A significant and very extended approach for Smart Cities is the use of sensors and the analysis of the data generated for the interpretation of phenomena. The proper sensor location represents a key factor for suitable data collection, especially for big data. There are different methodologies to select the places to install sensors. Such methodologies range from a simple grid of the area to the use of complex statistical models to provide their optimal number and distribution, or even the use of a random function within a set of defined positions. We propose the use of the same data generated by the sensor to locate or relocate them in real-time, through what we denominate as a ‘hot-zone’, a perimeter with significant data related to the observed phenomenon. In this paper, we present a process with four phases to calculate the best georeferenced locations for sensors and their visualization on a map. The process was applied to the Guadalajara Metropolitan Zone in Mexico where, during the last twenty years, air quality has been monitored through sensors in ten different locations. As a result, two algorithms were developed. The first one classifies data inputs in order to generate a matrix with frequencies that works along with a matrix of territorial adjacencies. The second algorithm uses training data with machine learning techniques, both running in parallel modes, in order to diagnose the installation of new sensors within the detected hot-zones.
Este trabajo presenta una implementación de una aplicación llamada API REST para evaluar el rendimiento de una aplicación web por medio del registro de las variables de la interfaz de sincronización de navegación. La aplicación se base en código abierto como Mongo y Node.js. La evaluación del rendimiento considera el retardo de carga y ejecución de la aplicación en un navegador web, e implica una percepción de satisfacción por parte del usuario que depende del tiempo de carga, si transcurre entre 100 y 300 ms, la percepción se considera negativa y es posible que el usuario la abandone. Por lo que es importante para cualquier proveedor de servicios, considerar esos tiempos para mejorar su calidad y asegurar la permanencia del cliente. El objetivo del trabajo es proporcionar una opción para valorar el rendimiento de cualquier aplicación web de forma sencilla, al integrar la aplicación en la plataforma del navegador web. Los resultados muestran los tiempos de retraso que tiene un usuario y esos coinciden con lo indicado en la literatura. La utilidad de contar con esta interfaz es la posibilidad de registrar estadísticos durante el acceso y mejorar la experiencia del usuario para garantizar su permanencia.
Se espera que estos trabajos sean de utilidad para otros investigadores que abordan temas relacionados, y a su vez, para que el público general pueda identificar las situaciones que se presentaron durante la pandemia y conocer propuestas al respecto.
In the last three years, stress has intensified due to COVID-19, so it is relevant to seek strategies to identify and cope with it, since it affects the daily life of any person in their emotional, physical, and psychological aspects, particularly among young people aged 18 to 25 years. The objective of this work is to make a proposal of the mobile application Stressting as a strategy, because mobile devices have high local penetration and acceptance among young people, to identify stress levels and prevent crisis situations. The design of Stressting was made with UML, after applying a survey with a stress diagnosis section by means of the Perceived Stress Scale with 10 items to determine the level of stress in university students through a quantitative, descriptive, and correlational study in a sample of 34 students, and unlike other applications it considers a diagnosis and a contact list for personalized attention. The scale was chosen because it has good internal consistency and is one of the most widely used and known internationally. The survey allowed us to know the stress level of the students and to corroborate the interest student in the application. The application is designed to diagnose stress and provide recommendations at the same time. The survey data was processed with Excel and shows that 58.82% of the students present moderate stress and 14.7% high stress, and that males present more stress than females. The scale has a good internal consistency with Alpha Crobach coefficient of 0.816. Stressting will be available free of charge and will allow the generation of general reports that can strengthen their integral formation with the follow-up of institutional tutoring. However, it is important that the institution implements workshops for coping with stress and the development of life skills.
Smart cities have been proposed as information technology strategies to generate solutions for the benefit of large cities to improve their quality of life, through phenomena identification tools that use artificial intelligence. Some work has been aimed at developing the infrastructure for monitoring events and the Internet of things, others merely on data analytics without an application system context. This work cites various investigations on data science processes of the smart cities and reports some of its works whose main topics are planning for the start of a smart city, the framework for the analysis of smart cities, and smart cities big data algorithms for sensors location. In these cases, the experiences in these cases are described as well as the trend towards a new process with the form of monitoring-analysis-evaluation-found pattern-driving object-decision-making and the future of smart cities is finally discussed.
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