the IAB. The article also describes the design and implementation of the FEIVISUAL visualization application for mobile devices, which monitors the technological processes in the IAB. This application is optimized for Android devices and is platform independent. The application requires implementation of an application server that communicates with the data server and the application developed. The data of the application developed is obtained from the data storage of the PI System via a PI Web REST API (Application Programming Integration) client.Web of Science8art. no. 2

A presence-based control strategy solution for HVAC systems

International audienceThis paper presents an energy-saving control solution which has been developed for existing public buildings by designing an intelligent ICT-based service system for monitoring and controlling the environmental conditions. The proposed control strategy addresses the required infrastructure and implements the design to properly balance energy savings and comfort issues. In this work, a combination of occupancy detection and daylight harvesting is presented as input to the control algorithm. The implemented results presented here utilize the hardware and software on a pilot campus and achieve an average energy saving of 71% for three sample days during summer times. Simulation results are also presented for annual period and complete test case building