This comprehensive review explores the integration of biosensors with multi-hop IoT systems via cloud connectivity, focusing on real-time remote patient monitoring. The paper highlights the strategic deployment of biosensors in medical facilities, connected to microcontrollers, to form robust multi-hop IoT networks. Cloud connectivity is emphasized as a critical component, providing secure and scalable platforms for remote patient monitoring. The integration of biosensors, such as ECG and heart rate/pulse oximeter biosensors, with multi-hop IoT systems enhances data transmission and reliability. The paper discusses the architectural and design considerations, including scalable and modular architecture, edge computing, and dynamic routing algorithms. It also covers node configuration, communication protocols, and routing node configuration, detailing the use of microcontrollers like the ESP32-WROVER-E and the integration of biosensors with these devices. The review underscores the transformative potential of this integration in overcoming traditional healthcare limitations and improving patient care through real-time remote monitoring.This comprehensive review explores the integration of biosensors with multi-hop IoT systems via cloud connectivity, focusing on real-time remote patient monitoring. The paper highlights the strategic deployment of biosensors in medical facilities, connected to microcontrollers, to form robust multi-hop IoT networks. Cloud connectivity is emphasized as a critical component, providing secure and scalable platforms for remote patient monitoring. The integration of biosensors, such as ECG and heart rate/pulse oximeter biosensors, with multi-hop IoT systems enhances data transmission and reliability. The paper discusses the architectural and design considerations, including scalable and modular architecture, edge computing, and dynamic routing algorithms. It also covers node configuration, communication protocols, and routing node configuration, detailing the use of microcontrollers like the ESP32-WROVER-E and the integration of biosensors with these devices. The review underscores the transformative potential of this integration in overcoming traditional healthcare limitations and improving patient care through real-time remote monitoring.