As hardware is becoming smaller and sensors are getting cheaper, there is an increasing interest in how to effectively analyze huge collections of sensor data. Meanwhile, the emergence of machine learning has led to applications, which have a direct impact in our lives. In an attempt to provide accurate, in some occasions real-time, predictions even for noisy sensor datasets, machine learning models are widely implemented.
This Special Issue highlights developments in machine leaning methodologies able to tackle the various challenges arising when dealing with sensor data. The issue accepts both high-quality articles containing original research results and review articles and will allow readers to learn more about the potentials of machine learning applications in sensor data.
Prof. Dr. Vassilis Plagianakos
Dr. Sotiris Tasoulis