Smart Hospitals E-Book
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- Herausgeber: John Wiley & Sons
- Kategorie: Wissenschaft und neue Technologien
- Sprache: Englisch
Discover the potential of 5G, 6G, and smart hospitals beyond connectivity in Smart Hospitals: 5G, 6G, and Moving Beyond Connectivity and learn how these advancements are revolutionizing healthcare and the digital world.
The advancement of wireless communication technologies has revolutionized the way we connect and interact with the digital world. The introduction of 5G networks has paved the way for faster, more reliable, and low-latency wireless connections. However, as technology continues to evolve, the focus is now shifting toward exploring the future potential of 5G and 6G and their applications in various industries. One such industry that stands to benefit significantly from these advancements is healthcare, particularly with the concept of smart hospitals. The development of smart hospitals relies on IT infrastructure, software solutions, and data management systems. IT professionals and software developers work with healthcare professionals on designing and implementing systems that enable seamless connectivity, data integration, analytics, and security in smart hospital environments. Smart Hospitals: 5G, 6G, and Moving Beyond Connectivity delves into the potential of 5G, 6G, and smart hospitals, highlighting how they go beyond mere connectivity.
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Veröffentlichungsjahr: 2024
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Table of Contents
Cover
Table of Contents
Series Page
Title Page
Copyright Page
1 Smart Hospitals: Integrating Connectivity and Intelligence
1.1 Introduction
1.2 Implementation of Smart Hospitals
1.3 Literature Review
1.4 Conclusion
References
2 Evolution of 5G and 6G Cellular Systems
2.1 Introduction
2.2 Objectives of the Study
2.3 Scope and Significance
2.4 Basics of Cellular Technology
2.5 5G Technology
2.6 Towards 6G
2.7 Technologies Enabling 6G
2.8 Challenges in 6G Developments
2.9 Future Prospects and Industry Impacts
2.10 Comparative Analysis: 5G Versus 6G
2.11 Main Contribution of 5G and 6G Evolution
2.12 Limitations of 5G and 6G Cellular System
2.13 Conclusion
References
3 A Review on Augmented Reality and Virtual Reality Technologies in the Field of Healthcare
Abbreviation
3.1 Introduction
3.2 Augmented Reality in Healthcare
3.3 Virtual Reality in Healthcare
3.4 Advantages of AR and VR in the Healthcare
3.5 Challenges and Future Scope
3.6 Conclusion
References
4 Compressed Sensing Reconstruction Algorithms for Medical Images – A Comparison
4.1 Introduction
4.2 Concept of Compressed Sensing Theory
4.3 Comprehensive Sensing Reconstruction Algorithms
4.4 Results and Discussion
4.5 Contribution of the Work
4.6 Limitations
4.7 Conclusion
References
5 Internet of Medical Things (IoMT)
5.1 Introduction: Internet of Medical Things
5.2 Wearable Devices and Sensors for IoMT
5.3 Challenges Faced in Customizing Wearable Devices
5.4 Real-World Examples of IoMT Implementation
5.5 Conclusions
References
6 The Impact of 5G and 6G on Healthcare
6.1 Introduction: The Evolution of Wireless Connectivity: A Journey from 4G to 6G
6.2 Telemedicine and Remote Patient Monitoring
6.3 IoT in Healthcare and Advanced Medical Imaging
6.4 Anticipated Impact of 6G in Healthcare
6.5 Current State of Healthcare Connectivity
6.6 Limitations and Hurdles in Current Healthcare Communication Systems
6.7 Impact of 5G on Healthcare
6.8 The 6G Horizon: Unveiling the Potential Frontiers of Advanced Connectivity
6.9 Terahertz-Frequency Communication
6.10 Ultra-Reliable, Low-Latency Communication (URLLC)
6.11 Holographic Communication
6.12 Advanced Artificial Intelligence Integration
6.13 Massive Device Connectivity
6.14 Environmental and Energy Efficiency
6.15 Designing an Antenna for Healthcare Applications
6.16 Conclusion
References
7 Design and Fabrication of Vehicle Automation Systems
Nomenclatures
7.1 Introduction
7.2 Related Work
7.3 Design of the Project
7.4 Fabrication
7.5 Conclusion
7.6 Future Scope
References
8 Design and Optimization of Antennas with Improved ON–OFF Body Performance for Biomedical Applications
8.1 Introduction
8.2 Literature Review
8.3 Antenna Design
8.4 Comparison Results
8.5 Limitations
8.6 Conclusion
References
9 Beyond 5G-Based Smart Hospitals: Integrating Connectivity and Intelligence
9.1 Introduction
9.2 Related Works
9.3 Methodology
9.4 6G-Enabled SHS Applications and Challenges
9.5 Future Research Directions and Recommendations
9.6 Conclusions
References
10 Patient Monitoring Using 5G, with MIMO-NOMA for mm-Wave Communications in Heterogeneous Networks
10.1 Introduction
10.2 Related Works
10.3 NOMA Architecture
10.4 Power Allocation to the 5G-Enabled NOMA Users and Hospital
10.5 NOMA-MIMO System
10.6 Results and Discussion
10.7 Conclusion and Future Scope
References
11 A Review on the Internet of Medical Things
11.1 Introduction
11.2 Architecture of IoMT
11.3 IoMT – Applications, Benefits and Challenges
11.4 Literature Review
11.5 Conclusion
References
12 6G Networks Technology: An Exhaustive Survey
12.1 Introduction
12.2 Wireless Networks Evolution: 1G to 6G
12.3 Methods
12.4 Results and Discussion
12.5 Conclusion
References
13 Smart Hospitals: Integrating Connectivity and Intelligence: A Comprehensive Study and Challenges
13.1 Introduction
13.2 Smart Hospital Challenges and Opportunities
13.3 Smart Hospital System Design
13.4 Smart and Connect Health
13.5 IoT Design Architecture for Healthcare
13.6 Conclusion
References
14 Exploring the Role of 6G Technology in Smart Healthcare Systems: Challenges, and Future Trends
14.1 Introduction
14.2 Theoretical Background
14.3 Taxonomy
14.4 Key Enabling Technologies for 6G Smart Healthcare
14.5 Research Challenges and Future Directions
14.6 Conclusion
References
Index
Also of Interest
End User License Agreement
List of Tables
Chapter 1
Table 1.1 A comparison of the survey on smart hospitals.
