Connected medical devices are multiplying fast, and so are the questions about how to keep them talking to each other safely. A comprehensive survey published in Discover Internet of Things pulls together evidence from more than 200 peer-reviewed publications to map the state of the medical Internet of Things, or IoMT, covering communication technologies, security frameworks, energy management, intelligent architectures and the emerging role of quantum-enabled approaches in healthcare. The review, authored by Abdelhamied A. Ateya, Mohammed ElAffendi and Mohamed Hammad, was published on 8 October 2026 as an open-access article.

The survey arrives amid remarkable market growth. The authors cite forecasts suggesting the global healthcare IoT/IoMT sector will reach 446.52 billion dollars by 2028, a compound annual growth rate of 25.9 percent from 2021 to 2028, driven by rising adoption of remote patient care and telemedicine. The COVID-19 pandemic acted as a significant catalyst, accelerating remote monitoring, telemedicine and automated health assessment systems. Yet the review stresses that considerable gaps remain in data security, interoperability and energy efficiency, problems the authors describe as vital to positioning IoMT in healthcare without compromising security or accessibility.

A central contribution is a comparative analysis of short-range and long-range communication protocols against healthcare-specific requirements. Bluetooth Low Energy dominates wearable medical applications such as fitness trackers, glucometers and pulse sensors because of its low power consumption and secure data transfer. Zigbee supports mesh networking that scales across many IoMT devices, while Wi-Fi, though more power-hungry, is preferred for bandwidth-rich tasks like image diagnosis and video conferencing, connecting directly to hospital management systems and cloud platforms. The selection process, the authors note, hinges on data rate needs, latency sensitivity, power constraints, environmental interference, device density and battery capacity.

Looking further ahead, the survey examines sixth-generation cellular networks, which target peak data rates of one terabit per second, latency below 0.1 milliseconds, positioning accuracy of one centimetre and connection density of ten million devices per square kilometre. These capabilities map onto distinct medical scenarios: telesurgery requires ultra-reliable low-latency communication with latency below one millisecond, holographic healthcare demands terabit rates for real-time 3D rendering, digital twin hospitals need massive connection density, and surgical robotics benefits from centimetre-level positioning. The authors are careful to note that 6G standards remain under development, with commercial deployment not expected until the late 2020s or early 2030s, and current 6G research for IoMT remains exploratory.

On architecture, the review describes a four-layer IoMT structure comprising device, gateway, edge computing and cloud services layers. Edge computing emerges as a key theme: by processing data near the point of generation rather than transmitting everything to central servers, edge nodes reduce latency for real-time monitoring, diagnostics and crisis response, while lowering the risk of sensitive patient data leaking to external networks. Edge nodes combine processors, memory, security modules and input-output interfaces, applying artificial intelligence and machine learning models locally to raw medical data before forwarding only essential information onward.

Security receives extensive treatment. The survey distinguishes data-at-rest protection, typically through AES-256 encryption with hardware security modules managing keys, from data-in-transit protection using end-to-end encryption, TLS 1.3 and VPN tunneling. Device authentication relies on trusted platform modules, certificate-based identity and mutual authentication protocols such as TLS and DTLS, while user authentication layers in multi-factor methods, biometrics and role-based access control. Importantly, the authors caution that technical controls alone do not establish compliance with HIPAA or GDPR; compliance also requires organizational policies, risk assessments, audit trails, staff training and legal review.

The quantum discussion is notably precise about terminology. Post-quantum cryptography refers to classical algorithms running on conventional computers that resist attacks from future quantum machines. Quantum key distribution uses quantum mechanics to establish shared secret keys, with any eavesdropping attempt disturbing quantum states in a detectable way. Quantum computing itself may accelerate certain computations. NIST finalized its first post-quantum cryptography standards in 2024, with CRYSTALS-Kyber for key encapsulation and CRYSTALS-Dilithium for digital signatures. Benchmark studies show ARM Cortex-M4 processors can execute Kyber-512 key generation in roughly 1.2 million cycles, suggesting feasibility for mid-range medical devices but remaining challenging for ultra-low-power implants. The authors highlight the harvest-now, decrypt-later threat: data encrypted today with RSA or ECC may become vulnerable within 10 to 15 years, making migration urgent for records with decades-long sensitivity.

Quantum key distribution faces steeper deployment hurdles. Current systems require dedicated fiber optic channels, cannot run over existing hospital networks without modification, and a single link can exceed 100,000 dollars excluding installation and maintenance. Commercial systems achieve roughly 100 to 200 kilometres over standard fiber, technically feasible for hospital campuses but costly. The survey expects gradual adoption in targeted high-value scenarios such as inter-hospital genomic data transfer and remote surgery connections, rather than universal deployment. Quantum machine learning for medical imaging and quantum optimization for drug discovery remain largely experimental, with current hardware lacking the qubit counts and coherence times needed for real-time clinical use.

The review also quantifies practical trade-offs in federated learning, where AI models train across institutions without exchanging raw patient data. Reported experiments show training chest X-ray classifiers with a differential privacy budget of epsilon equal to 1.0 reduces accuracy by 8 to 12 percent compared with non-private baselines, while epsilon values of 4 to 8 limit degradation to 3 to 5 percent or less. Non-uniform data distributions across hospitals increase communication rounds by two to three times, and a single training round for 100 hospitals transfers roughly 10 gigabytes, with total communication reaching one to five terabytes per cycle. On medical benchmarks, federated models achieve AUCs within 2 to 3 percent of centralized training for mortality prediction on MIMIC-III.

Blockchain receives a similarly grounded assessment. Public chains like Ethereum process 15 to 30 transactions per second, inadequate for high-frequency medical data, though consortium chains such as Hyperledger Fabric reach 1,000 to 3,000 transactions per second. Deployments like MedRec at Beth Israel Deaconess Medical Center demonstrated patient-controlled data access but did not scale to production workloads, while Estonia’s national use of Guardtime shows blockchain can work at scale when appropriately scoped. The authors conclude blockchain works best for audit trails, consent management and data integrity verification rather than storing all healthcare data. Persistent challenges in interoperability, scalability, reliability, standardization and energy optimization remain, and the survey outlines future directions spanning quantum-secured communication protocols, AI-driven adaptive healthcare architectures and innovative sensing technologies as the field’s most pressing research frontier.

Subject of Research: A survey of communication technologies, security frameworks and intelligent architectures for the medical Internet of Things.

Article Title: A comprehensive survey of communication technologies, security frameworks, and intelligent architectures for medical internet of things and quantum-enabled healthcare

Article References: Ateya, A. A., ElAffendi, M., & Hammad, M. (2026). A comprehensive survey of communication technologies, security frameworks, and intelligent architectures for medical internet of things and quantum-enabled healthcare. Discover Internet of Things, 6(1), Article 195. https://doi.org/10.1007/s43926-026-00525-1

Image Credits: AI Generated

DOI: 10.1007/s43926-026-00525-1

Keywords: Internet of Medical Things, IoMT, communication protocols, edge computing, post-quantum cryptography, quantum key distribution, blockchain, federated learning, energy harvesting, remote patient monitoring, 6G networks, healthcare security