Brazilian agriculture production requires new types of rural buildings that are more sustainable, economical, and well adapted to their environment. Furthermore, these buildings are no longer simple living quarters, but a way of valuing rural workers. Thus, this study aimed to create a linear programming model for optimizing decision-making when different techniques and construction materials are combined to build rural housing dwellings, thereby enabling an assessment of both the cost and comfort of such buildings. The research considered localizing network facilities via analogies in order to adapt a budget matrix. Three main criteria were applied: cost, runtime, and the environmental comfort provided. The model comprised six construction systems, three types of sealing masonry, two types of roofing, and four types of tiles. Simulations were performed for two Brazilian states, considering the same reference date of validation and comparison. Each input variable resulted in a different construction model. It was demonstrated that the new industrialized construction technologies are advantageous since they provide faster execution, competitive prices, and sustainable raw materials, whilst the application of the criteria to the traditional system of reinforced concrete is also feasible. The linear programming model offers its users an additional decision-making tool for construction systems, enabling time and resource optimization.

Owing to the exponential growth of the human population and problems related to food supply, research focused on finding the most suitable approach to manage and geographically explore the environment using sustainable technologies stand out. The present study aims to produce a consistent interpolation of historical series of enthalpy (H) resulting in a thematic map of enthalpy, using the spline method as a kriging option in areas with few sampling points. The thematic map considers thermal comfort conditions to produce broiler chickens, that could be used as a management tool to reduce power consumption due to the cooling process of the facilities. It was verified that spline is an efficient method to create a suitable thematic maps representations of areas presenting a few sampled units. The geographical representation of enthalpy allowed the evaluation of the environments, concluding that the state of Mato Grosso do Sul, Brazil is inadequate for broiler chickens production without suitable thermal cooling systems. Evidence suggests introduction of aviculture in areas still unexplored, e.g., Chapadão do Sul and Sete Quedas.

With the advancement of smart sensors and the Internet of Things, innovative technologies for environmental monitoring and rural installations have become solutions to increase production sustainably. Thus, this work analyzes the application of smart sensors and the Internet of Things (IoT) in the environmental monitoring of rural facilities, aiming to promote sustainability and efficiency in agricultural production. Smart sensors can collect environmental data in real-time, which is essential in rural environments. IoT enables communication and integration of this data. These technologies bring several benefits, such as improvements in efficiency, productivity, and sustainability. The study addresses types of sensors used in monitoring, such as optical, acoustic, chemical, and physical, in addition to monitored parameters, such as air and soil quality. Emerging technologies are also explored, including wireless network sensors, multispectral monitoring, microsatellites, blockchain, and virtual reality. The review includes case studies on successful applications of IoT and sensors in contexts such as smart irrigation, precision agriculture, and animal facility monitoring. It is concluded that these technologies have a high potential to contribute to more sustainable agricultural systems and animal production. Challenges such as privacy, security, and ethical use of data are highlighted.

Cuidar do bem-estar e da saúde dos trabalhadores é um princípio básico de engenharia, que compreende estudos científicos e visa alcançar um resultado positivo no final dos processos. O uso de unidades de processamento e armazenamento de grãos é vantajoso, pois permite o armazenamento de produtos por longos períodos. Por outro lado, esses locais oferecem riscos aos trabalhadores. Atualmente, existe um grande número de pesquisas que utilizam sistemas especializados para auxiliar na tomada de decisões. A Lógica Fuzzy é uma das mais utilizadas, pois apresenta fácil manuseio e interpretação dos resultados. Assim, este estudo teve como objetivo utilizar a Lógica Fuzzy na Engenharia de Segurança do Trabalho, a fim de elaborar um modelo matemático que represente os níveis de risco de acidentes nas Unidades de Processamento e Armazenamento de Grãos e que possa ser utilizado como ferramenta para auxiliar na tomada de decisões. A possibilidade de acidentes; exposição ao risco; e a experiência dos trabalhadores foram consideradas variáveis de entrada. A resposta da simulação foi o risco de ocorrência de acidente ocupacional. Como conclusão, foi possível verificar que a Lógica Fuzzy foi tão eficiente quanto uma ferramenta de engenharia para representar riscos de acidentes. O cumprimento das Normas de Regulamentação (NR) e a "Experiência dos Trabalhadores"podem impactar o "Risco de acidente"nas unidades de processamento e armazenamento de grãos.

This study analyzed the impact of regulatory changes on the implementation of photovoltaic solar energy projects in the State of Mato Grosso do Sul, focusing on the amendments introduced by Law 14.300. The research explored solar generation conditions in various regions, highlighting the influence of geographic location on the productivity of photovoltaic systems. Using fuzzy logic, the attractiveness of solar energy was assessed in different scenarios, relating variables such as productivity, tariffs, and consumption. The results indicate that increases in productivity and tariffs are positively correlated with the attractiveness of solar energy. Additionally, an average increase in the payback period was observed in response to the new regulations. However, specific conditions, such as reduced installation costs, were identified that could mitigate this increase in payback. The study highlighted that adapting to the new regulatory policies could open significant opportunities for distributed generation, particularly in the agricultural sector, contributing to the energy and economic sustainability of the Mato Grosso do Sul region. Fuzzy logic was essential for modeling decision support systems, enabling a precise analysis of the regulatory policies' implications for the economic viability of solar energy projects.