OverviewThe emergence of nontrivial embedded units mounting a rich sensor and actuator platform, sensor networks, the Internet of Things (IoT), pervasive and cyber-physical systems has made possible the design of sophisticated applications where large amounts of real-time data are collected to constitute a “big data” picture as time passes. Intelligence, adaptation through learning, neural and neuromorphic systems, cognitive fault tolerance and healing abilities constitute some key mechanisms needed to boost the future generation of intelligent systems and derived applications.
TopicsThe special session aims at gathering scholars and practitioners addressing those research topics and applied problems that the interaction of intelligent systems with the real world is requesting.
Papers must present original work, applications or review the state-of-the-art in the following non-exhaustive list of topics:
- Intelligent devices and solutions for the Internet of things
- Cognitive Sensor Networks
- Neural and neuromorphic Systems
- Intelligent Measurement Systems
- Incremental learning in cyber-physical and embedded systems
- Intelligent diagnosis and healing mechanisms
- Low level learning mechanisms for time invariant environments
- Intelligent sensors and robotics
- Intelligent systems for embedded applications
Relevance of the topicAlthough we experience an increasingly pervasive presence of embedded applications in our everyday life, such that by 2020 it is predicted that each person will possess between 5 and 10 embedded systems, the presence of intelligence in current versions of embedded devices is generally very basic, mostly confined to passive adaptation. Learning and cognitive mechanisms play a key role here to boost the next generation of embedded systems and applications.
Cesare Alippi (Italy)CESARE ALIPPI received the degree in electronic engineering cum laude in 1990 and the PhD in 1995 from Politecnico di Milano, Italy. Currently, he is a Full Professor of information processing systems with the Politecnico di Milano. He has been a visiting researcher at UCL (UK), MIT (USA), ESPCI (F), CASIA (RC), USI (CH). Alippi is an IEEE Fellow, Vice-President education of the IEEE Computational Intelligence Society (CIS), Associate editor (AE) of the IEEE Computational Intelligence Magazine, past AE of the IEEE-Trans Instrumentation and Measurements, IEEE-Trans. Neural Networks.
In 2004 he received the IEEE Instrumentation and Measurement Society Young Engineer Award; in 2011 has been awarded Knight of the Order of Merit of the Italian Republic; in 2013 he received the IBM Faculty Award.Current research activity addresses adaptation and learning in non-stationary environments and Intelligent embedded systems. He holds 5 patents and has published one monograph book published by Springer on "Intelligence for embedded systems", 6 edited books and about 200 papers in international journals and conference proceedings.
Manuel Roveri (Italy)MANUEL ROVERI received the Dr.Eng. degree in Computer Science Engineering from the Politecnico di Milano (Milano, Italy) in June 2003, the MS in Computer Science from the University of Illinois at Chicago (Chicago, Illinois, U.S.A.) in December 2003 and the Ph.D. degree in Computer Engineering from Politecnico di Milano (Milano, Italy) in May 2007.
Currently, he is an assistant professor at the Departent of Electroncis and Information of the Politecnico di Milano. His research interests include intelligent embedded systems, computational intelligence and adaptive algorithms. Manuel Roveri is an Associate Editor of the IEEE Transactions on Neural Networks and Learning Systems and served as chair and member in many IEEE subcommittees.
- Embedded systems
- Cyber-physical systems
- Intelligent applications
- Intelligent sensors
- Intelligence for sensor networks
- Neuromorphic systems
- Internet of Things
- Approximate computing
Further information and Paper submission can be found at the conference homepage: http://www.ijcnn.org/
Please make sure you select the correct Special Session in the submission process.