This thesis presents ’Sensato’, a common sense knowledge system with the objective
of helping the users in the development of Smart Home related tasks. This systems aims
to offer information about how are some elements used in Smart Home Automation tasks,
and give the necessary steps in order to complete that task, for the use of human beings
or other pieces of software. The system covers all the stages of the process, starting from
the knowledge acquisition, the extraction of the information contained on it, the adaptation
int a knowledge base and the development of a final agent. We will discuss in detail the
processing of the knowledge in order to fulfil our objectives, as well as the study of metrics
that will help us to measure the efficiency of our system.
In order to achieve such objectives, we will study some tools such as Ollie, ReVerb or
ConceptNet, among others, modifying them in order to satisfy our needs. We will also
develop new pieces of software to accomplish the goals defined.
This document shows the architecture of the proposed solution, as well as the detail
of the implementation of each module. Also, some example use cases of the platform are
shown, although the scope is not limited to them.