Artificial Intelligence has been combined with many sensorc technologies, such as Digital Spectrometry by IdeaCuria Inc. which enables many applications such as at home water quality monitoring.
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.