Chapter 8
Table 8.1 Parametric list.
Table 8.2 Parametric list.
Table 8.3 SAR comparison.
List of Illustrations
Chapter 1
Figure 1.1 Architecture of smart hospitals [15].
Figure 1.2 Implementation of smart hospitals using 5G [16].
Chapter 3
Figure 3.1 Augmented reality in the platform of healthcare.
Figure 3.2 Application of AR and VR in the medical field reproduced by the Ref...
Chapter 4
Figure 4.1 Compressive sensing acquisition and reconstruction system.
Figure 4.2 A comparison of OMP, SaMP, AS-SaMP and DSS-SaMP algorithms.
Chapter 5
Figure 5.1 The Internet of Things in medical care.
Figure 5.2 The IoT deployment structure.
Chapter 6
Figure 6.1 Capabilities and instruments of 5G for healthcare applications.
Figure 6.2 Proposed antenna for healthcare communications.
Chapter 7
Figure 7.1 Layout of obstacle detection car.
Figure 7.2 Arduino uno board.
Figure 7.3 Ultrasonic sensor.
Figure 7.4 Motor driver shield.
Figure 7.5 Servo motor.
Figure 7.6 Algorithm of the obstacle detection car.
Figure 7.7 A prototype of an obstacle detection car.
Figure 7.8 Isometric view of customized frame.
Figure 7.9 Front view of the customized frame.
Chapter 8
Figure 8.1 Patch antenna without a phantom model.
Figure 8.2 Dimensions of an antenna.
Figure 8.3 Stack representation of antenna.
Figure 8.4 S-parameters of the antenna without the phantom model.
Figure 8.5 The VSWR of the antenna without a phantom model.
Figure 8.6 Radiation pattern of an antenna without a phantom model.
Figure 8.7 Gain of the antenna without a phantom model.
Figure 8.8 Antenna inside the phantom model.
Figure 8.9 S-parameters of the antenna inside phantom.
Figure 8.10 The VSWR of the antenna inside phantom.
Figure 8.11 Radiation pattern of an antenna inside phantom.
Figure 8.12 The SAR of the antenna inside the phantom.
Figure 8.13 Antenna on the wearable phantom model.
Figure 8.14 S-parameters of antenna on body.
Figure 8.15 The VSWR of antenna on body.
Figure 8.16 Radiation pattern of an antenna on a phantom model.
Figure 8.17 The SAR of the antenna on a phantom model.
Figure 8.18 Antenna placed 10mm away from phantom model.
Figure 8.19 S-parameters of the antenna with 10mm gap.
Figure 8.20 The VSWR of the antenna with 10mm gap.
Figure 8.21 Radiation pattern of an antenna with 10mm gap.
Figure 8.22 The SAR of the antenna placed 10mm away from phantom model.
Figure 8.23 Antenna placed 15mm away from phantom model.
Figure 8.24 S-parameters of the antenna with 15mm gap.
Figure 8.25 The VSWR of the antenna with 15mm gap.
Figure 8.26 Radiation pattern of an antenna with 15mm gap.
Figure 8.27 The SAR of antenna placed 15mm away from phantom model.
Figure 8.28 S parameter comparison.
Figure 8.29 Gain comparison.
Chapter 9
Figure 9.1 Technologies for 6G-enabled smart healthcare challenges.
Figure 9.2 The TIF (Tag Image File Format) for healthcare apps using 6G.
Figure 9.3 Structure of the proposed approach.
Figure 9.4 The CC for a populace smart healthcare system.
Figure 9.5 6G-enabled future SHS.
Chapter 10
Figure 10.1 NOMA topology.
Figure 10.2 A wireless connection is established between the patient and the m...
Figure 10.3 The procedures used in the simulation’s output between the medical...
Figure 10.4 Proposed MIMO-NOMA beam space.
Figure 10.5 Examining of bit error calculation.
Figure 10.6 Outage probability v/s signal-to-noise ratio (SNR).
Figure 10.7 Spectral effectiveness diagram.
Figure 10.8 Q’s energy efficiency graph.
Chapter 11
Figure 11.1 The Internet of Medical Things (IoMT) – architecture [1].
Figure 11.2 The impact of the IoMT on healthcare [5].
Figure 11.3 On-body segment device [7].
Figure 11.4 In-home segment device [6].
Figure 11.5 In-hospital segment device [9].
Figure 11.6 Applications of the IoMT [8].
Chapter 12
Figure 12.1 Leading communication achievements for several generations (1G to ...
Figure 12.2 The 5G-infrastructure-fronthault-midhaul-backhaul.
Figure 12.3 5G vs. 6G key requirements comparison.
Figure 12.4 An example of a holographic telepresence. Left: presenter’s setup....
Chapter 13
Figure 13.1 A layout of a smart hospital.
Figure 13.2 Smart hospital objectives.
Figure 13.3 The intelligent hospital BMS design layers.
Figure 13.4 Design of an intelligent hospital building.
Figure 13.5 Smart and connected health classification.
Figure 13.6 Iot-based network architecture.
Figure 13.7 IoT architecture for remote patient healthcare.
Figure 13.8 IoT architecture for ambient assisted living.
Figure 13.9 IoT architecture for mobile healthcare.
Figure 13.10 IoT architecture for smart healthcare coaching systems.
Chapter 14
Figure 14.1 Structure of the intelligence 6G-enabled healthcare systems.
Figure 14.2 Different network layers of 6G.
Figure 14.3 Taxonomy of 6G intelligent healthcare.
Figure 14.4 Various key-enabled technologies for a 6G-assisted smart healthcar...
