{"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\/fr\/show-me-the-way-big-data-reveals-highest-risk-schools-in-vietnam\/","title":{"rendered":"Montrez-moi le chemin\u00a0: le Big Data r\u00e9v\u00e8le les \u00e9coles les plus \u00e0 risque au Vietnam"},"content":{"rendered":"

Dans trois villes vietnamiennes abritant plus de 9 millions d'habitants, comment identifier les zones scolaires les plus \u00e0 risque et les enfants qui les fr\u00e9quentent quotidiennement afin de lutter contre la principale cause de mortalit\u00e9 chez les jeunes\u00a0: les accidents de la route\u00a0? La r\u00e9ponse\u00a0? Le Big Data.<\/p>\n

Une m\u00e9thodologie d'analyse des m\u00e9gadonn\u00e9es, d\u00e9velopp\u00e9e dans le cadre du projet AI&Me, a permis d'effectuer une analyse \u00e0 distance des donn\u00e9es relatives \u00e0 H\u00f4 Chi Minh-Ville, Pleiku et Yen Bai. Cette analyse a permis d'identifier les 106 \u00e9coles pr\u00e9sentant les risques les plus \u00e9lev\u00e9s et n\u00e9cessitant une enqu\u00eate approfondie en mati\u00e8re de s\u00e9curit\u00e9 routi\u00e8re, et de prioriser les investissements parmi les 1\u00a0063 \u00e9coles analys\u00e9es.<\/p>\n

S\u2019appuyant sur ces r\u00e9sultats, le projet attribuera un syst\u00e8me d\u2019\u00e9toiles \u00e0 la s\u00e9curit\u00e9 des \u00e9coles. Star Rating for Schools<\/a> application, tester une nouvelle application d'engagement des jeunes YEA aupr\u00e8s de 1 800 \u00e9l\u00e8ves cartographiant les endroits o\u00f9 ils se sentent en s\u00e9curit\u00e9 et en danger sur leur trajet vers l'\u00e9cole, et travailler avec les d\u00e9cideurs des gouvernements locaux pour mettre en \u0153uvre des am\u00e9liorations d'infrastructure dans 18 \u00e9coles prioritaires.<\/p>\n

Les sources de donn\u00e9es massives sont de plus en plus accessibles et permettent d'obtenir des informations sur un large \u00e9ventail d'\u00e9l\u00e9ments de l'environnement urbain susceptibles de repr\u00e9senter un risque pour la s\u00e9curit\u00e9 routi\u00e8re. L'utilisation de ces donn\u00e9es pour identifier les zones \u00e0 haut risque constitue un moyen efficace d'\u00e9tendre les \u00e9valuations \u00e0 l'\u00e9chelle d'une ville, d'une r\u00e9gion ou d'un pays.<\/p>\n

La m\u00e9thodologie a utilis\u00e9 des sources de donn\u00e9es massives, notamment des donn\u00e9es t\u00e9l\u00e9matiques et satellitaires, pour collecter des attributs routiers, infrastructurels et sociod\u00e9mographiques et identifier les \u00e9coles \u00e0 risque o\u00f9 la combinaison des \u00e9l\u00e9ments environnementaux pourrait repr\u00e9senter un risque pour les \u00e9l\u00e8ves.<\/p>\n

Les attributs ont \u00e9t\u00e9 class\u00e9s selon leur niveau de risque en quatre cat\u00e9gories, une approche qui a permis de r\u00e9duire les co\u00fbts et les efforts d'analyse. Le premier niveau comprenait les informations librement accessibles et, \u00e0 mesure que les niveaux progressaient et que le p\u00e9rim\u00e8tre d'\u00e9tude se r\u00e9duisait, des donn\u00e9es plus complexes, plus co\u00fbteuses et plus d\u00e9taill\u00e9es pouvaient \u00eatre collect\u00e9es et analys\u00e9es de mani\u00e8re tr\u00e8s cibl\u00e9e.<\/p>\n

