Machine learning (ML) has become an effective approach to enhance wireless sensor networks (WSNs) in the realm of Internet of Things (IoT). This paper reviews the effect of ML algorithms in this regard, focusing on energy-efficient routing protocols and data transmission optimization in IoT sensor networks. A secondary qualitative research methodology was adopted using existing literature in the area of how ML can enhance WSN. ML greatly increases network life and service efficiency towards realisation of industrial automation objective. But computational complexity and data quality are obstacles. Energy efficient ML models for scale and sustainability of IoT applications can be a future research area.