In the current era, the e-communication technology is developing swiftly and has made a remarkable transformation in e-healthcare sector by facilitating efficient and secure transmission of patient’s data. Internet of Things (IoT) is developing drastically in the e-healthcare sector and the intelligent devices are also improving with many new innovative enhancements. The confluence of IoT and ML is manifested in many sectors but its implementation in e-healthcare sector provides real-time surveillance and monitoring of patient’s data and health status through prediction, anticipation and the capability of taking decisions intelligently. Nowadays, cryptographic and biometric systems, anomaly detection and machine learning (ML) approaches for authentication are being widely used for ensuring the security and functioning of healthcare systems. The present study aims to know how the convergence of IoT e-healthcare management system (EHMS) and ML techniques helps to design automated systems for proper monitoring and intelligent decision making. It also focuses to present an innovative architecture to safeguard the real-time healthcare from outside threats with the consumption of less possible resources of low-powered devices.