Human Mobility Prediction With Region-Based Flows and Water Consumption

We are witnessing an increasing need to accurately measure people's mobility as it has become instrumental factor for the development of innovative services in multiple domains. In this context, several ICT solutions have relied on location-based technologies such GPS, WiFi or Bluetooth track individual's movements. However, these limited by privacy restrictions data providers. paper we propose a methodology robustly predict citizens' patterns based heterogeneous from different sources. Particularly, our focuses human predictor low-resolution dataset and use water consumption facilitator prediction task. As result, work explores whether within geographical region can reveal activity relevant point view mining discipline. This approach been tested residential area near Madrid (Spain) obtaining quite promising results.