The Internet-of-Things (IoT) domain area is expanding rapidly and the fast immersion in our daily activities is changing the perception of people’s life, not only from a technological perspective else in the way how we do personal activities, professional career and also in the way we establish social interactions. IoT is already considered as crucial in the process for designing the Future of the Digitised Society. It is expected IoT also will revolution our perception of the world enabling more smartness to the different external aspects of the human being activities and economic activity (cities, industries, agriculture, clothing, fashion, etc.), At the IoT unit we investigate the convergence of software systems, the semantic web and the Internet, heavily focused on the evolution of sensor technologies and the semantic technologies to unify the real and the virtual worlds.
The Internet of Things Laboratory, the main areas of interest at IoT-Lab are as follow:
- Internet of things Architecture, Systems and Applications.
- M2M communication and End-to-End System Solutions.
- Peer-to-Peer systems and Applications .
- Methods and Algorithms for Big Data, Collection and Transformation.
- Autonomics – Self-organisation and self-Management
- Cloud Computing Infrastructures and Management Platforms.
- Privacy and Security-Enabled Middleware Platforms.
Artificial intelligence (AI) is maturing and with the advance in computing systems the opportunities to improve the intelligence in the machines is expanding. Humans understand rapidly changing and use the perception to learn and comprehend daily events in physical and virtual lives, not only from a logic perspective but using complex reasoning tat drive us to generate new knowledge to invent and innovate. This human perspective is nothing else but singularity and identity in our personal human formation. Robotic Engineering Systems is already deployed in industry and it is considered as crucial area for the progress of humanity form an industrial perspective, we are in a transition where not only robots will assist, improve and minimise the load for a human, Robotic Systems will designing the Future in an intelligent manner and in a very reduced period of time that will provide enormous evolutive aspects for humanity. However It is expected AI and Robotics will promote a fast evolution, yet the perception of the world enabling more intelligence based on knowledge and analysis and considering the multiple and at the same time different external aspects (context awareness). At the IoT unit we contribute to evolve the state of the art on Robotics and the Programmatic ways to resolve Complex Operations to enable Machine Intelligence, we investigate the convergence of Programming Systems and Control, the semantic web technologies and the Interaction with Robots in a more natural way, the Automation and conduct innovation heavily focused on the evolution Control and Autonomy of Robotics systems with the sensor technologies to unify the real and the virtual worlds.
We are developing software technology for supporting the distributed complex operations that
Artificial Intelligent systems requires in order to be more efficient, we work on link data collisions of data to interconnect robotic systems for collaboration in industry, we are also looking at re-use interconnected legacy sensor networks and robotic sensors to enable more powerful base of information the feed the intelligent part of the robotic system performing better problem resolution and operation. We extensively dedicate time to study human perception and human brain using neural network principles to replicate the intelligent behaviour in machines. We also work on the security by design principles for device and robotics infrastructures, technologies for more natural and advanced human-computer interaction (HCI) and likewise the processing and protocol manipulation for robotics technology.
The AIRES Laboratory, the main focus areas in AIRES research are as follow:
- Cyber-Physical Systems, Robust and
Extensible Software Platforms.
- Neural networks and Stochastic Models
for re-inforced Learning and planning.
- Peer-to-Peer systems and Applications .
- Semi-Autonomus and Assisted Navigation.
- Control and programming techniques.
- Cognitive Patterns for Self-driven Robots.
- Human-Machine Awareness and Singularity.
- Access Control and Protection-Enabled