It has been established so far that IoT-DS-AI nexus can offer significant assistance to the governments for achieving SDG-3. However, there are various challenges associated with the use of these technologies, mainly due to the involvement of human subject. The use of proposed nexus requires patients and general users to share lot of personal and family data, which raises privacy and security concerns; this is a crucial challenge because globally accepted standardization and legal frameworks are not yet developed. There are also issues pertaining to outdated infrastructure, need for processing high volumes of data, increasing vulnerabilities, and user resistance for adoption of technology. Some of the measures to manage these challenges include ensuring performance and reliability of the technology solutions, developing interoperable solutions and developing internationally accepted ethical, security and legal frameworks. This chapter sheds light on the major challenges and way forward for adopting the IoT-DS-AI nexus in an attempt to achieve SDG-3. Due to the increasing affordability and acceptance of IoT, DS and AI technologies by the patients and doctors, disruptive applications have been developed over the past decade. As the funds by venture capitalists, public and private sectors continue to grow in the industry, there are chances of even more rapid development and adoption. The prospect IoT, DS and AI in the healthcare is promising as new functions are being added into the healthcare products services with technological advances in all the domains of IoT-DS-AI nexus earlier illustrated in Fig. 1.4 . As this nexus promises to improve the quality of care both at individual and population level, it can largely contribute to the achievement of SDG 3. The rapidly advancing capabilities in the hardware, communication techniques, big data analytics are revolutionizing the way healthcare is delivered. For example, AI techniques like predictive analytics and natural language processing are being used to anticipate patient needs and improve diagnostic accuracy. Similarly, Data Science methods such as data mining and statistical modeling help uncover patterns in patient data, leading to more personalized treatment plans. IoT devices, equipped with advanced sensors and connectivity, facilitate continuous monitoring and real-time data collection, ensuring that healthcare providers can respond promptly to any changes in a patient’s condition. Together, these technologies enhance patient outcomes, streamline healthcare operations, and pave the way for innovative treatments and interventions. The end-to-end connected healthcare system starting at the patient’s wearables or ambient sensors and ending at the central dashboards/physician’s devices is expected to arrive soon. The technology will be mainly beneficial for the chronic patients, and since chronic disease management is not a once-off event, a continuously evolving IoT-DS-AI nexus to facilitate holistic monitoring and management. Unlike the conventional healthcare systems where the diagnosis and treatment strategies were largely based on the population averages, the use of computing and communication technologies ensures highly customized medical assessment and administration (Shaik T, Wiley Interdiscip Rev: Data Min Knowl Discov 2023:e1485, 2023). However, the critical scenarios requiring generating/collecting data from multiple points involving diverse technologies and stakeholders give rise to several open issues and challenges. We present some of the major challenges and recommendations for realizing the use of IoT-DS-AI nexus in the healthcare:

The Way Forward

章节
发表日期：

2025年

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Shama Siddiqui,
Anwar Ahmed Khan,
Muazzam Ali Khan Khattak,
Raazia Sosan

摘要

It has been established so far that IoT-DS-AI nexus can offer significant assistance to the governments for achieving SDG-3. However, there are various challenges associated with the use of these technologies, mainly due to the involvement of human subject. The use of proposed nexus requires patients and general users to share lot of personal and family data, which raises privacy and security concerns; this is a crucial challenge because globally accepted standardization and legal frameworks are not yet developed. There are also issues pertaining to outdated infrastructure, need for processing high volumes of data, increasing vulnerabilities, and user resistance for adoption of technology. Some of the measures to manage these challenges include ensuring performance and reliability of the technology solutions, developing interoperable solutions and developing internationally accepted ethical, security and legal frameworks. This chapter sheds light on the major challenges and way forward for adopting the IoT-DS-AI nexus in an attempt to achieve SDG-3. Due to the increasing affordability and acceptance of IoT, DS and AI technologies by the patients and doctors, disruptive applications have been developed over the past decade. As the funds by venture capitalists, public and private sectors continue to grow in the industry, there are chances of even more rapid development and adoption. The prospect IoT, DS and AI in the healthcare is promising as new functions are being added into the healthcare products services with technological advances in all the domains of IoT-DS-AI nexus earlier illustrated in Fig. 1.4 . As this nexus promises to improve the quality of care both at individual and population level, it can largely contribute to the achievement of SDG 3. The rapidly advancing capabilities in the hardware, communication techniques, big data analytics are revolutionizing the way healthcare is delivered. For example, AI techniques like predictive analytics and natural language processing are being used to anticipate patient needs and improve diagnostic accuracy. Similarly, Data Science methods such as data mining and statistical modeling help uncover patterns in patient data, leading to more personalized treatment plans. IoT devices, equipped with advanced sensors and connectivity, facilitate continuous monitoring and real-time data collection, ensuring that healthcare providers can respond promptly to any changes in a patient’s condition. Together, these technologies enhance patient outcomes, streamline healthcare operations, and pave the way for innovative treatments and interventions. The end-to-end connected healthcare system starting at the patient’s wearables or ambient sensors and ending at the central dashboards/physician’s devices is expected to arrive soon. The technology will be mainly beneficial for the chronic patients, and since chronic disease management is not a once-off event, a continuously evolving IoT-DS-AI nexus to facilitate holistic monitoring and management. Unlike the conventional healthcare systems where the diagnosis and treatment strategies were largely based on the population averages, the use of computing and communication technologies ensures highly customized medical assessment and administration (Shaik T, Wiley Interdiscip Rev: Data Min Knowl Discov 2023:e1485, 2023). However, the critical scenarios requiring generating/collecting data from multiple points involving diverse technologies and stakeholders give rise to several open issues and challenges. We present some of the major challenges and recommendations for realizing the use of IoT-DS-AI nexus in the healthcare: