The environment consists of the interaction between the physical, biotic, and anthropic means. As this interaction is dynamic, environmental characteristics tend to change naturally over time, requiring continuous monitoring. In this scenario, the internet of things (IoT), together with traditional sensor networks, allows for the monitoring of various environmental aspects such as air, water, atmospheric, and soil conditions, and sending data to different users and remote applications. This paper proposes a Standard-based Internet of Things Platform and Data Flow Modeling for Smart Environmental Monitoring. The platform consists of an IoT network based on the IEEE 1451 standard which has the network capable application processor (NCAP) node (coordinator) and multiple wireless transducers interface module (WTIM) nodes. A WTIM node consists of one or more transducers, a data transfer interface and a processing unit. Thus, with the developed network, it is possible to collect environmental data at different points within a city landscape, to perform analysis of the communication distance between the WTIM nodes, and monitor the number of bytes transferred according to each network node. In addition, a dynamic model of data flow is proposed where the performance of the NCAP and WTIM nodes are described through state variables, relating directly to the information exchange dynamics between the communicating nodes in the mesh network. The modeling results showed stability in the network. Such stability means that the network has capacity of preserve its flow of information, for a long period of time, without loss frames or packets due to congestion.

The Internet of Things (IoT) is based on objects or “things” that have the ability to communicate and transfer data. Due to the large number of connected objects and devices, there has been a rapid growth in the amount of data that are transferred over the Internet. To support this increase, the heterogeneity of devices and their geographical distributions, there is a need for IoT gateways that can cope with this demand. The SOFTWAY4IoT project, which was funded by the National Education and Research Network (RNP), has developed a software-defined and virtualized IoT gateway that supports multiple wireless communication technologies and fog/cloud environment integration. In this work, we propose a planning method that uses optimization models for the deployment of IoT gateways in smart campuses. The presented models aimed to quantify the minimum number of IoT gateways that is necessary to cover the desired area and their positions and to distribute IoT devices to the respective gateways. For this purpose, the communication technology range and the data link consumption were defined as the parameters for the optimization models. Three models are presented, which use LoRa, Wi-Fi, and BLE communication technologies. The gateway deployment problem was solved in two steps: first, the gateways were quantified using a linear programming model; second, the gateway positions and the distribution of IoT devices were calculated using the classical K-means clustering algorithm and the metaheuristic particle swarm optimization. Case studies and experiments were conducted at the Samambaia Campus of the Federal University of Goiás as an example. Finally, an analysis of the three models was performed, using metrics such as the silhouette coefficient. Non-parametric hypothesis tests were also applied to the performed experiments to verify that the proposed models did not produce results using the same population.

O presente trabalho apresenta o desenvolvimento do Website de Monitoramento e Análise de Informações de Fenômenos Atmosféricos e Microclimas, uma plataforma voltada ao acompanhamento e à visualização de dados meteorológicos coletados por estações automatizadas. A aplicação foi desenvolvida com React no frontend e Node.js/Express no backend, proporcionando uma interface intuitiva e responsiva, com visual limpo e moderno. A interface interativa permite o monitoramento de temperatura, umidade, pressão, radiação solar, luminosidade, vento, precipitação e qualidade do ar. O painel principal exibe ligações para os gráficos dinâmicos de todos os fenômenos atmosféricos em páginas independentes, além de recursos flexíveis para intervalos de datas. O website também possibilita a seleção de estações meteorológicas, o ajuste de períodos de observação e a exportação de dados em formato .csv. O sistema integra o backend e o frontend, permitindo o registro de sensores, estações e localizações em um banco de dados PostgreSQL, disponibilizando essas informações à comunidade. Dessa forma, busca-se contribuir para os estudos sobre microclimas e fenômenos atmosféricos locais, tema de extrema importância para a agricultura, bem como para diversas pesquisas e aplicações científicas desenvolvidas na região.