Guide
Cover Page
Table of Contents
Series Page
Title Page
Copyright Page
Begin Reading
Index
Also of Interest
WILEY END USER LICENSE AGREEMENT
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Scrivener Publishing100 Cummings Center, Suite 541JBeverly, MA 01915-6106
Publishers at ScrivenerMartin Scrivener ([email protected])Phillip Carmical ([email protected])
Smart Hospitals
5G, 6G and Moving Beyond Connectivity
Edited by
Arun Kumar
Manoj Gupta
Sanjeev Sharma
Er. Himanshu Sharma
and
Khursheed Aurangzeb
This edition first published 2024 by John Wiley & Sons, Inc., 111 River Street, Hoboken, NJ 07030, USA and Scrivener Publishing LLC, 100 Cummings Center, Suite 541J, Beverly, MA 01915, USA© 2024 Scrivener Publishing LLCFor more information about Scrivener publications please visit www.scrivenerpublishing.com.
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Library of Congress Cataloging-in-Publication Data
ISBN 9781394275441
Front cover images supplied by Adobe FireflyCover design by Russell Richardson
1Smart Hospitals: Integrating Connectivity and Intelligence
Yashwanth S., Varshini Kulkarni, Chethana H. T.* and Chaitra N. C.
Department of Computer Science and Engineering, Vidyavardhaka College of Engineering, Mysuru, India
Abstract
Health is a crucial part of every person; sometimes, a person may have an unstable condition such as a disease or illness. For people to revert to good condition, they may need intensive care provided by hospitals. Nowadays, hospitals have become busier because of rapid growth in population. Due to this, doctors, nurses, paramedics, and administrative staff are struggling to handle them. A solution to this problem is the use of technology such as the Internet of Things (IoT) to upgrade hospitals to smart hospitals including doing medical works like monitoring patients’ data and performing various scanning tasks at a faster rate.
The “smart hospitals” concept is a comprehensive integration of 5th generation (5G) technology with cloud computing, big data analytics, IoT, and artificial intelligence (AI). The integration of 5G in smart hospitals encompasses several key elements—5G healthcare terminals, including medically integrated terminals, information collection and display terminals, and auxiliary terminals. The 5G healthcare-dedicated network employs network slicing, a dedicated user plane function (UPF), and multi-access edge computation for tailored medical networks, efficient data transmission, and low-latency processing. The healthcare-dedicated cloud manages network capabilities, computation resources, and medical applications. 5G healthcare applications showcase production efficiency and smart medical services. The healthcare-dedicated network architecture includes local, wide-area, and dynamic networks for intra- and inter-hospital services along with out-of-hospital medical services. The integration with existing medical systems and a unified platform management layer ensures seamless cloud–network integration, gradual migration, and efficient resource management. The aim of the chapter is to create a flexible ecosystem utilizing 5G technology for enhanced healthcare services and patient outcomes.
Keywords: 5G, IoT, AI, integration, patients, cloud, hospital, medical
1.1 Introduction
Health is defined as a state of complete physical, mental, and social well-being; it is not just the absence of disease or illness [1]. The word “hospital” is derived from the Latin word “hospice,” which means guest. Hospitals are institutions that provide medical and surgical treatment along with nursing care for any sick or injured people [22]. Ensuring that those in need of receiving comprehensive healthcare, including preventive and curative treatments, is a fundamental role of social and medical organizations. It serves as a center for biosocial research, as well as a training center for health workers [21].
Hospitals are part of a social structure, which again have a subsystem, like supportive and utility services, clinical services with heterogeneous group of people like doctors, nurses, paramedics, and administrative staff all working together to provide medical care to patients [2]. The pandemic has brought to our attention and intensified the challenges faced by the healthcare industry. Numerous problems exist such as excessive doctor workloads, disgruntled patients, and disorganized facilities where staff members spend hours looking for essential equipment [3]. The rise of “informed patients,” who reject passive treatment, is another significant issue. They expect greater details and a vote during treatment [24]. To be able to transform their facilities into “smart hospitals,” which will enable them to handle the pandemic and center their offerings on the patient, numerous healthcare facilities have already turned to healthcare technology businesses [23].
The main contributions of this chapter are as follows:
A new method is defined to implement smart hospitals.
This method involves a layered approach using 5G.
Comfort and convenience can be improved through this method.
A detailed description of this framework is provided.
As a result, we can observe that 5G can support high-resolution medical imaging and diagnostic tools.
1.1.1 Exploring the Concept of Smart Hospitals
Smart hospitals are designed to leverage optimized and automated processes based on the information and communication technology (ICT) environment to improve current patient care methods and introduce new features at a minimal cost [3]. Data and technology are used by smart hospitals to increase patient care and operational efficiency. They work in a setting that is highly optimized and automated. These healthcare facilities use data analytics, artificial Intelligence (AI), 5G, and linked equipment. Each hospital will have different designs and common functions for its smart room, but they all enhance patient experience, expedite the clinical process, and promote collaboration.
The patients are clients and should receive personalized attention from healthcare facilities, which serve as the basis for smart hospitals. Since the word “customer” connotes a more engaged and exacting consumer, astute hospitals try their hardest to provide a distinctive experience rather than only concentrate on medical care. They even provide their services to the carers of their patients. For example, a health librarian employed by Stanford Hospital will assist family members [2].
1.1.2 Working of Smart Hospitals
A crowded hospital has many moving components such as patients, hospital employees, medicine, and medical equipment. Artificial intelligence automation offers a chance to streamline the operations throughout the institution. Even while a patient cannot always have a doctor or nurse by their side, patients can be closely monitored by a mix of smart sensors and intelligent video analytics, which can notify medical professionals when a patient is in distress and needs care. For example, patients in an intensive care unit (ICU) are linked to monitoring equipment that takes their vital signs continuously. Many of these beep repeatedly with different alerts, which occasionally causes medical professionals to miss the alarm from a single sensor. The smart hospital can be compared to an octopus. The secure server of the organization, which houses and manages all the facility’s data, serves as its brain. Every department within its tentacles—radiology lab, ICU, emergency room (ER), and operating room, for example—is covered in sensors, or “octopus’ suckers,” that gather information from their environment. It would be impossible for the octopus to respond quickly throughout its entire body based on information sensed by a single arm if each tentacle functioned independently. The octopus can adapt to its changing surroundings because each tentacle relays data back to the central brain.
