The SATRD (Sistemas y Aplicaciones en Tiempo Real Distribuido) group was founded in 1995. The group is part of the Communication Department of the Universitat Politècnica de València (UPV). It is composed of 2 professors and 22 researchers developing different activities related to the area of real-time systems with distributed nature and its applications, requiring for them a thorough knowledge of communications systems.
In the area of research projects, the SATRD group collaborates with national and international companies from different fields and sectors. The group has continuous participation in EC-funded R&D projects and in technology transfer where its involvement ranges from project coordination to technical coordination and development and contribution to real pilots. The group has a lot of expertise in coordination in European projects, both on work package and general project levels.
The group has two main research areas:
- Cyber security & Cyber intelligence. This area is specialized in command-and-control systems, virtual reality systems applied to emergency management training related to emergency management, interoperability of command-and-control systems, wireless tactical communications systems, homeland security-related applications, transfer applications content in IP networks, video streaming, QoE, wireless sensor networks, Sensor Web Enablement. This is a topic of great relevance to the cPAID project, where the previous expertise in cyber security helps in the tasks of Work Package 3, the WP lead by the UPV.
- IoT digitisation. This area specialises in IoT, Big Data, Machine Learning, innovative applications using 5G, sensors, data processing (where our experience with AIS and satellite data stands out), edge computing, and Cloud-Edge continuum. The SATRD has a deep understanding of the application of the latest technologies in different environments, which has resulted in multiple publications in journals and conferences of references (see publications section). Again the previous expertise, particularly in Machine Learning is of great help in the tasks of WP3.