Ameliorating IoT and WSNs via Machine Learning

The dependence of everyday human life on smart devices is exponentially increasing. Wireless Sensor Networks (WSNs) and Internet of Things (IoT) are becoming of momentous importance every day. However, their challenges also increase with their evolution, and the urge for their improvement and continuous enhancement becomes more important. To adapt to such conditions, machine learning techniques are recently employed within WSNs and IoT systems to leverage their potential. This paper presents a survey of the use of machine learning-based algorithms in WSNs and IoT to deem numerous basic operation and performance constraints.