# Smart Healthcare: Exploring the Internet of Medical Things with Ambient Intelligence
## 1 Introduction  
In recent years, healthcare management systems have encountered increasing strain. While healthcare services predominantly center around hospitals, chronic diseases remain a formidable challenge worldwide. Cardiovascular diseases notably rank as a leading cause of death in regions such as the EU [1]. This strain on healthcare has become particularly apparent during pandemics such as COVID-19 and swine flu, with healthcare centers sometimes stretched to their limits. Additionally, patients often require ongoing monitoring post-surgery until their health stabilizes; however, current practices often entail frequent and burdensome hospital visits, which can prove costly, inefficient, and inconvenient for patients in need of routine checkups. Despite technological advances, many industrialized nations are grappling with significant challenges regarding the quality and affordability of healthcare services. Consequently, the sustainability of the healthcare sector is increasingly questioned, necessitating the utilization of makeshift facilities and telehealth technologies to ensure the continued viability of healthcare systems.  
only brief glimpses of physiological conditions, and lack continuous monitoring over extended periods.  
The limitations of contemporary healthcare systems have spurred interest in alternative approaches aimed at promoting effective personalized care. Among these approaches, Ambient Intelligence (AMI) and the Internet of Medical Things (IoMT) represent a paradigm shift towards intelligent healthcare. AMI, renowned for its capacity to cultivate adaptable and contextually aware environments, holds vast potential for revolutionizing healthcare facilities into intelligent ecosystems that cater to the unique needs of individual patients [3]. Simultaneously, IoMT technologies can facilitate the utilization of interconnected medical devices and sensors, providing unparalleled opportunities for real-time monitoring, data collection, and remote patient management [4]. The integration of Artificial Intelligence (AI) algorithms in AMI and IoMT systems enhances their capabilities by enabling advanced data analytics, predictive modeling, and decision support functionalities. The benefits of such integration can be briefly summarized as follows:  
* Automated home monitoring services
* Reduced hospital and hospice occupancy
* Reduced healthcare cost
* Personalized healthcare services
* Predictive analysis for early disease detection  
Collectively, these AI-powered technologies can usher in a new era of intelligent healthcare that prioritizes patient-centered care while optimizing operational efficiency. In response to these advancements, this paper endeavors to delve into the integration of AMI and AI in the healthcare environment through the IoMT. The focus is on exploring how the synergy between adaptive AMI environments and IoMT technologies, augmented by the analytical capability of AI, can effectively address the prevailing challenges encountered by healthcare systems with the goal of elevating the quality of patient care and ultimately enhancing healthcare outcomes. Through an exhaustive examination of the pertinent literature encompassing various components of AMI in communication, healthcare, and cutting-edge technological advancements in AI, this study aims to shed light on the myriad benefits, potential hurdles, and future trajectories associated with the utilization of AMI and AI in healthcare via the IoMT.