System of Prediction, Optimization and Detection of Users with the Use of Radio Tomography and Computational Intelligence Methods
Purpose: The objective of the article is to present a comprehensive building management system using radio tomography methods and computational intelligence methods. Design/Methodology/Approach: The system under development integrates a number of proprietary solutions with solution existing on the market, the best and most recent communication standards for IoT (Internet of Things) devices have been used, the software used allows for high scalability of the platform in the future, easy adaptation to various types of supported facilities, while remaining open to new integration with more and more popular solutions for servicing the Smart Home / Building market. Great emphasis was placed on the visualization on both tomographic solutions and presentation of the current state of the building equipped with a number of software and hardware solutions. Findings: The results of the research work indicate that created building system will optimize energy consumption through direct management of energy receivers as well as indirectly through appropriately adapted control algorithms taking into account many internal and external factors. Detection of people by means of radio tomography, automation adjusting the operation of devices to the environmental conditions of the building and individual rooms, prediction of behavior, appropriate visualizations and the ability to check the energy condition of the building. Practical Implications: The system can be used to analyze and predict the behavior of consumers in any larger facility equipped with standard comfort systems like lighting, heating, ventilation and air conditioning. Originality/Value: The created innovative system, thanks to the ability to accurately determine the position (RTI) and identification of a person (individual tags), will allow to manage building systems in an individual way.