Using decision tree for efficient data classification in Cyber-physical systems

Abstract

Applications of sensor networks to physical systems control can benefit directly from data mining techniques. This paper presents two approaches based on decision tree for event prediction in a Cyber-physical System. Special attention was paid to efficient resources management. The fist approach is a centralized solution validated through an application of temperature control for indoor spaces. The second one is based on results of the first approach and represents a study for a decentralized solution having an innovative design that improves efficiency. Tests are conducted using Monte Carlo simulation to cover various practical situations.