Paper 27 (Research track)

Supporting the Interpretation of Predictive Models results with Semantic Technologies

Author(s): Iker Esnaola-Gonzalez, Jesús Bermúdez, Izaskun Fernandez, Aitor Arnaiz

Abstract: Thermal comfort in tertiary buildings not only has a direct impact on occupants health, morale and satisfaction, but also in their working efficiency and productivity. Therefore, there is a need to establish HVAC (Heating, Ventilation and Air Conditioning) control strategies that ensure comfortable thermal situations in these environments. Since Predictive Models are used to forecasting, they are suitable to identify adequate HVAC control strategies that will ensure thermal comfort within a building in advance. This paper makes use of Semantic Technologies to interpret results obtained from Predictive Models and aids facility managers choosing the most adequate HVAC control strategies in advance. The proposed approach is applied in a real use case and compares obtained outcomes with an already existing solution. Results show that the proposed solution is more scalable, simple and flexible, easing the results interpretation and decision making tasks, as well as opening new possibilities for automatizing the HVAC control strategy selection.

Keywords: Semantic Technologies; Interpretation; Predictive Models; Thermal Comfort

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