\u201c Cette approche nous a permis de d\u00e9finir la m\u00e9thodologie d'analyse et d'exploiter les donn\u00e9es massives disponibles pour analyser et comparer 1\u00a0063 \u00e9coles. Elle nous a \u00e9galement permis de cibler et d'\u00e9valuer un ensemble de param\u00e8tres de risque \u00e0 grande \u00e9chelle et au niveau de chaque \u00e9cole au Vietnam \u201d, a d\u00e9clar\u00e9 Peter Jamieson, directeur g\u00e9n\u00e9ral de la soci\u00e9t\u00e9 d'analyse de donn\u00e9es., Anditi<\/a>.<\/p>\n

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

\u00c9volution des niveaux et modifications du p\u00e9rim\u00e8tre d'analyse \u2013 Source des images\u00a0: Anditi et iRAP<\/em><\/p>\n

Shanna Lucchesi, chef de projet AI&Me du International Road Assessment Programme (iRAP<\/a>) a d\u00e9clar\u00e9 que, \u00e0 notre connaissance, c'est la premi\u00e8re fois qu'une m\u00e9thodologie de m\u00e9gadonn\u00e9es a \u00e9t\u00e9 d\u00e9velopp\u00e9e et mise \u00e0 l'essai pour \u00e9valuer les risques li\u00e9s aux infrastructures routi\u00e8res aux abords des \u00e9coles.<\/p>\n

\u201c Les trois villes sont tr\u00e8s diff\u00e9rentes en taille et en complexit\u00e9, ce qui prouve la flexibilit\u00e9 de la m\u00e9thodologie pour s'adapter \u00e0 diff\u00e9rents contextes \u201d, a d\u00e9clar\u00e9 Mme Lucchesi.<\/p>\n

\u201c<\/em>\u201d Nous sommes ravis de lancer le programme pilote AI&Me au Vietnam, o\u00f9 nous pourrons utiliser le big data pour transformer notre fa\u00e7on de penser, d'aborder et de r\u00e9soudre la crise routi\u00e8re \u00bb, a d\u00e9clar\u00e9 Trang Truong, chef de projet AI&Me. Fondation AIP<\/a>.<\/p>\n

\u201cLes autorit\u00e9s locales ont \u00e9galement recueilli des informations sur les d\u00e9c\u00e8s de pi\u00e9tons et le nombre d'\u00e9l\u00e8ves. La m\u00e9thodologie a \u00e9t\u00e9 partag\u00e9e avec nos partenaires des collectivit\u00e9s locales et des \u00e9tablissements scolaires au Vietnam. L'enqu\u00eate men\u00e9e apr\u00e8s la formation a r\u00e9v\u00e9l\u00e9 que 861\u00a0000 participants ont jug\u00e9 la m\u00e9thodologie d'analyse des donn\u00e9es massives pr\u00e9sent\u00e9e utile, voire tr\u00e8s utile, pour permettre aux acteurs gouvernementaux d'identifier plus facilement les communaut\u00e9s et les zones \u00e0 haut risque.<\/p>\n

\u201c Non seulement la m\u00e9thodologie a r\u00e9v\u00e9l\u00e9 des perspectives int\u00e9ressantes pour une application au Vietnam, mais elle est con\u00e7ue pour \u00eatre \u00e9volutive, transf\u00e9rable, abordable et facile \u00e0 appliquer partout en conjonction avec l'application iRAP Star Rating for Schools (SR4S) pour affiner une liste prioritaire de sites pour des \u00e9valuations d\u00e9taill\u00e9es \u201c, a d\u00e9clar\u00e9 Mme Lucchesi.<\/p>\n

\u201c Associ\u00e9e \u00e0 SR4S, cette m\u00e9thode aidera les d\u00e9cideurs \u00e0 faire des choix efficaces et fond\u00e9s sur des donn\u00e9es probantes quant aux domaines o\u00f9 concentrer les efforts en mati\u00e8re de s\u00e9curit\u00e9 routi\u00e8re, en lien avec les interventions les plus efficaces et les plus rentables pour sauver des vies d'enfants \u201d, a-t-elle d\u00e9clar\u00e9.<\/p>\n

