Diseño del sistema de control de una planta de residuos térmicos

This article deals with the development of the design of a temperature control system for a vegetable waste treatment plant, specifically the Verilog hardware description language is used on a PSoC CY8-CKIT-059. The system has three stages of information handling, in the first instance the conversion of a decimal voltage value represented by a pulse to bits is performed, then a component in charge of the transformation entered in bits to a new bit sentence that will feed the terminals of different seven-segment displays that make up the graphical interface of the system will be added.Este artículo trata sobre el desarrollo del diseño de un sistema de control de temperatura para una planta de tratamiento de desechos vegetales, específicamente se usa el lenguaje de descripción por hardware Verilog sobre un PSoC CY8-CKIT-059. El sistema cuenta con tres etapas de manejo de información, en primera instancia se realiza la conversión de un valor de tensión decimal representado por un pulso a bits, luego de ello se agregara un componente encargado de la transformación ingresada en bits a una sentencia de bits nueva que alimentara los terminales de distintos displays de siete segmentos que componen la interfaz gráfica del sistema

Remote sensing imagery detects hydromorphic soils hidden under agriculture system

Abstract The pressure for food production has expanded agriculture frontiers worldwide, posing a threat to water resources. For instance, placing crop systems over hydromorphic soils (HS), have a direct impact on groundwater and influence the recharge of riverine ecosystems. Environmental regulations improved over the past decades, but it is difficult to detect and protect these soils. To overcome this issue, we applied a temporal remote sensing strategy to generate a synthetic soil image (SYSI) associated with random forest (RF) to map HS in an 735,953.8 km2 area in Brazil. HS presented different spectral patterns from other soils, allowing the detection by satellite sensors. Slope and SYSI contributed the most for the prediction model using RF with cross validation (accuracy of 0.92). The assessments showed that 14.5% of the study area represented HS, mostly located inside agricultural areas. Soybean and pasture areas had up to 14.9% while sugar cane had just 3%. Here we present an advanced remote sensing technique that may improve the identification of HS under agriculture and assist public policies for their conservation