{"id":3419,"date":"2022-09-12T23:13:58","date_gmt":"2022-09-12T13:13:58","guid":{"rendered":"https:\/\/wordpress.temp.irap-dev.org\/show-me-the-way-big-data-reveals-highest-risk-schools-in-vietnam\/"},"modified":"2026-04-30T12:39:59","modified_gmt":"2026-04-30T02:39:59","slug":"show-me-the-way-big-data-reveals-highest-risk-schools-in-vietnam","status":"publish","type":"post","link":"https:\/\/irap.org\/es\/show-me-the-way-big-data-reveals-highest-risk-schools-in-vietnam\/","title":{"rendered":"Muestra el camino: Big Data revela las escuelas de mayor riesgo en Vietnam"},"content":{"rendered":"

En tres ciudades vietnamitas con m\u00e1s de 9 millones de habitantes, \u00bfc\u00f3mo podemos empezar a identificar las zonas escolares de mayor riesgo y a los ni\u00f1os que las frecuentan a diario para combatir la principal causa de muerte juvenil: los accidentes de tr\u00e1fico? \u00bfLa respuesta? El Big Data.<\/p>\n

Una metodolog\u00eda de an\u00e1lisis de macrodatos desarrollada en el marco del proyecto AI&Me ha permitido realizar an\u00e1lisis de macrodatos desde ordenadores de Ho Chi Minh City, Pleiku y Yen Bai. El an\u00e1lisis identific\u00f3 las 106 escuelas con mayor riesgo para una investigaci\u00f3n m\u00e1s exhaustiva sobre seguridad vial y prioriz\u00f3 la inversi\u00f3n de un total de 1063 escuelas analizadas.<\/p>\n

Con base en los hallazgos, el proyecto calificar\u00e1 con estrellas la seguridad de las escuelas utilizando el Calificaci\u00f3n por estrellas para escuelas<\/a> Desarrollar una aplicaci\u00f3n piloto para la participaci\u00f3n juvenil de YEA con 1800 estudiantes, que permite identificar los lugares donde se sienten seguros e inseguros en su camino a la escuela, y colaborar con los responsables de la toma de decisiones del gobierno local para implementar mejoras de infraestructura en 18 escuelas prioritarias.<\/p>\n

Las fuentes de macrodatos son cada vez m\u00e1s accesibles y ofrecen informaci\u00f3n valiosa sobre una amplia gama de elementos del entorno urbano que pueden representar un riesgo para la seguridad vial. Trabajar con macrodatos para identificar zonas de alto riesgo es una forma eficiente y eficaz de ampliar las evaluaciones a nivel de ciudad, regi\u00f3n o pa\u00eds.<\/p>\n

La metodolog\u00eda emple\u00f3 fuentes de macrodatos, en particular datos telem\u00e1ticos y satelitales, para recopilar informaci\u00f3n sobre carreteras, infraestructura y caracter\u00edsticas sociodemogr\u00e1ficas, e identificar escuelas de riesgo donde la combinaci\u00f3n de los elementos ambientales podr\u00eda representar un riesgo para los estudiantes.<\/p>\n

Los atributos se clasificaron seg\u00fan su riesgo en cuatro niveles, un enfoque que permiti\u00f3 ahorrar costes y esfuerzo de an\u00e1lisis. El primer nivel inclu\u00eda informaci\u00f3n disponible p\u00fablicamente y, a medida que se avanzaba de nivel y se reduc\u00eda el alcance, se pod\u00edan recopilar y analizar datos m\u00e1s complejos, costosos y detallados de forma muy espec\u00edfica.<\/p>\n

\u201cEste enfoque nos permiti\u00f3 definir c\u00f3mo se realiz\u00f3 el an\u00e1lisis y aprovechar los macrodatos disponibles para analizar y comparar 1.063 escuelas. Tambi\u00e9n nos dio la capacidad de centrarnos y evaluar una serie de par\u00e1metros de riesgo a gran escala y a nivel de escuelas individuales en todo Vietnam\u201d, dijo Peter Jamieson, director general de la empresa de an\u00e1lisis de datos., Anditi<\/a>.<\/p>\n

\"Ai&Me\"Levels<\/p>\n

Progresi\u00f3n de niveles y cambios en el alcance del an\u00e1lisis \u2013 Fuente de las im\u00e1genes: Anditi y iRAP<\/em><\/p>\n

Shanna Lucchesi, directora del proyecto AI&Me del International Road Assessment Programme (iRAP<\/a>Seg\u00fan se ha indicado, hasta donde sabemos, esta es la primera vez que se desarrolla y se pone a prueba una metodolog\u00eda de macrodatos para evaluar el riesgo de la infraestructura vial en torno a las escuelas.<\/p>\n

\u201cLas tres ciudades son muy diferentes en tama\u00f1o y complejidad, lo que demuestra la flexibilidad de la metodolog\u00eda para adaptarse a diferentes contextos\u201d, dijo la Sra. Lucchesi.<\/p>\n

\u201c<\/em>Estamos encantados de poner en marcha el programa AI&Me en Vietnam, donde podremos utilizar macrodatos para cambiar nuestra forma de pensar, abordar y resolver la crisis vial\u201d, dijo Trang Truong, gerente del proyecto AI&Me. Fundaci\u00f3n AIP<\/a>.<\/p>\n