Similar to this, the smart hospital is a hub-and-spoke system with sensors placed throughout the building that may relay important information back to a central hub, assisting in the making of choices that affect the entire facility. Artificial intelligence would notify personnel in the recovery room to get ready for the patient’s arrival, for example, if video feeds in the operating room indicate that a surgical procedure is almost finished.
Medical device companies, academic medical centers, and startups are using an end-to-end AI platform that integrates with the entire hospital network to power smart hospital solutions. This platform powers everything from medical devices running real-time applications to secure servers that store and process data over an extended period. It is compatible with several software libraries, cloud, edge, and data center infrastructure, as well as international partner ecosystem. Data are compiled by smart hospitals using intricately linked systems. The different systems like lighting, climate control, and shading are combined in one infrastructure (total room automation) at the ward level, where integration begins. Smart hospitals are patient-focused establishments that exchange data with other organizations and are integrated into an ecosystem. Programmers for healthcare management are offered in a variety of settings within this ecosystem, such as patient homes and gyms. Hospitals are generally designed to handle sophisticated treatments, such as critical care and surgery. Technologywise, smart hospitals use the Internet of Things (IoT) and employ a variety of new technologies such as big data analytics, 5G, AI, augmented reality (AR), and cloud platforms. The architecture of smart hospitals is shown in Figure 1.1.
1.2 Implementation of Smart Hospitals
The implementation of 5G in smart hospitals involves the integration of 5G technology across various layers and devices of the healthcare system. The key aspects of how 5G is implemented in smart hospitals are given here:
5G Healthcare Terminals
Medically Integrated Terminals: These serve as a gateway to 5G access, enabling medical devices without the inbuilt 5G capability to access the 5G-based healthcare dedicated network.
Figure 1.1 Architecture of smart hospitals [15].
Information Collection and Display Terminals: These include wearable devices, smart boxes, video terminals, first-aid kits, and imaging equipment, which gather and display data.
Auxiliary Terminals: Modern devices like ambulances, robots, and drones enhance the flexibility and efficiency of remote medical services.
5G Healthcare-Dedicated Network
Network Slicing: A specialized 5G network designed for healthcare purposes employs network slicing, enabling the establishment of distinct virtual medical networks on a shared physical infrastructure. These slices are customized to meet various application needs within the healthcare sector.
Dedicated UPF: A dedicated UPF facilitates the seamless transmission of medical data between healthcare-specific terminals and the cloud infrastructure dedicated to healthcare services.
Multi-Access Edge Computation (MEC) Technology: Ensures efficient low-latency processing for healthcare applications by enabling computation at the network’s edge.
5G Healthcare-Dedicated Cloud
Health-Dedicated Network Management: Health-dedicated network management oversees the comprehensive capabilities of the network, ensuring consistent latency, throughput, global mobility, and secure connections throughout its entirety.
Computation Resources Management: Leverages virtualization technology tailored specifically for medical applications, encompassing AI, big data processing, video streaming, object storage, and network functionalities.
Medical Applications Management: Deploys and administers advanced 5G smart healthcare applications, accommodating mobile edge computing (MEC) alongside private or alternative cloud architectures.
5G Healthcare Applications
5G Basic Applications: Showcase the experience of 5G in improving hospital production efficiency and transmission capacities.
Medical Applications: This builds a full-scenario, smart medical service ecosystem, covering all the components like smart hospitals, telemedicine, and emergency rescue applications under various medical scenarios.
Healthcare Dedicated Network Architecture
Local Healthcare Dedicated Network (LHDN): Facilitates wireless surgery, medical handcart operations, service robots, and seamless data sharing within the hospital premises, enhancing intra-hospital medical services.
Wide-Area Healthcare Dedicated Network (WHDN): Facilitates broad-scale interconnectivity among multiple hospitals, enabling remote diagnosis, surgery, inspections, checkups, and collaborative efforts across distant locations. Dynamic Healthcare Dedicated Network (DHDN): Responds to medical requirements beyond hospital settings, including 5G ambulances, drones, home medical care, and remote consultations, through dynamic adjustments of network slicing to accommodate various needs effectively.
Healthcare-Dedicated Cloud Integrating with Network and Existing Medical Systems
Integration with Health-Dedicated Network: This takes the help of the industry gateway for cloud-network integration, supporting authentication to access, controlling of network, data transmission, and wide-area interconnection.
Integration with Existing Medical Systems: Implements a strategy for the mutual existence of 5G and traditional hospital information infrastructures, allowing gradual migration of applications to 5G.
Unified Platform Management Layer: Manages the life cycle, status monitoring, access authority, and self-service resource management of the 5G healthcare dedicated cloud.
Overall, the implementation of 5G in smart hospitals shown in Figure 1.2 involves creating a seamless, efficient, and flexible ecosystem that leverages the capabilities of 5G technology for improved healthcare services to patients.
Figure 1.2 Implementation of smart hospitals using 5G [16].
1.2.1 Benefits of Smart Hospitals
In the past few years, the healthcare industry has witnessed a transformative shift with the advent of smart hospitals innovative healthcare facilities that make use of the power of connectivity and intelligence to increase the efficiency of patient care, streamline operations, and enhance overall efficiency. The benefits of smart hospitals extend across various dimensions, reshaping the landscape of healthcare delivery. This introduction aims to highlight the key benefits of smart hospitals, showcasing the profound impact they have on both patient outcomes and healthcare system dynamics.
