The rapid expansion of the Internet of Things (IoT) in healthcare has introduced revolutionary advancements in patient care, enabling real-time monitoring, efficient diagnosis, and enhanced treatment protocols. Machine-to-Machine (M2M) communication within healthcare IoT networks serves as the backbone of this transformation, facilitating seamless data exchange between medical devices, healthcare professionals, and patients. challenges such as power consumption, resource constraints, security concerns, and scalability remain critical obstacles in the widespread adoption of M2M-based healthcare systems. This chapter explores the fundamentals of M2M communication, focusing on its role in scalable healthcare IoT networks, with an emphasis on the integration of low-power communication protocols, real-time data transmission, and device interoperability. The discussion extends to the real-world applications of M2M in critical healthcare services, including emergency medical systems, remote patient monitoring, and chronic disease management.the chapter delves into emerging trends, such as the use of artificial intelligence and edge computing, to address the limitations of current systems. Ultimately, it offers valuable insights into overcoming the technical barriers and optimizing M2M communication to enhance healthcare delivery.ÂÂ
The integration of Machine-to-Machine (M2M) communication in healthcare IoT (Internet of Things) networks has rapidly evolved from a theoretical concept to an essential infrastructure in modern healthcare systems [1]. M2M communication enables seamless data exchange between connected medical devices, healthcare professionals, and patients [2]. This data-driven communication framework has the potential to revolutionize the delivery of care by enabling real-time patient monitoring, automated diagnostics, and personalized treatment plans [3]. As the global healthcare industry embraces technological advancements, M2M communication was increasingly being adopted as a key enabler of scalable, efficient, and cost-effective healthcare services [4]. Its immense promise, the full potential of M2M communication in healthcare was hindered by various challenges that need to be addressed for its successful implementation [5].
A major benefit of M2M communication in healthcare IoT was the ability to enhance patient monitoring and decision-making [6]. With real-time data transmission from wearables, sensors, and diagnostic devices, healthcare professionals can receive continuous updates on patient health status, regardless of location [7]. Remote monitoring tools allow clinicians to track chronic conditions such as diabetes or heart disease in real-time, enabling them to make timely interventions before the situation worsens [8]. Emergency medical systems can benefit from M2M communication by allowing paramedics to send patient data to hospitals in real-time, improving preparedness and response times [9]. This constant flow of information reduces delays, improves accuracy in diagnosis, and ensures that patients receive appropriate treatment in critical moments [10].
