Objectives The Internet of Things (IoT) and its applications are growing simultaneously. These applications need new intelligent devices along heterogeneous networking. Which makes them costly to implement indeed. Platforms and open devices designed for open-source hardware are possible solutions. This research was conducted under an IoT design, implementation, and assessment model for the remote monitoring of pulse oximetry via oxygen partial saturation (SpO 2 ) and heart rate (HR) with low-energy consumption. Methods This study focused on the development of SpO 2 and HR measurements that will allow the monitoring and estimation in real time of the user's state and health related to the established parameters. Measurements were acquired and recorded using a remote web server that recorded the acquired variables for further processing. The statistical analysis data allows comparison of the registered data measured with theoretical models. Results The IoT model was developed use Bluetooth low-energy devices, which comply with low-cost and open-hardware solutions operated via ‘HTTP requests’ for data transmission and reception from a cloud server to an edge device. Network performance assessment was conducted to guarantee the availability and integrity of the acquired values and signals. The system measured SpO 2 and HR variables. The most significant result was to achieve energy consumption 20% lower than that of devices in the market. Conclusions In summary, the acquired data validation based on the IoT model had a transmission error of 0.001% which proves its applicability in healthcare.

The implementation of the Internet of things in healthcare is a promising challenge to achieve coverage for a bigger number of users in different places at lower costs. Internet of things might mean better technology regarding response time and proper control of medical parameters. This study introduces an Internet-of-things system for healthcare with possibilities to control medical variables according to recent breakthroughs in sensors and data processing. The goal of the system is to optimize the development of applications to obtain variables in real time and with less energy consumption. The proposed model is validated on the measurement and monitoring of oxygen saturation, heart rate, and body temperature in patients with respiratory disorders. This was achieved by the optimization of data acquisition, integrated into a secure architecture using Message Queuing Telemetry Transport protocol. A cloud architecture with interconnection to low-cost and open-source devices was implemented, which interconnect to the sensors and actuators' network. The experimental results were statistically treated against the device pattern data, through hypothesis tests for mean differences to probe the accuracy of the model. Finally, the proposed model demonstrates an efficient performance in several clinical parameters, such as oxygen saturation and heart rate per minute.

The interest on firefly approaches to the problem of synchronizing the nodes of a wireless ad hoc communication network is rising, because of its efficiency and efficacy. In this paper we show that it is enough to have an indirect interaction among nodes, either spatially (through multi-hop paths), or temporally (through mobility) to achieve synchronism among them. As the interactions among nodes increases, global synchronization emerges faster.

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