ResumenEn este trabajo se presentan los resultados obtenidos en el reconocimiento de plagas utilizando la visión de máquina por computador como elemento de diagnóstico. La captura de las imágenes se realizó por medio de un agente robótico aéreo (drone) equipado con una cámara, lo que permitió capturar las imágenes del estado de las hojas de un cultivo de la planta conocida como 'flor de azúcar' (Begonia semperflorens). Estas imágenes fueron procesadas utilizando técnicas de visión de máquina con el fin de identificar el posible ataque de plagas en el cultivo. Las técnicas utilizadas corresponden a filtros morfológicos, difuminado gaussiano y filtrado HSL. Como resultado principal de este trabajo se detectaron perforaciones de hojas ocasionadas por el ataque de plagas, específicamente babosas, caracoles, arañas rojas y minadoras.Palabras claves: Procesamiento de imágenes, detección de plagas, monitoreo de cultivos, filtros morfológicos, difuminado gaussiano. AbstractNowadays, an important element in farming, is the use of technology, based on the analysis of the different factors that affect the succesfull development of the crops. The results are presented in the recognition of pests, in this work a computer machine vision, as a diagnostic was used. The images capturing were doing with a robotic air agent, equipped with a camera, capturing images of the state of a crop of a plant called 'Flor de azúcar' (Begonia semperflorens). These images are processed using machine vision techniques to identify the possible attack of pests on the crop. The techniques used are morphological filters, Gaussian blur filter and HSL. The main result of this work was accomplished, perform the detection of the perforation of the leaves as a result of pest attack, specifically slugs, snails, spider mites and leafminers.

Abstract: The implementation of Manufacture and Automation techniques is mandatory in the current world. Mainly, the enhancement and progress of healthcare are fundamental in wellbeing improvement. This paper points to the utilization of the Internet of Things (IoT) and Industry 4.0 concepts oriented to the optimization of a Smart Hospital using the Hospital Emergency Department (HED) as a case study. This proposal focuses on the development of a smart Hospital-based of the IoT, Industry 4.0, Health 4.0, and other current technology. On the other hand, the use of a computational simulation tool like the Discrete Event Simulation Model (DES) will allow the test, recognition, and reduction of bottlenecks in the HED workflow. The issue given by the bottlenecks is automatically controlled using an improved dynamic shift management proposal based on control theory, forecasting methods, and telemedicine. The results show an improvement in the use of the resources and a reduction of the length of stay that directly reduces the HED mortality rate, improving the service quality. The objective of this paper is to propose a simulation tool-based on DES for a selected HED, using forecasting methods of the patients’ arrival in a HED using the Autoregressive integrated moving average (ARIMA) model. Following the forecasted entries, a proposal for bottleneck avoidance using a HED DES was realized. The forecasting data provided useful predictive information for the improvement of the HED workflow. As well as the analyzed data of a traditional HED system is helpful to solve the overcrowding problem. Finally, the use of simulation tools allows the test and validation of novel proposals for two smart HED optimization proposals following e-Health and Hospital 4.0 principles.

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