\u201cLas agencias gubernamentales locales tambi\u00e9n recopilaron informaci\u00f3n sobre muertes de peatones y el n\u00famero de estudiantes. La metodolog\u00eda se comparti\u00f3 con nuestros socios gubernamentales locales y escuelas en Vietnam. La encuesta posterior a la capacitaci\u00f3n mostr\u00f3 que el 86% de los participantes consider\u00f3 \u00fatil o muy \u00fatil la metodolog\u00eda de an\u00e1lisis de macrodatos presentada en la capacitaci\u00f3n para que las partes interesadas del gobierno identifiquen m\u00e1s f\u00e1cilmente las comunidades y ubicaciones de alto riesgo.\u201d.<\/p>\n

\u201cLa metodolog\u00eda no solo ha revelado informaci\u00f3n valiosa para su aplicaci\u00f3n en Vietnam, sino que est\u00e1 dise\u00f1ada para ser escalable, transferible, asequible y f\u00e1cil de aplicar en cualquier lugar junto con la aplicaci\u00f3n iRAP Star Rating for Schools (SR4S) para refinar una lista de prioridades de sitios para evaluaciones detalladas\u201c, dijo la Sra. Lucchesi.<\/p>\n

\u201cJunto con SR4S, este m\u00e9todo ayudar\u00e1 a quienes toman las decisiones a elegir de forma eficaz y basada en la evidencia d\u00f3nde centrar los esfuerzos en materia de seguridad vial, vincul\u00e1ndolos a las intervenciones de mayor impacto y m\u00e1s rentables para salvar la vida de los ni\u00f1os\u201d, afirm\u00f3.<\/p>\n

Los accidentes de tr\u00e1fico afectan de forma desproporcionada a los j\u00f3venes, siendo la principal causa de muerte entre las personas de 5 a 29 a\u00f1os en todo el mundo.<\/p>\n

La combinaci\u00f3n de condiciones viales inseguras cerca de las escuelas, la especial vulnerabilidad de los ni\u00f1os y la elevada tolerancia al riesgo de los conductores j\u00f3venes, exponen a los j\u00f3venes al riesgo diario de sufrir lesiones e incluso la muerte en accidentes de tr\u00e1fico.<\/p>\n

Se estima que cada d\u00eda mueren 500 ni\u00f1os en las carreteras del mundo y m\u00e1s de 10.000 sufren lesiones que les cambian la vida, lo que tiene enormes implicaciones econ\u00f3micas y sociales para las generaciones futuras.<\/p>\n

A pesar de estos niveles inaceptables de trauma juvenil, la verdadera magnitud del problema a menudo permanece oculta a la conciencia de la comunidad, al tiempo que se percibe como un problema demasiado grande para abordarlo.<\/p>\n

La Sra. Lucchesi afirm\u00f3 que puede resultar abrumador para los gobiernos saber por d\u00f3nde empezar a priorizar la seguridad y para qui\u00e9n, y decidir d\u00f3nde centrar la inversi\u00f3n en modificaciones viales o en la aplicaci\u00f3n de la ley.<\/p>\n

\u201cEl proyecto Ai&Me es apasionante no solo por su innovador enfoque basado en macrodatos, sino tambi\u00e9n por la participaci\u00f3n integral de todas las personas afectadas y capaces de ayudar: desde los estudiantes hasta los administradores escolares, los representantes del gobierno local responsables y facultados para tomar decisiones de inversi\u00f3n, y los expertos mundiales en seguridad vial y datos con los conocimientos m\u00e1s recientes. Todos ellos se unen para proteger a los m\u00e1s vulnerables en las inmediaciones de las escuelas y apoyar la toma de decisiones gubernamentales.<\/p>\n

\u201cNos entusiasma la metodolog\u00eda de macrodatos, los conocimientos que ha revelado y las mejoras espec\u00edficas en seguridad vial que permitir\u00e1 implementar en las tres ciudades. Tambi\u00e9n nos entusiasma su potencial global para hacer que los trayectos escolares sean m\u00e1s seguros de la manera m\u00e1s rentable, mucho m\u00e1s all\u00e1 de las fronteras de Vietnam\u201d, declar\u00f3 la Sra. Lucchesi.<\/p>\n

La metodolog\u00eda se ha desarrollado como parte de la AI&Me: Proyecto para empoderar a los j\u00f3venes y lograr carreteras m\u00e1s seguras<\/a> fundada por Fundaci\u00f3n Botnar<\/a> y Fundaci\u00f3n FIA<\/a>, liderado por la Fundaci\u00f3n AIP y apoyado por iRAP y ANDITI.<\/p>\n

Para obtener m\u00e1s informaci\u00f3n sobre la metodolog\u00eda, descargue el documento. Informe sobre la metodolog\u00eda de Big Data de AI&Me aqu\u00ed<\/a>.<\/p>\n

Tambi\u00e9n se presentar\u00e1 en el Conferencia Internacional Walk21<\/a> Se celebrar\u00e1 la pr\u00f3xima semana, del 19 al 23 de septiembre, en Dubl\u00edn.<\/p>\n

Fuente de la imagen del encabezado: Vuong B\u00f9i en Pixabay<\/em><\/p>\n

 <\/p>","protected":false},"excerpt":{"rendered":"

In three Vietnamese cities homing over 9 million people, how can we begin to identify the highest risk school zones and the children who use them daily to tackle the leading killer of youth \u2013 road traffic crashes. The answer? Big Data. 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