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    Mobile application for the monitoring and control of electrical energy consumption through a meter made with Arduino
    (IJETAE Publication House, 2021-01-01)
    This year, citizens were complaining that the power companies were overcharging their bills because of the pandemic, but investigations in previous years also showed claims in Peru and internationally. In this work, the Scrum Methodology was used for the development of the mobile application and the Balsamiq tool was used for the design of the prototype. In addition, the Arduino tool was used for the electricity consumption meter. As for the case study, we developed the prototypes of the application with its functions and the methodology of how it is elaborated, at the same time we described the way in which the meter will be implemented with Arduino. The results obtained from the research are that people can compare the consumption of the bill issued by the electricity company and the consumption shown by the Arduino meter, in addition to the union of the mobile application with the meter will allow them to consult the consumption and also issue reports having a better control of electricity. This work can be implemented not only in the cities, but also in remote places where traditional meters have not been implemented. Keywords— Arduino; Mobile applications; Power consumption; Scrum methodology
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    A YOLO algorithm for pattern recognition in images of marine species in closed seasons
    (Springer Science and Business Media Deutschland GmbH, 2024-01-01)
    One of the main problems that arise in the process of extracting marine species during the closed seasons is the indiscriminate loading of marine species that are prohibited because they are in spawning season. These problems are often aggravated by the lack of transparency in inspection process, where inspectors receive bribes when they intervene with vessels on the high seas (Ministerio de la Producción in https://pescayconsumoresponsable.produce.gob.pe/presentacion.html, [1]). In addition to that, (Mar del Perú in https://mardelperu.pe/articulos_wikipesca/reglas-de-juego/, [2]) details how the process of identifying marine species does not have rigorous verification due to not having the appropriate tools and control mechanisms. For those reasons, this paper will show an implementation of a technological solution based on a Artificial Intelligence and mobile application integrated into identification and control processes of marine species in closed seasons by providing an adequate classification of the species detected by those devices. To achieve this, YOLO algorithm has been trained and used in an integrated app. YOLO is an algorithm whose architecture is based on convolutional neural networks. This algorithm, unlike other CNN-based architectures, seeks to perform detection in a single run, which allows it to be an extremely fast alternative by performing two fundamental tasks at the same time: identifying a region of interest and classifying it.