Special Issue on Artificial Intelligence for Distributed Smart Sensing
• 大类 : 工程技术 - 3区
• 小类 : 计算机：人工智能 - 3区
The goal of Artificial Intelligence (AI) is to reproduce biological intelligence in the form of adaptive machines.
The path towards this goal is characterized by several steps, among which the integration of the AI with Smart Sensors (SS) is fundamental. SS and, more generally, Smart Cyber Physical Systems are nowadays significantly impacting the everyday life of citizens and, in perspective, they will become pervasive in every aspect of human life from public health and well-being to home, infrastructures and environment management.
It is only thanks to the integration of AI and SS that computers can increasingly see, hear, touch, smell and taste and so become aware and capable to positively interact with the environment in which they are deployed.
The research activity (industrial and scientific) in AI is still very fragmented. In fact the development of an intelligent system capable of dealing with all the senses and adapting to different contexts is still relatively far. Furthermore, the results obtained on different sensing areas are still very unbalanced.
Indeed, the obtained results are impressive for some senses and weak for the others. Into the first category it is possible to include sight (with vision systems made by large companies and research institutes), hearing (with the speech to text systems of many devices for everyday use) and the more general "comprehension".
For the other senses, much more work remains to be done: touch sensors are little more than devices able to understand if "I’m touching something", whereas on smell and taste there is still much to be done.
Another important issue is related to the possibility of exploiting collaborative approaches through Distributed Architectures. In this kind of applications, SS are spread into the environment of interest where some kind of “social intelligence” is generated. Many applications of such an architecture are possible in smart cities, smart industries, smart buildings, etc.
The improvements will necessarily have to take place at different levels: physical (sensors with increased discriminatory capabilities, robustness and stability), data processing (sensors equipped with electronics for signal conditioning in order to make them "informative"), data communication (sensors equipped with different solutions for sending/receiving data following for example the IoT paradigm) and, finally, understanding the data (with AI).
The aim of this Special Issue is to bring together academics and industrial practitioners to exchange and discuss the latest innovations and applications of AI in the domain of SS and DSS.
- Wired and wireless solutions
- New sensor technologies
- Internet of Things
- Computer Vision
- Natural Language processing
- Deep and Reinforcement Learning
- Ontology solutions
- Sensor Network
- Critical applications
- Soft Computing
- Computational Intelligence
- Neurocomputing/Neural Systems
- Case studies
- Multimedia Learning
- Classification and clustering algorithms for DSS.
- Solutions for Industry 4.0 (energy, logistics, optimization, ...)