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Current research projects make use of android mobile development, computer vision, data mining, machine learning, and deep learning techniques to find solutions for problems in the areas of:

  • Automatic determination of the way a user is carrying a smartphone
  • Automatic user laterality detection by observing smartphone usage patterns
  • Biometrics using mobile device sensors
  • Evaluation of machine learning algorithms for image recognition from UAVs
  • SensDSL: A Domain-Specific Language to Automate Tasks that use Android Sensors
  • Ontology to represent public incidents and collaborative interface to manage them
  • Using the OBD II port to prevent vehicle accidents collectively and avoid inefficient ways of driving
  • Designing a metamodel and a domain-specific language to define the data to be extracted from the OBD II port in vehicles
  • Smart Nose for the administration of places using Artificial Intelligence
  • Predictive maintenance and quality control in 3D printing processes
  • Intelligent geolocated mobile robot which detect efficient locations to place mobile solar panels
  • Semantic integration of streaming data using RDF Data Shapes Detection of heart problems using low-cost mobile technology

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