Projetando sistemas IdC para monitoramento remoto de pacientes que sejam interoperáveis, escaláveis ​​e sustentáveis

Abstract

Internet of Things (IoT) consists of networks of everyday objects, called ‘things’, equipped with embedded technology, sensors and actuators, capable of collecting and transmitting data through wireless network connections to the Internet. One of the big challenges in IoT is dealing with the huge amount of data produced by their things, in addition to dealing with the data heterogeneity, the varied capabilities of the things, the diverse offered services, and the different IoT platforms. For each domain and for each vendor, there is usually a specific and proprietary IoT platform, with no de facto standards it is currently being used or expected in the near future. Therefore, ensuring semantic interoperability when multiple and different IoT devices and system components must interoperate is one of the problems that needs extensive investigation in this area. In addition to generating large volumes of data that require relatively complex processing, IoT systems have become increasingly complex and hard to maintain. Furthermore, they require high scalability, availability and data throughput in the context of critical applications such as in the Health domain. IoT, Ubiquitous Computing, and Cloud Computing can be used in combination to build telemedicine systems to contribute to the Pervasive Healthcare's holistic vision of providing healthcare anywhere, anytime, to anyone. Such healthcare includes: prevention; short-term monitoring (e.g., patient at home) and long-term monitoring (e.g., elderly); incident detection and management; intervention in case of emergency; and treatment. Among the main tools of Pervasive Healthcare, Remote Patient Monitoring (RPM) stands out. According to the World Health Organization (WHO), Noncommunicable diseases (NCD) are one of the biggest challenges in Health. The four main groups of NCDs, cardiovascular diseases, Diabetes, chronic respiratory diseases and Cancer cause about 70% of deaths in the world. NCDs have a non-infectious origin, tend to be long-lasting and are the result of a combination of genetic, physiological, environmental and lifestyle factors. For a more effective treatment of NCD patients, WHO recommends a periodic monitoring of the health conditions of these patients. Some NCDs, such as Hypertension, Diabetes, Asthma and Obesity, allow for continuous RPM, enabling the patients and their health professionals to actively exert disease control. In this context, this research investigated how to design interoperable, scalable and maintainable RPM IoT systems for continuous monitoring of patients suffering from NCDs that can be monitored remotely. The main contributions of this research are: • A layered architecture to design RPM IoT systems for NCDs that can be monitored remotely. • The design of three RPM IoT systems for monitoring Hypertension, which include: - A sensor platform built in a wearable IoT device to capture the patient’s vital signs; - A mobile application running on the patient’s mobile device to pre-process the clinical data; - Two applications deployed in the cloud for processing, managing, and archiving clinical data; - An IoT semantic model deployed in the cloud to enable interoperability of different devices and system components; and - An IoT Microservices Architecture (MSA) deployed in the cloud to improve system, scalability, maintainability and data throughput. • An approach to design interoperable, scalable and maintainable RPM IoT systems for NCDs that can be monitored remotely.