The healthcare industry is undergoing a momentous transformation with the advent of artificial intelligence (AI) and the internet of medical things (IoMT), as these technologies are significant in managing patient data, simple medical surgery, and medical personnel. This development has shown the potential to mitigate medical shortages, health issues, and global disasters. Nevertheless, the dynamic characteristics of the system and its vulnerability to intrusions give rise to apprehensions regarding the possible compromise of patient data, endangerment of life, and reputational harm. This study examines the influence of medical robots and AI-aided diagnostics on smart healthcare sustainability.
Top1. Introduction
The 21st century has seen significant technical advancements, including the emergence of the Internet of Things (Iot) and Artificial Intelligence (AI), making cities smarter (Shafik, 2023). This technological innovation has undoubtedly contributed to the progress of humanity by providing a range of services to enhance our daily lives (Taylor et al., 2016). The IoTs seek to establish connectivity between all digital entities, enabling machine-to-human (M2H), human-to-human (H2H), and machine-to-machine (M2M) communication (Chegini et al., 2019). This interconnectedness offers significant advantages in various fields, including but not limited to surveillance, agriculture, military operations, manufacturing, energy production, and healthcare (Kassim et al., 2023).
In this context, healthcare can be seen as a significant arena in which the IoT, like medical robotics, is utilized. The utilization of IoT in the healthcare sector is commonly referred to as the Internet of Medical Things (IoMT), with increased benefits like medical wearables (Shafik, 2023). The majority of IoMT apps and services in the healthcare sector have the potential to deliver high-quality and comprehensive patient care more efficiently like in surgery. These applications can be utilized in many clinical settings, including hospitals, nursing homes, communities, and private residences (Shafik, 2023).
As cities and villages get smarter, smart healthcare plays a significant role, wherein AI is extensively employed in conjunction with the IoMT to interpret the significance of collected pathological data and make prompt and accurate determinations regarding the underlying pathological problems (Muheidat et al., 2023). AIoMT technologies are extensively utilized in diverse healthcare domains, particularly in disease diagnosis, patient condition monitoring, clinical environment monitoring, surgical procedures, and pandemic situation management/surveillance (Kumar et al., 2023). These technologies are highly prevalent due to their ubiquitousness and offer advantages such as facilitating prompts and accurate decision-making. These advancements have also led to the development of numerous healthcare apps, including those focused on senior care, remote health monitoring, chronic illness management, and fitness programs (Baker et al., 2023).
AIoMT and medical robotics have garnered significant interest from academic institutions, industry professionals, and researchers recently (Chang et al., 2023). This interest stems from the potential of AIoMT to address the substantial strain on healthcare systems caused by various factors, including a scarcity of medical personnel, the emergence of global pandemics like SARS and the ongoing COVID-19 crisis, the increasing elderly population, and the prevalence of chronic illnesses (Almujally et al., 2023). Due to the dynamic nature of the AIoMT ecosystem and its handling of sensitive patient data, it has become a prime target for cyber attackers who are increasingly focused on exploiting the evolving attack vectors in the contemporary threat landscape (Nozari et al., 2023).