1.2.1.1 Benefits of Implementing IoT in Healthcare
Enhanced patient comfort and convenience are achieved through IoT technologies, leading to heightened patient satisfaction and quicker recovery times. Healthcare professionals utilize IoT devices and data for efficient patient monitoring and optimal therapy delivery [18–20]. Furthermore, IoT security systems ensure the safety of patients, doctors, and hospital staff [21]. Sanitization through UV lights maintains a clean environment, promoting overall health [22]. Telemedicine, as defined by the International Society for Telemedicine and eHealth, utilizes information and communication technology to deliver healthcare services, facilitating accurate data sharing among physicians for improved diagnosis, treatment, and prevention of diseases and injuries. Telemedicine offers a solution for the complexity of patient records and helps reduce patient travel costs while addressing emergency care challenges faced by rural healthcare clinics [23].
1.2.1.2 Benefits of Adopting 5G in Healthcare
The implementation of 5G technology in smart hospitals can bring about several benefits, enhancing various aspects of healthcare delivery. The 5G system offers a significant amount of faster data speeds compared to previous generations. This enables quick and seamless transmission of large medical files, high resolution imaging, and real-time patient monitoring. It can enhance the efficiency of telemedicine services, allowing healthcare professionals to access and analyze data more rapidly. 5G networks provide low latency, reducing the delay in data transmission. This is critical for applications that require real-time communication, such as remote surgery to the patient, where even a slight delay can have serious consequences. Low latency is also beneficial for applications such as AR and virtual reality (VR) in medical training and education. With the increased capacity and connectivity of 5G networks, smart hospitals can seamlessly integrate a multitude of IoT devices and sensors. This enables the continuous monitoring of patients, medical equipment, and hospital facilities. The connectivity can also support the use of smart wearables for patient monitoring and management of chronic conditions. 5G facilitates more comprehensive and real-time remote patient monitoring. This is particularly beneficial for patients who are dealing with chronic conditions, allowing healthcare providers to monitor vital signs and other health metrics remotely. This can lead to early detection of potential issues, reducing the need for hospital admissions and improving overall patient outcomes. The high data speeds and low latency of 5G enable the healthcare providers to process and analyze a huge amount of patient data rapidly. This can contribute to the advancement of precision medicine by tailoring treatment plans based on individual patient characteristics and genetic makeup. Big data analytics can also help identify patterns and trends in health data for better disease management and prevention strategies. Networks come with improved security features, including advanced encryption and authentication protocols. This is crucial in healthcare settings where the privacy and security of patient data are of utmost importance. Robust security measures can help protect sensitive medical information from unauthorized access and cyber threats. 5G can support the use of advanced imaging technologies, such as high-resolution medical imaging and diagnostic tools. This can lead to more accurate and timely diagnoses, improving the overall quality of healthcare services.
5G networks are designed to accommodate the increasing demands of emerging technologies. As new healthcare innovations and technologies continue to evolve, the scalability and adaptability of 5G make it well-suited to support future advancements in smart hospitals.
1.2.2 Challenges of Smart Hospitals
Smart hospitals hold immense promise for revolutionizing healthcare delivery through the integration of connectivity and intelligence, but they are not without their set of challenges. The journey toward implementing and sustaining a smart hospital ecosystem is marked by obstacles that span technological, organizational, and ethical dimensions. While the implementation of 5G in smart hospitals offers numerous benefits, there are also challenges and considerations that need to be addressed. This introduction outlines some of the key challenges faced by smart hospitals as they strive to redefine healthcare in the digital age.
Challenges encountered in implementing the Internet of Medical Things (IoMT) network designs within smart hospitals include:
Body Movements: Patient movements can alter the topology of the body sensing network (BSN), requiring IoMT routing protocols capable of adapting to such changes while maintaining communication quality
[13]
.
Temperature Fluctuations: Absorption of radiation by antennas and power consumption by node circuitry can elevate the temperature of IoMT devices. Elevated temperatures in wearables or implants can damage patient cells or organs, necessitating consideration of device power consumption.
Energy Efficiency: The lifespan, usability, and size of IoMT devices are contingent upon energy efficiency. Routing protocols should optimize device energy consumption, aiming for a battery life of 10 – 15 years for implant devices to minimize the need for repetitive surgeries and avoid associated physical and financial burdens. Frequent battery changes for wearable devices decrease device utilization.
Transmission Range: Short data transmission ranges can result in sensor node disconnections due to patient postural movements within the IoMT system
[14]
.
Heterogeneous Environments: Data from various sensors within IoMT systems are heterogeneous, requiring routing protocols capable of managing the diverse environment of BSN applications, such as the Dexter Net.
Quality of Service (QoS): Real-time BSN applications, such as ECG monitoring, demand increased QoS to address time-critical situations and sensitivity to data loss effectively.
Security: Cloud storage of user data enables doctors’ accurate and prompt responses to remotely monitored patients. However, this advancement poses the risk of user data being vulnerable to hacking or misuse.
Challenges faced in implementing 5G are as follows:
Infrastructure Costs: Upgrading to 5G requires significant investment in new infrastructure, including the installation of 5G base stations and antennas. The initial costs of deploying 5G networks can be substantial, and healthcare organizations may need to allocate resources for these infrastructure upgrades
[10]
.
Security Concerns: As with any advanced technology, 5G networks may pose security challenges. The increased connectivity and reliance on IoT devices in smart hospitals create more potential entry points for cyber threats. Ensuring robust cybersecurity measures is crucial to protect patient data and the integrity of healthcare systems.
Interoperability Issues: Integrating 5G technology with existing healthcare systems and devices can be complex. Ensuring interoperability between different medical devices, electronic health record (EHR) systems, and other hospital infrastructure is essential for a seamless and efficient operation. Standardization efforts are needed to address these interoperability challenges
[11]
.
Regulatory Compliance: Healthcare is a highly regulated industry, and the deployment of 5G in smart hospitals must comply with various regulations related to patient privacy, data security, and healthcare standards. Adhering to these regulations while implementing new technologies can be a complex process.
Privacy Concerns: The increased use of IoT devices and sensors for patient monitoring and data collection raises concerns about patient privacy. Healthcare providers must implement robust privacy policies and mechanisms to safeguard patient information and ensure compliance with data protection regulations
[12]
.
Health Concerns: There have been public discussions about potential health effects associated with exposure to electromagnetic fields (EMFs) from 5G technology. While scientific studies generally indicate that 5G technology is safe, addressing public concerns and ensuring transparent communication about the technology’s safety is important.
Data Management and Storage: The high-speed data transfer capabilities of 5G generate large volumes of data in smart hospitals. Managing, storing, and analyzing this massive amount of data can strain existing IT infrastructure and require investments in advanced data storage and processing capabilities.
Workforce Training and Education: The adoption of 5G in smart hospitals necessitates training healthcare professionals to effectively use new technologies. Ongoing education is essential to ensure that staff can leverage the full potential of 5G and associated technologies for improved patient care.
Limited Coverage: While 5G networks are expanding, there may still be areas with limited 5G coverage. Smart hospitals in remote or underserved areas may face challenges in accessing the full benefits of 5G technology until coverage becomes more widespread.
Spectrum Allocation: The availability of suitable radiofrequency spectrum is crucial for 5G deployment. Issues related to spectrum allocation and interference can impact the performance of 5G networks in certain locations.
Addressing these challenges requires collaboration between healthcare providers, technology vendors, regulatory bodies, and other stakeholders. As technology continues to evolve, ongoing efforts are essential to overcome these challenges and fully realize the potential of 5G in smart hospitals.
1.2.3 Opportunities
In 2016, the smart hospital market was valued at $13.52 billion, and it is projected to reach $63.49 billion by 2023, reflecting a remarkable compound annual growth rate of 24.00% from 2017 to 2023 [25]. This market is categorized based on wireless connectivity, application types, services offered, service components, technology types, and geographic regions [25]. Smart hospitals must integrate smart hardware, software, and related technologies to optimize their operations. These technologies encompass smart mobility and systems for patients, staff, and equipment. Key technological drivers for smart hospitals include blockchain, biotelemetry, 5G and 6G technologies, drug development, precision medicine based on genomics and big data, and virtual rehabilitation in orthopedics [1]. The smart hardware component comprises WIFI, active radio frequency identification (RFID), IoT sensors, wearables, dashboards, and 5G networking, among others. Factors propelling the growth of the smart hospital market involve the increasing demand for healthcare infrastructure modernization, efficient solutions in hospitals, advancements in IoT technologies in healthcare, rising incidence of chronic diseases, and the expanding use of connected devices and instruments in hospital settings [25]. The integration of the Internet of Health Things (IoHT) and 5G technology, with their intelligent devices, equipment, applications, and buildings, holds significant promise for enhancing smart hospitals [17]. This integration improves healthcare delivery efficiency and cost-effectiveness by optimizing asset utilization. The current utilization of information technology in healthcare stands to benefit greatly from the incorporation of 5G technologies. The integration of 5G technology in smart hospitals presents a myriad of opportunities to revolutionize healthcare delivery and elevate patient outcomes. This advancement enables high-speed, low-latency communication, fostering the expansion of telemedicine services and facilitating real-time video consultations and remote monitoring, particularly benefiting those in remote or underserved areas. With enhanced connectivity and low latency, smart hospitals can implement advanced remote patient monitoring systems, continuously tracking vital signs for patients with chronic conditions. The capabilities of 5G, such as low latency and high bandwidth, support groundbreaking enhancements in surgical procedures, including advanced robotic surgery and real-time collaboration among experts in different locations. The improved connectivity of 5G also allows for seamless integration of IoT devices and wearables, enabling the collection of valuable data for patient health monitoring and preventive care. Additionally, 5G’s low latency and high data speeds make it conducive to immersive experiences like AR and VR in healthcare, applicable to medical training, surgical simulations, and patient education. The rapid transfer and analysis of large datasets facilitated by 5G contribute to the implementation of big data analytics and predictive medicine, empowering healthcare providers to make informed, data-driven decisions for improved patient outcomes. The technology also supports real-time smart imaging and diagnostics, enhancing the accuracy of medical imaging and expediting the interpretation of results. Beyond clinical applications, 5G improves hospital operations by enabling smart technologies for asset tracking, inventory management, and facility monitoring, resulting in streamlined workflows, reduced costs, and optimal resource utilization. Furthermore, the increased connectivity and data transfer capabilities contribute to the advancement of personalized and precision medicine, allowing healthcare providers to tailor treatment plans based on patient-specific data, including genetic information. Smart hospitals with 5G can enhance the overall patient experience through technologies like virtual health assistants, smart patient rooms, and interactive portals, fostering patient engagement and participation in their own care. In summary, the deployment of 5G in smart hospitals signifies a transformative shift, offering a comprehensive and efficient approach to healthcare services while driving innovation in the industry. These opportunities collectively contribute to the evolution of healthcare systems, promoting efficiency, personalization, and accessibility in patient care.
1.3 Literature Review
In this section, a literature review on different approaches adapted by different authors is discussed.
Anuj Raghav and Paliwal [1] introduced a comprehensive conceptual framework for smart architecture, emphasizing energy conservation and security/interoperability. Central to their approach is the building management system (BMS), a multi-layered design consisting of cameras and end-of-system components at the field layer, middleware for the integration of physical and cyber systems, and the efficient management layer for decision-making based on intelligent network insights. In addressing security and interoperability, Raghav et al. leveraged IoT technologies, employing a hybrid network architecture that blends star and mesh topologies. Each floor and room feature sensor and actuator networks (Internet protocol version 6 over low-power wireless personal area networks: 6LoWPANs) linked to microcontrollers. These microcontrollers collect data from network nodes, transmitting it to gateways through IPv6 connections. Gateways, comprising local databases and routers, then relay the data to remote cloud platforms. The cloud platform, housing a database and server, serves as the ultimate destination for data storage and analysis. This system enhances a hospital’s energy efficiency while ensuring a robust security framework through interconnected IoT technologies.
