Abstract:

Finding solutions to the world’s greatest challenges is a process of an exponentially increasing complexity. From major issues such as global warming, large scale conflicts, poverty, and discrimination to more abstract ones, for example, privacy and data protection, nowadays societies are dealing with problems converging into massive convolutions that natural algorithms are unable to solve. In computational terms, problems that lack direct, immediate approach are called complex, and they are conventionally divided into manageable subproblems. Perhaps the most pressing complex problem modern society encounters is the necessity of an increasing healthcare quality as a key aspect in human life continuity. Health must be defined by a constantly changing state of preservation: while improving the quality of life is mandatory, the knowledge in treating problems is equally important with the ability of predicting them. Continuously increasing mortality rate is a frequently disputed matter, nevertheless, some concerning areas, that we would consequently associate with the manageable subproblems, are often neglected and yet to be researched. One such concerning area that we are considering in our study is the role of geriatric care in our everyday life. Globally, over 12 million deaths are related to ageing population, corresponding to almost 30% of the global deaths. Despite many of them being imminent, numerous deaths are associated with medical errors such as incorrect medical decisions. In an era of everlasting emerging technologies, it is unthinkable to overlook their use in medical practice, as potential subjects of statistical change. Therefore, one important aspect outlined in this paper is the recognition of IoT-powered applications role in developing an augmented, smart healthcare system, and it is realized by achieving our main goal: providing findings and results using the foundations of an advanced, efficient, and scalable conceptual framework.