Field of practice: LARIISA: smart digital solutions to support decision-making in Family Health Strategy management.

The LARIISA collaborators group has been conducting research and development of technological solutions to support decision-making in health systems since 2009. GISSA, a cloud system resulting from the scientific and technological evolution of the LARIISA project, is among the solutions produced. This paper aims to describe the developing trend of GISSA©, a technological tool supporting the Family Health Strategy in northeastern Brazil, pointing out challenges, paths, and potentialities.

EPMOSt: an energy-efficient passive monitoring system for wireless sensor networks.

Monitoring systems are important for debugging and analyzing Wireless Sensor Networks (WSN). In passive monitoring, a monitoring network needs to be deployed in addition to the network to be monitored, named the target network. The monitoring network captures and analyzes packets transmitted by the target network.

A routing protocol based on energy and link quality for Internet of Things applications.

The Internet of Things (IoT) is attracting considerable attention from the universities, industries, citizens and governments for applications, such as healthcare, environmental monitoring and smart buildings. IoT enables network connectivity between smart devices at all times, everywhere, and about everything. In this context, Wireless Sensor Networks (WSNs) play an important role in increasing the ubiquity of networks with smart devices that are low-cost and easy to deploy.

Improving prediction accuracy for WSN data reduction by applying multivariate spatio-temporal correlation.

This paper proposes a method based on multivariate spatial and temporal correlation to improve prediction accuracy in data reduction for wireless sensor networks (WSN). Prediction of data not sent to the sink node is a technique used to save energy in WSNs by reducing the amount of data traffic. However, it may not be very accurate.