Consumo de combustible de las unidades de transporte urbano de la ciudad de Ibarra – Análisis Comprensivo de las variables

    Resumen— La presente investigación se relaciona al sector del transporte en la ciudad de Ibarra, enfocado principalmente en la organización del sistema de servicio de buses urbanos, de una parte, su planificación, y por otra, el análisis de la flota de buses mediante un diagnóstico técnico del consumo de combustibles. Finalmente se abordará un análisis de las incidencias de las combustiones en el medio ambiente. Para realizar esta investigación se utilizó fuentes primarias de información sobre el consumo diario promedio de combustible, mediante una encuesta efectuada a los conductores de las unidades de bus en función de la determinación del ciclo de conducción y también través de la utilización de tecnología portátil. Como resultados, se obtuvieron relaciones directas entre el consumo de combustible y las características de ciclo de conducción obtenido por cada unidad de transporte. Se determinaron los parámetros de conducción que pueden afectar negativamente al consumo de combustible de estas unidades. Los parámetros de conducción, así como la velocidad mínima de manejo promedio, y el incremento del número de paradas durante el trayecto hacen que el consumo de combustible de estos vehículos sea mayor, por lo cual se deben Ibarra, adoptar estilos de conducción más eficientes

BITOUR: A Business Intelligence Platform for Tourism Analysis

[EN] Integrating collaborative data in data-driven Business Intelligence (BI) system brings an opportunity to foster the decision-making process towards improving tourism competitiveness. This article presents BITOUR, a BI platform that integrates four collaborative data sources (Twitter, Openstreetmap, Tripadvisor and Airbnb). BITOUR follows a classical BI architecture and provides functionalities for data transformation, data processing, data analysis and data visualization. At the core of the data processing, BITOUR offers mechanisms to identify tourists in Twitter, assign tweets to attractions and accommodation sites from Tripadvisor and Airbnb, analyze sentiments in opinions issued by tourists, and all this using geolocation objects in Openstreetmap. With all these ingredients, BITOUR enables data analysis and visualization to answer questions like the most frequented places by tourists, the average stay length or the view of visitors of some particular destination.This work has been supported by COLCIENCIAS through a PhD scholarship. This work is supported by the Spanish MINECO project TIN2017-88476-C2-1-R.Bustamante, A.; Sebastiá Tarín, L.; Onaindia De La Rivaherrera, E. (2020). BITOUR: A Business Intelligence Platform for Tourism Analysis. ISPRS International Journal of Geo-Information. 9(11):1-23. https://doi.org/10.3390/ijgi9110671S123911Nakahira, K. T., Akahane, M., & Fukami, Y. (2012). The Difference and Limitation of Cognition for Piano Playing Skill with Difference Educational Design. Smart Innovation, Systems and Technologies, 609-617. doi:10.1007/978-3-642-29934-6_59Chua, A., Servillo, L., Marcheggiani, E., & Moere, A. V. (2016). 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On the Representativeness of OpenStreetMap for the Evaluation of Country Tourism Competitiveness

[EN] Since 2007, the World Economic Forum (WEF) has issued data on the factors and policies that contribute to the development of tourism and competitiveness across countries worldwide. While WEF compiles the yearly report out of data from governmental and private stakeholders, we seek to analyze the representativeness of the open and collaborative platform OpenStreetMap (OSM) to the international tourism scene. For this study, we selected eight parameters indicative of the tourism development of each country, such as the number of beds or cultural sites, and we extracted the OSM objects representative of these indicators. Then, we performed a statistical and regression analysis of the OSM data to compare and model the data emitted by WEF with data from OSM. Our aim is to analyze the tourist representativeness of the OSM data with respect to official reports to better understand when OSM data can be used to complement the official information and, in some cases, when official information is scarce or non-existent, to assess whether the OSM information can be a substitute. Results show that OSM data provide a fairly accurate picture of official tourism statistics for most variables. We also discuss the reasons why OSM data is not so representative for some variables in some specific countries. All in all, this work represents a step towards the exploitation of open and collaborative data for tourism.This work has been supported by COLCIENCIAS through a PhD scholarship.Bustamante, A.; Sebastiá Tarín, L.; Onaindia De La Rivaherrera, E. (2021). On the Representativeness of OpenStreetMap for the Evaluation of Country Tourism Competitiveness. ISPRS International Journal of Geo-Information. 10(5):1-22. https://doi.org/10.3390/ijgi10050301S12210