A digitalization of business process through utilizing Digital Twins is an approach that assists companies to align themselves with changes of technology development, and accordingly, improve their outcomes. To take full advantage of implementing Digital Twins, the importance of the creative phase role as pillars of this technology on the performance of the other parts and overall outcome should not be overlooked. This research addresses the lack of an integrated framework for setting up the creative phase of digital twins. To design the proper framework, by relying on a qualitative empirical method, an interview with persons who are experts in the Digital Twin area was organized to collect the information about all obvious and hidden aspects of this phase and manifest what kind of entities participate in this phase, what potential challenges and obstacles exist and what solution is effective to overcome them. The structural feature of the proposed framework continuously prepares the system for changes, aiming to adopt improvement within. The findings of this study can be used as instruction by all companies that want to take the first steps toward the digital representation of physical assets, or for those who deal with Digital Twin and want to improve their systems’ interactions.

Despite their substantial economic and financial burden, modern healthcare systems are frequently criticized for their poor efficiency and inclusivity, and substantial concerns arise about their capability to provide adequate responses to the population's needs in the near future. In such context, new digital healthcare models based on advanced bio-sensing technologies are regarded as a possible solution to improve the screening and prevention processes thus improving the overall performance of the healthcare supply chains. This is particularly relevant for respiratory diseases, which are currently among the first causes of death and medical expenditures in industrialized countries. In this research, a new approach to the testing and diagnosis of respiratory diseases is proposed as a new e-health model based on a fog-based architecture and a smart device. According to such a model, the fog-based system that allows for patients’ testing through the analysis of the exhaled breath is collected using a smart device based on a novel nanostructured sensor integrated into a breathing mask, and capable of transferring relevant patient information to a centralized decision-making process. The objective of this new healthcare model is thus to improve the diagnosis process of respiratory diseases by minimizing under-diagnosed or late-diagnosed cases. The practical relevance of the approach proposed is the possibility of enabling remote diagnostics of respiratory diseases without the need for skilled medical staff and bulky equipment only available in specialized labs, thus allowing for decentralized patient testing and self-testing. The original testing method and system proposed have been validated in the lab using samples extracted from real patients.