Atmosphere: Context and situational-aware collaborative IoT architecture for edge-fog-cloud computing

The Internet of Things (IoT) has grown significantly in popularity, accompanied by increased capacity and lower cost of communications, and overwhelming development of technologies. At the same time, big data and real-time data analysis have taken on great importance and have been accompanied by unprecedented interest in sharing data among citizens, public administrations and other organisms, giving rise to what is known as the Collaborative Internet of Things. This growth in data and infrastructure must be accompanied by a software architecture that allows its exploitation. Although there are various proposals focused on the exploitation of the IoT at edge, fog and/or cloud levels, it is not easy to find a software solution that exploits the three tiers together, taking maximum advantage not only of the analysis of contextual and situational data at each tier, but also of two-way communications between adjacent ones. In this paper, we propose an architecture that solves these deficiencies by proposing novel technologies which are appropriate for managing the resources of each tier: edge, fog and cloud. In addition, the fact that two-way communications along the three tiers of the architecture is allowed considerably enriches the contextual and situational information in each layer, and substantially assists decision making in real time. The paper illustrates the proposed software architecture through a case study of respiratory disease surveillance in hospitals. As a result, the proposed architecture permits efficient communications between the different tiers responding to the needs of these types of IoT scenarios

Atmosphere: Context and situational-aware collaborative IoT architecture for edge-fog-cloud computing

The Internet of Things (IoT) has grown significantly in popularity, accompanied by increased capacity and lower cost of communications, and overwhelming development of technologies. At the same time, big data and realtime data analysis have taken on great importance and have been accompanied by unprecedented interest in sharing data among citizens, public administrations and other organisms, giving rise to what is known as the Collaborative Internet of Things. This growth in data and infrastructure must be accompanied by a software architecture that allows its exploitation. Although there are various proposals focused on the exploitation of the IoT at edge, fog and/or cloud levels, it is not easy to find a software solution that exploits the three tiers together, taking maximum advantage not only of the analysis of contextual and situational data at each tier, but also of two-way communications between adjacent ones. In this paper, we propose an architecture that solves these deficiencies by proposing novel technologies which are appropriate for managing the resources of each tier: edge, fog and cloud. In addition, the fact that two-way communications along the three tiers of the architecture is allowed considerably enriches the contextual and situational information in each layer, and substantially assists decision making in real time. The paper illustrates the proposed software architecture through a case study of respiratory disease surveillance in hospitals. As a result, the proposed architecture permits efficient communications between the different tiers responding to the needs of these types of IoT scenarios.This work was partially supported by the Spanish Ministry of Science and Innovation and the European Regional Development Fund (ERDF) under project FAME [RTI2018-093608-B-C33] and excellence network RCIS [RED2018-102654-T]. We also thank Carlos Llamas Jaén for his support with the setting up of the performance evaluation tests

Recursos tecnológicos en el desarrollo del aprendizaje autónomo en estudiantes de primaria de una universidad pública, Trujillo 2021

El objetivo fue determinar la relación de los recursos tecnológicos y el desarrollo del aprendizaje autónomo con estudiantes de primaria de una universidad pública de Trujillo. Se aplicó un enfoque cuantitativo, de tipo básico, de diseño no experimental, transversal y correlacional. La población la conformaron 60 estudiantes y la muestra la conformaron 30 estudiantes del décimo ciclo de la carrera profesional educación primaria de una universidad pública en la ciudad de Trujillo, mediante un muestreo no probabilístico. Se encontró que los niveles de uso de recursos tecnológicos en el nivel alto son de 60,0% de los estudiantes, por lo cual la variable se utiliza en su mayoría, de forma adecuada a los recursos tecnológicos. Asimismo, los niveles de aprendizaje autónomo que el 53.33% se encuentra en el nivel alto, indicando que los estudiantes, en su mayoría, tienen la capacidad desarrollada de un aprendizaje autónomo. Se concluyó que los recursos tecnológicos tienen una relación directa y muy alta con el aprendizaje autónomo con una correlación de Spearman (Rho=0,998) con un p-valor 0,000 menor p<0,05, aumentando o disminuyendo sus niveles de forma proporcional