| Resumo: | Internet of Things (IoT) systems are experiencing rapid growth due to their applicability in several domains, from smart cities to healthcare among many. In these systems, devices communicate with each other, or with infrastructure, resorting to machine-to-machine (M2M) communications. Since many of these devices are simple systems, with weak processing capacity, lightweight M2M protocols were developed such as Constrained Application Protocol (CoAP) and Messaging Queue Telemetry Transport (MQTT) as well as frameworks to support M2M communications. As expected, there are challenges when developing M2M and IoT applications: interoperability, scalability, standardisation, among others. Therefore, several M2M standards were created to overcome these issues, with oneM2M being one of them. Nowadays, there are multiple devices available that have an embedded WiFi interface, thus, when inserted in an IoT system, these devices do not need a gateway (GW) to access the Internet since WiFi is one of the most common technologies at Internet boundary. This is a key feature because it increases the system's pervasiveness as well as the overall cost of the system. Additionally, these devices, such as the ESP32 module, offer sleep modes that allow exploiting the power management features by the IEEE 802.11 standard. Healthcare institutions always strive to provide the best services concerning the reliability, safety and comfort of the patients. To do so, IoT technologies have been embraced and developed in recent years to improve these services. The work proposed in this dissertation is an end-to-end continuous monitoring system via IoT capable of monitoring a patient's vital signs and displaying them to the medical personnel. Moreover, the system can be applied to a wide range of application scenarios from emergency wards and home environment to sports training and competition. The system has two major components, a low-cost and low-power WiFi-enabled wearable device for the user and, at the upper end, a monitoring interface for the medical personnel. The wearable is composed by a MAX30100/MAX30102 PhotoPletysmoGraphy (PPG) sensor to measure the heart rate and oxygen saturation levels, an ESP32 with a built-in WiFi antenna to process and send the sensor data to the monitoring system and, finally, a Lithium Polymer (LiPo) battery to power-up the previous two components. At the upper end, the monitoring interface is composed of a time-series database to store all the data, a graphics visualisation software of patient's vital signs and a Graphic User Interface (GUI) serving as a control panel. Additionally, the system relies on the oneM2M standard for the interoperability concerning the architecture and follows a publish-subscribe communication model due to its efficiency in sensing and remote monitoring. Furthermore, the goal of this dissertation is to develop a low-cost and energy-efficient monitoring system while not compromising the reliability and robustness of traditional machines and systems.
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