Diabetes mellitus (DM) is a metabolic disorder characterized by blood glucose levels above normal limits. The impact of this disease on the population has increased in recent years. It is already a public health problem worldwide and one of the leading causes of death. Recently, several proposals have been developed for better and regular monitoring of glucose. However, theses proposals do not discard erroneous readings and they are not able to anticipate a critical condition. In this work, we propose an algorithm based on the double moving average supported by an IoT architecture to prevent possible complications in elderly patients. The algorithm uses historical readings to construct a series. Given a number of periods, it is possible to calculate averages of different subsets and trends for the next periods and, in this way, the prognosis is obtained. With the prognosis, it is possible to notify the doctor and relatives in advance about a possible critical condition in the patient. The aim of our work is to validate the architecture and prognosis algorithm used for elderly persons. Tests of the algorithm and the architecture were performed with different readings and it was shown that the system generated corresponding notifications before the glucose values were higher than those defined by the WHO (World Health Organization), thus avoiding unnecessary alarms.
El presente proyecto es realizado en una compan?i?a de arneses ele?ctricos. Esta compan?i?a presenta un problema en el troquelado del circuito trenzado con el conector de sen?al del arne?s. El conector para ser troquelado necesita de una lubricacio?n en su terminal y asi? evitar dan?ar los dados de troquelado los cuales son muy costosos. El proceso de lubricacio?n se realiza de manera manual lo que ocasiona un 40% de mermas en el producto, adema?s de la contaminacio?n por el exceso de lubricante utilizado. Por lo tanto, este trabajo propone automatizar el proceso de lubricacio?n de conectores, con la finalidad de mejorar la calidad del producto. Se disen?o? e implemento? un prototipo, mediante un microcontrolador arduino MEGA 2560, obteniendo como resultado un incremento del 70% en produccio?n, y reduccio?n de tiempos muertos, asi? como la eliminacio?n de contaminacio?n por residuos to?xicos.
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