Field of practice: LARIISA: smart digital solutions to support decision-making in Family Health Strategy management. / LARIISA: soluções digitais inteligentes para apoio à tomada de decisão na gestão da Estratégia de Saúde da Família.

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. This is a descriptive and exploratory study, based on secondary sources from the IBGE, INMET, SINAN, SIM, and SINASC, with quantitative analysis based on machine-learning techniques applied to create digital health microservices. Operating in the northeast and southeast regions, GISSA© provides information that qualifies health managers' decision-making process, improving the municipal health system's management.

O grupo de colaboradores do LARIISA realiza pesquisa e desenvolvimento de soluções tecnológicas para apoio à tomada de decisão em sistemas de saúde desde 2009. Dentre as soluções produzidas está o GISSA®, sistema em nuvem resultado da evolução científica e tecnológica do projeto LARIISA. O objetivo do presente artigo é descrever a trajetória de evolução do GISSA®, ferramenta tecnológica que apoia a Estratégia de Saúde da Família no nordeste do Brasil, apontando desafios, caminhos e potencialidades. Trata-se de um estudo descritivo e exploratório, baseado em fontes secundárias do IBGE, INMET, SINAN, SIM e SINASC, com análise quantitativa a partir de modelos de aprendizagem de máquina aplicados na criação de microserviços em saúde digital. Operando nas regiões nordeste e sudeste, o GISSA® disponibiliza informações que qualificam o processo de tomada de decisão de gestores de saúde e, consequentemente, contribui para aperfeiçoar a gestão do sistema de saúde municipal.

LARIISA: soluções digitais inteligentes para apoio à tomada de decisão na gestão da Estratégia de Saúde da Família / Field of practice: LARIISA: smart digital solutions to support decision-making in Family Health Strategy management

Resumo O grupo de colaboradores do LARIISA realiza pesquisa e desenvolvimento de soluções tecnológicas para apoio à tomada de decisão em sistemas de saúde desde 2009. Dentre as soluções produzidas está o GISSA®, sistema em nuvem resultado da evolução científica e tecnológica do projeto LARIISA. O objetivo do presente artigo é descrever a trajetória de evolução do GISSA®, ferramenta tecnológica que apoia a Estratégia de Saúde da Família no nordeste do Brasil, apontando desafios, caminhos e potencialidades. Trata-se de um estudo descritivo e exploratório, baseado em fontes secundárias do IBGE, INMET, SINAN, SIM e SINASC, com análise quantitativa a partir de modelos de aprendizagem de máquina aplicados na criação de microserviços em saúde digital. Operando nas regiões nordeste e sudeste, o GISSA® disponibiliza informações que qualificam o processo de tomada de decisão de gestores de saúde e, consequentemente, contribui para aperfeiçoar a gestão do sistema de saúde municipal.

Abstract 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. This is a descriptive and exploratory study, based on secondary sources from the IBGE, INMET, SINAN, SIM, and SINASC, with quantitative analysis based on machine-learning techniques applied to create digital health microservices. Operating in the northeast and southeast regions, GISSA© provides information that qualifies health managers' decision-making process, improving the municipal health system's management.

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. However, sensor nodes are restricted in terms of energy, processing and memory. Additionally, low-power radios are very sensitive to noise, interference and multipath distortions. In this context, this article proposes a routing protocol based on Routing by Energy and Link quality (REL) for IoT applications. To increase reliability and energy-efficiency, REL selects routes on the basis of a proposed end-to-end link quality estimator mechanism, residual energy and hop count. Furthermore, REL proposes an event-driven mechanism to provide load balancing and avoid the premature energy depletion of nodes/networks. Performance evaluations were carried out using simulation and testbed experiments to show the impact and benefits of REL in small and large-scale networks. The results show that REL increases the network lifetime and services availability, as well as the quality of service of IoT applications. It also provides an even distribution of scarce network resources and reduces the packet loss rate, compared with the performance of well-known protocols.