Articles

Emerging smart medical instruments combined with advanced smart industrial equipment facilitate the collection of vast volumes of critical data. This data not only enables significantly more accurate and cost-effective diagnosis and maintenance but also enriches the datasets available for AI algorithms, leading to improved insights and outcomes. The integration of high-speed and ultra-reliable telecommunications infrastructure is crucial, as it supports the cloud model. This model allows for off-device aggregation in the cloud, which effectively offloads infrastructure demands and provides an extended runway for future technological improvements before the deployment of the next generation of devices. However, in certain scenarios, latency and bandwidth limitations present significant challenges. These limitations require that a substantial amount of AI and machine learning processing is conducted directly on the transmitted data, which places rigorous demands on both the processing subsystems and the communications links themselves. The current project directly addresses the accelerator side of this multifaceted issue. It will carry out comprehensive end-to-end demonstrations leveraging pilot 5G networks and telemedicine facilities, collaborating closely with major industry participants to showcase the capabilities and potential of this innovative technology. This collaborative effort is essential to pushing the boundaries of what is possible in smart medical instruments and industrial applications [1].

This work details how the integration of cloud computing and advanced data engineering can innovate and reshape patient care and digital infrastructure. In the healthcare sector, cloud services offer the necessary support to generate digitally-oriented services and service kits. These services can contain high levels of availability, low levels of latency, and on-demand scaling capabilities, while following the strictest data protection laws and regulations. On the other hand, these services can be combined with data engineering techniques to construct an ecosystem that enhances and adds an optimized data layer on any cloud environment. This ecosystem includes technologies to acquire, process, and manage healthcare data while respecting all regulatory obligations and institutions and can be part of a comprehensive digitalization strategy. The objective is to augment the healthcare services that the industry offers by leveraging healthcare data and AI technologies. Designed services, processes, and technologies can be described either as industry-agnostic services or healthcare-specific services that process and manage electronic healthcare records (EHR). Industry-agnostic services offer a set of tools and methodologies to conduct optimized data experiments. The goal is to exploit any variety, velocity, volume, and veracity of medical data. Healthcare-specific services offer a set of tools and methodologies to connect to any common EHR vendor in a privacy-preserving manner. Participating companies are thus able to hold, share, and make use of healthcare data in real-time. The proposed architecture can be transformative for the healthcare industry, opening up and facilitating experimentation on new and scalable service models. The transition to a more digital health approach would help overcome the limits encountered in traditional settings. Limitations in the availability of healthcare facilities and healthcare professionals have underpinned the increasing share of telemedicine in the care process. However, the record-keeping of the patients that undergo care outside of traditional healthcare facilities is often missing and can severely influence the continuity of treatment. Identifying new methods to implement disease prevention and early intervention processes is crucial to avoid more extensive treatment and to support those on multiple line therapies. For chronic patients, having a service available that monitors the state of health and intervenes when parameters go off the wanted range is crucial. However, the same patients are the most under the influence of the decision of care providers; a second opinion might be given remotely which the patient can access at any time on-demand. To address these different kinds of services, an ecosystem composed of a dictionary's worth data layer is outlined, able to live and operate seamlessly in any cloud environment. This future work's envisioned outcome is the rapid evolution and re-definition of the European healthcare landscape.