A novel and secure IoT based cloud centric architecture to perform predictive analysis of users activities in sustainable health centres

Diabetes, blood pressure, heart, and kidney, some of the diseases common across the world, are termed 'silent killers'. More than 50% of the world's population are a ected by these diseases. If suitable steps are not taken during the early stages then severe complications occur from these diseases. In the work proposed, we have discussed the manner in which the Internet- of-Things based Cloud centric architecture is used for predictive analysis of physical activities of the users in sustainable health centers. The architecture proposed is based on the embedded sensors of the equipment rather than using wearable sensors or Smartphone sensors to store the value of the basic health- related parameters. Cloud centric architecture is composed of a Cloud data center, Public cloud, Private cloud, and uses the XML Web services for se- cure and fast communication of information. The architecture proposed here is evaluated for its adoption, prediction analysis of physical activities, e - ciency, and security. From the results obtained it can be seen that the overall response between the local database server and Cloud data center remains almost constant with the rise in the number of users. For prediction analysis, If the results collected in real time for the analysis of physical activities ex- ceed any of the parameter limits of the de ned threshold value then an alert is sent to the health care personnel. Security analysis also shows the e ective encryption and decryption of information. The architecture presented is e ec- tive and reduces the proliferation of information. It is also suggested, that a person su ering from any of the diseases mentioned above can defer the onset of complications by doing regular physical activities.http://link.springer.com/journal/110422018-09-01hb2016Electrical, Electronic and Computer Engineerin

The mining minds digital health and wellness framework

The provision of health and wellness care is undergoing an enormous transformation. A key element of this revolution consists in prioritizing prevention and proactivity based on the analysis of people’s conducts and the empowerment of individuals in their self-management. Digital technologies are unquestionably destined to be the main engine of this change, with an increasing number of domain-specific applications and devices commercialized every year; however, there is an apparent lack of frameworks capable of orchestrating and intelligently leveraging, all the data, information and knowledge generated through these systems. This work presents Mining Minds, a novel framework that builds on the core ideas of the digital health and wellness paradigms to enable the provision of personalized support. Mining Minds embraces some of the most prominent digital technologies, ranging from Big Data and Cloud Computing to Wearables and Internet of Things, as well as modern concepts and methods, such as context-awareness, knowledge bases or analytics, to holistically and continuously investigate on people’s lifestyles and provide a variety of smart coaching and support services. This paper comprehensively describes the efficient and rational combination and interoperation of these technologies and methods through Mining Minds, while meeting the essential requirements posed by a framework for personalized health and wellness support. Moreover, this work presents a realization of the key architectural components of Mining Minds, as well as various exemplary user applications and expert tools to illustrate some of the potential services supported by the proposed framework. Mining Minds constitutes an innovative holistic means to inspect human behavior and provide personalized health and wellness support. The principles behind this framework uncover new research ideas and may serve as a reference for similar initiatives.N/