Arun Kumar et al.[2] advocated for the implementation of MicroStation technology to address the high data rates, ranges from 112 Mbps to 1.8 Gbps, required for medical applications like remote surgery and emergency clinic. The MicroStation includes microcells, femtocells, and picocells, which function as small cells compared to large-scale cells. Femtocells enhance coverage and capacity in confined spaces, while picocells extend wireless coverage in small areas. Microcells, similar to picocells, differ in coverage area and support more users. These small cells increase area range efficiency through higher frequency reuse. The architecture incorporates body area networks (BANs) comprising IoT devices to monitor health parameters. Due to the growing reliance on connected medical devices, the risk of cyberattacks on patient data transmission increases. Patient data from BANs are transmitted to macro base stations (MBS) in three scenarios: directly through a millimeter (mm) link backhaul if the BAN is close to MBS, via MBS transmission line if the BAN is far, and through small base stations (SBS) if the BAN is much farther. The MBS, equipped with smart antennas and 5G technology, uses massive multiple input multiple output (MIMO) for efficient data transfer to the 5G network, which is directly linked to a central data center. The data center stores and analyzes all patient information to provide accurate outputs to users. This comprehensive system ensures the secure and efficient transmission of medical data for improved healthcare outcomes.
Abdul Ahad et al.[3] presented a comprehensive 5G-based smart healthcare architecture incorporating key enabler technologies such as advanced MIMO, software-defined networking (SDN), device-to-device (D2D) communication, mm waves, small cells, network functions virtualization (NFV), and edge computing. Addressing security concerns, the system focuses on authentication, confidentiality, availability, nonrepudiation, and integrity. Given the high data rates demanded by smart healthcare applications, small cells, including femtocells, picocells, and microcells, are utilized to enhance capacity and coverage in limited areas. Security measures include primary and secondary authentication for mutual verification between medical devices and networks, with primary authentication supporting non-3G partnership project (3GPP) technologies. Confidentiality is ensured through key generation and exchange, involving the master base node (MeNB) and secondary next-generation base node (SgNB), providing privacy and authenticity for radio resource control (RRC) messages and user plane (UP) data. The incorporation of these components is intended to fulfill the data transfer speed needs of sophisticated healthcare applications, all the while ensuring the network’s resilience against possible security risks and attacks.
In the development of smart hospitals, Suganthi et al.[4] employed IoMT and introduced an innovative approach. The system was organized into three main facets: the patient side, nurse side, and doctor side. On the patient side, various sensors, including a temperature sensor for room temperature control, an ultrasonic sensor for monitoring saline levels in a Trips bottle, and a light-dependent resistor (LDR) for light monitoring, were integrated. The sensor data were directly transmitted to a universal serial bus (USB), which served as the conduit for transmitting data to the Arduino Circuit. The collected data were then formatted using MQ telemetry transport (MQTT), a crucial element for data subscription awareness. The MQTT played a pivotal role in managing electronic devices such as fans. The doctors received sensor data through an Android application connected to the server, and prescriptions were sent from the server to the patients via Android Apps. All these data transfers were facilitated through the WIFI module. Subsequently, the acquired data were uploaded to the doctors’ app, aiding in the administration of patient treatment. The prescribed medication from the doctor was then dispatched to the patients by the nurse, completing the integrated healthcare system.
A system developed by Aditi Khekale et al.[5] operates exclusively on IoT and a WIFI module, which serves the dual purpose of keeping patient information up to date. This module enables prompt actions by doctors and hospital staff based on the patient’s condition, allowing for immediate medical interventions. The initial component includes a fan, light, and ultrasonic sensor that gather patient data, transmitting it to an Arduino mega (ATMEGA Atmel328PU) integrated with an Ethernet shield (W5100) via USB. An essential intermediary in this setup is the web server, which acts as a bridge between users and the Arduino. The server’s primary functions include storing, processing, and delivering web pages to users through the hypertext transfer protocol (HTTP). These pages primarily consist of HTML documents containing images, style sheets, and scripts. In cases of high website traffic, multiple servers may be employed. The sensors generate data, transmitted to the Arduino mega board via USB, and then forwarded to the server using the WIFI module. To monitor the received data, individuals need to subscribe to the web server, allowing hospital staff to oversee the information. The web platform is utilized for switch control, managing electrical appliances and lighting. If the room temperature surpasses a predetermined level, the data are sent to the webpage, where it can be accessed either from the webpage itself or a mobile device [26].
This paper by Jyoti Srivastava et al.[6] summarized the vision of IoMT, a framework based on smart healthcare system, designed in different stages. The first stage is to gather real-time data from patients using various digital electronic devices like smart watches or implemented devices connected using a BSN or wireless sensor network (WSN). The second stage focuses on transferring data from a BSN to remote center over the Internet for future analysis. The help of AI-based data transmission and interpretation technique is employed, but in case of serious situations, healthcare professionals or other medical necessities can be alerted through AI-based applications on smartphones [25]. For less critical cases, patients can implement self-preventive measures.
Bingwen Zhou and Zhang [7] presented a smart medical framework that uses the advantages of resource integration and provide real-time health and medical services. The smart framework consists of the software, business, and hardware frameworks. Their idea is to keep all medical resources in the cloud. Patients can benefit from various medical services through the platform integrated with the help of medical institutions; they provide accurate medical-records editing services for patients through the same platform. From a business perspective, they provide online outpatient services. Patients can register an online appointment and pay in advance from this platform. Telemedicine service is designed for users in areas with underdeveloped medical facilities. Based on the symptoms, patients can consult doctors by text chatting. Doctors will then confirm the time of online diagnosis and treatment time.
