International Technology Robotics Applications

Abstract

The efficient use of resources is a matter of great concern in today’s society. Specifically, power consumption has led to small networks that incorporate management systems, which are also being integrated in other networks that increasingly cover larger installations (homes and offices, buildings, districts, cities, etc.). From the natural evolution of the common services management, the concepts of Smart Grid and even Smart Cities have arisen strongly, pursuing the efficient management of resources, which is the strategic investment of these complex and smart systems. One of the biggest restrictions on setting up an intelligent environment is the lack of interoperability between different devices. In this context, the need to be able to identify the devices connected to the network will allow to automatically execute a software adapter that makes the device interact with the whole system in a standard way. Achieving that objective could also bring other positive consequences, such as being able to anticipate energy demand. Based on the idea that the amount of consumption data is large and is increasing, the suitability of using big data techniques to handle this information, combined with automatic machine learning techniques to extract value from such a large amount of data, is proposed in this work in progress.