PLEIAData: consumption, HVAC, temperature, weather and motion sensor data for smart buildings applications

The current cost that energy represents is crucial in a field like climate control which has high energy demands, therefore its reduction must be prioritized. The expansion of ICT and IoT come with an extensive deployment of sensors and computation infrastructure creating an opportunity to analyze and optimize energy management. Data on building internal and external conditions is essential for developing efficient control strategies in order to minimize energy consumption while maintaining users' comfort inside. We here present a dataset that provides key features that could be useful for a wide range of applications in the context of modeling temperature and consumption via Artificial Intelligence algorithms. The data gathering has taken place for almost 1 year in the Pleiades building of the University of Murcia, which is a pilot building of the European project PHOENIX aiming to improve building energy efficiency.

Automated summary

The current cost of energy in the field of climate control is crucial and needs to be reduced. The expansion of ICT and IoT allows for the deployment of sensors and computation infrastructure, presenting an opportunity to optimize energy management. Data on building conditions is essential for developing efficient control strategies. Here, we present a dataset from the Pleiades building, collected for almost a year, which can be used for modeling temperature and consumption using AI algorithms.