Naik et al.[8] introduced a groundbreaking initiative in the realm of Diabetes 2.0 expenditure targeting the average user. They have proposed a 5G-Smart Diabetes application, representing an intelligent and cost-effective solution for diabetes diagnosis that ensures easy accessibility for users. This innovative approach capitalizes on 5G technologies, incorporating elements such as smart textiles, AI models, and the analysis of medical data [27]. The primary objective is to deliver a reliable detection and analysis platform for individuals dealing with diabetes. In their comprehensive study, the authors also outlined a data exchange mechanism among patients and introduced a personalized model utilizing medical data specifically tailored for the 5G-smart Diabetes application. The culmination of their efforts resulted in the development of a prototype system, consisting of smart textiles, smartphones, and medical data clouds. The research findings indicate the system’s effectiveness in successfully providing personalized diagnostic and therapeutic assistance to patients, showcasing the potential of the 5G-Smart Diabetes initiative in enhancing the overall management of diabetes.
J. Lloret et al.[9] stressed the critical importance of 5G technologies for real-time patient monitoring. They highlight that the deployment of 5G networks is essential due to their ability to provide low latency and ensure sufficient bandwidths for all users. The suggested system architecture comprises distinct elements, including wearable technology equipped with sensors for gathering body measurements. A smartphone positioned next to the patient processes the data obtained from the wearable technology. Additionally, there is a database incorporating a smart engine for diagnosis, which triggers alarms using machine learning algorithms applied to extensive big data sourced from diverse hospitals and patient records. Table 1.1 shows the comparison of the survey on smart hospitals.
Table 1.1 A comparison of the survey on smart hospitals.
Authors
Methodology
Limitations
Accuracy
Anuj Raghav and Paliwal
[1]
It uses building management system (BMS) and IoT technologies like star and mesh topologies along with sensors, actuators, and microcontrollers. For analytics and data storage, they used cloud environment.
High cost, and implementation and maintenance are difficult.
85%
Arun Kumar
et al.
[2]
They used IoT gadgets, massive multiple input and multiple output (MIMO) integrated smart antenna, wire backhaul, mm link backhauls, and radio wires.
Valid system integration, significant latency, limited range, and data speed issues, and elevated expenses.
73%
Abdul Ahad
et al.
[3]
This approach encompasses the utilization of edge computing, device-to-device (D2D) communication, sophisticated multipleinput and multiple-output (MIMO) technology, software-defined networking (SDN), millimeter waves (mm waves), nonorthogonal multiple access (NOMA), network function virtualization (NFV), and small cells.
High cost, limitations in resources, susceptibility to a single-point-of-failure, and restricted scalability.
77%
Suganthi
et al.
[4]
Combination of various sensors like temperature, ultrasonic, heart-beat sensor, and blood pressure sensors along with LDR to acquire data from patients. Arduino UNO (ATMEGA328) for Processing with WIFI module.
Limited scalability, single-point-of-failure, no security provided.
65%
Aditi Khekale
et al.
[5]
This method uses various sensors like temperature, ultra-sonic, heart-beat sensors and Arduino mega (ATMEGA Atmel328U) +Ethernet shield (W5100), WIFI module.
Availability is low. The model is not robust. No security provided.
57%
Jyoti Srivastava
et al.
[6]
Uses various sensors, BSN, WSN, or RFID.
Continuous power supply is required. Implementation is difficult.
91%
Bingwen Zhou and Zhang
[7]
This approach comprises MongoDB, web technologies, and cloud infrastructure.
Able to reach small regions only.
83%
Naik
et al.
[8]
They used cloud infrastructure, smart textiles, and artificial intelligence models
Limited scalability, single-point-of-failure, and high cost.
62%
J. Lloret
et al.
[9]
Combination of various sensors to measure different patient parameters, cloud facility, and web app technology.
Difficulty in maintenance
69%
The limitations of this research study are as follows:
There may be accessibility issues for certain regions, especially in rural areas or underserved areas with limited access to high-speed Internet or advanced facilities.
The integration of 5G technology across multiple layers and devices of the healthcare system adds complexity to the infrastructure.
Ensuring seamless communication and data exchange between different devices can be challenging.
Protecting sensitive patient data and ensuring the security of medical devices connected to the 5G network is crucial.
The healthcare system must adhere to strict regulations and compliance standards to ensure patient safety and privacy.
Implementing terminals, networks, and cloud systems can be expensive.
1.4 Conclusion
In conclusion, the integration of 5G technology and IoT in smart hospitals has revolutionized healthcare delivery. Smart hospitals, leveraging connectivity and intelligence, offer a myriad of benefits that reshape patient care and operational efficiency. The implementation of 5G technology enables faster data transmission, seamless connectivity, and low latency, enhancing telemedicine services, and real-time patient monitoring. The adoption of IoT in healthcare within smart hospitals has significantly improved patient comfort, safety, and physician capabilities. The IoT devices, wearable technologies, and data access have contributed to higher patient satisfaction, faster recovery times, and safer environments. The use of IoT security support systems and UV light sanitation systems has also enhanced safety measures within healthcare facilities. Furthermore, telemedicine, facilitated by IoT, has played a crucial role in overcoming barriers for rural healthcare clinics, providing accurate data sharing for prevention, diagnosis, and treatment of diseases, while reducing patient travel costs. Moreover, the transformative shift toward smart hospitals has had a profound impact on patient outcomes and healthcare system dynamics. The combination of 5G technology and IoT has not only improved the efficiency of telemedicine services but has also facilitated quick and seamless transmission of large medical files and high-resolution imaging. This technological advancement marks a significant milestone in the healthcare industry, emphasizing the crucial role of connectivity and intelligence in enhancing patient care and overall operational effectiveness.
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Note
*
Corresponding author:
2Evolution of 5G and 6G Cellular Systems
Kama Ramudu1*, Bodla Rushikesh1, Pingili Shiva Chandana1, B. Jagadish Kumar2 and Venkat Tulasi Krishna Gannavaram3
1Department of ECE, Kakatiya Institute of Technology and Science, Warangal, India
2Department of EEE, Kakatiya Institute of Technology and Science, Warangal, India
3School of Electrical, Computer and Energy Engineering, Arizona State University, Tempe, United States
