Artificial Intelligence and Machine Learning in Sensors Networks
A special issue of Sensors (ISSN 1424-8220). This special issue belongs to the section "Intelligent Sensors".
Deadline for manuscript submissions: closed (15 October 2018) | Viewed by 150104
Special Issue Editors
2. Air Institute, IoT Digital Innovation Hub, 37188 Salamanca, Spain
3. Department of Electronics, Information and Communication, Faculty of Engineering, Osaka Institute of Technology, Osaka 535-8585, Japan
Interests: artificial intelligence; smart cities; smart grids
Special Issues, Collections and Topics in MDPI journals
Interests: intelligent decision making; artificial intelligence; computational intelligence
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
At present, there is a growing number of solutions that provide Artificial Intelligence (AI) and Machine Learning (ML) based systems. These solutions facilitate the creation of new products and services in many different fields. Sensor networks (SNs) are undergoing great expansion and development and the combination of both AI and SNs are now realities that are going to change our lives. The integration of these two technologies benefits other areas such as Industry 4.0, Internet of Things, Demotic Systems, etc. Furthermore, sensor networks (SNs) are widely used to collect environmental parameters in homes, buildings, vehicles, etc., where they are used as a source of information that aids the decision-making process and, in particular it allows systems to learn and to monitor activity. New AI and ML real time or execution time algorithms are needed, as well as different strategies to embed these algorithms in sensors. New clustering and classification techniques, reinforcement learning methods, or data quality approaches are required, as well as distributed AI algorithms.
This Special Issue calls for innovative work that explores new frontiers and challenges in the field of applying AI algorithms to SNs. As mentioned previously, this work will include new machine learning models, distributed AI proposals, hybrid AI systems, etc., as well as case studies or reviews of the state-of-the-art.
The topics of interest include, but are not limited to:
- Artificial Intelligence models for Sensor Networks.
- Machine Learning models for Sensor Networks.
- Clustering and classification algorithms for SNs.
- Deep and reinforcement learning for SNs.
- Intelligence processing algorithms for SNs.
- Intelligence image processing algorithms for SNs.
- Big Data analytics for data processing from SNs.
- Fuzzy Systems proposals for SNs.
- Expert Systems for SNs.
- Hybrid Systems for SNs
- Intelligent real time algorithms for SNs.
- Intelligent execution time algorithms for SNs.
- Intelligent security proposals for WSNs.
- Blockchain in WSNs.
- Multi Agent Systems.
- Organization Based Multiagent Systems.
- Virtual Organizations.
- Applications of AI in SN domains: energy, IoT, Industry 4.0, etc.
Prof. Dr. Juan Manuel Corchado Rodríguez
Prof. Dr. Enrique Herrera
Guest Editors
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Keywords
- Machine Learning
- Artificial Intelligence
- Learning
- Fuzzy
- ANN
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