Les accidents de la route touchent de mani\u00e8re disproportionn\u00e9e les jeunes, \u00e9tant la principale cause de mortalit\u00e9 chez les personnes \u00e2g\u00e9es de 5 \u00e0 29 ans dans le monde.<\/p>\n

La combinaison de conditions routi\u00e8res dangereuses \u00e0 proximit\u00e9 des \u00e9coles, de la vuln\u00e9rabilit\u00e9 particuli\u00e8re des enfants et de la tol\u00e9rance au risque \u00e9lev\u00e9e des jeunes conducteurs expose ces derniers au risque quotidien de blessures et de d\u00e9c\u00e8s sur les routes.<\/p>\n

On estime que 500 enfants meurent chaque jour sur les routes du monde et que plus de 10 000 subissent des blessures qui bouleversent leur vie, ce qui aura d'\u00e9normes cons\u00e9quences \u00e9conomiques et sociales pour les g\u00e9n\u00e9rations futures.<\/p>\n

Malgr\u00e9 ces niveaux inacceptables de traumatismes chez les jeunes, l'ampleur r\u00e9elle du probl\u00e8me est souvent cach\u00e9e \u00e0 la conscience collective, tout en paraissant trop importante pour \u00eatre prise en charge.<\/p>\n

Mme Lucchesi a d\u00e9clar\u00e9 qu'il peut \u00eatre difficile pour les gouvernements de savoir par o\u00f9 commencer en mati\u00e8re de priorit\u00e9 \u00e0 la s\u00e9curit\u00e9 et pour qui, et de d\u00e9cider o\u00f9 concentrer leurs investissements dans les modifications routi\u00e8res ou l'application de la loi.<\/p>\n

\u201cLe projet Ai&Me est passionnant non seulement par son approche novatrice du big data, mais aussi par l'implication de toutes les personnes concern\u00e9es et capables d'apporter leur contribution\u00a0: \u00e9l\u00e8ves, directeurs d'\u00e9tablissement, \u00e9lus locaux habilit\u00e9s \u00e0 prendre des d\u00e9cisions d'investissement, et experts internationaux en s\u00e9curit\u00e9 routi\u00e8re et en donn\u00e9es, forts de leur savoir-faire de pointe. Tous unissent leurs efforts pour prot\u00e9ger les plus vuln\u00e9rables aux abords des \u00e9coles et appuyer les d\u00e9cisions gouvernementales.<\/p>\n

\u201c Nous sommes enthousiasm\u00e9s par la m\u00e9thodologie du Big Data, les enseignements qu'elle a permis de tirer et les am\u00e9liorations tr\u00e8s cibl\u00e9es qu'elle rendra possibles en mati\u00e8re de s\u00e9curit\u00e9 routi\u00e8re dans les trois villes. Nous sommes \u00e9galement enthousiasm\u00e9s par son potentiel \u00e0 l'\u00e9chelle mondiale pour s\u00e9curiser les trajets scolaires de la mani\u00e8re la plus rentable, bien au-del\u00e0 des fronti\u00e8res du Vietnam \u201d, a d\u00e9clar\u00e9 Mme Lucchesi.<\/p>\n

La m\u00e9thodologie a \u00e9t\u00e9 d\u00e9velopp\u00e9e dans le cadre de IA et moi : Projet d'autonomisation des jeunes pour des routes plus s\u00fbres<\/a> fond\u00e9e par Fondation Botnar<\/a> et FIA Foundation<\/a>, dirig\u00e9 par la Fondation AIP et soutenu par iRAP et ANDITI.<\/p>\n

Pour plus d'informations sur la m\u00e9thodologie, t\u00e9l\u00e9chargez le Rapport m\u00e9thodologique sur le Big Data d'AI&Me disponible ici<\/a>.<\/p>\n

Il sera \u00e9galement pr\u00e9sent\u00e9 \u00e0 Conf\u00e9rence internationale Walk21<\/a> qui se tiendra la semaine prochaine, du 19 au 23 septembre, \u00e0 Dublin.<\/p>\n

Source de l\u2019image d\u2019en-t\u00eate : Vuong B\u00f9i sur Pixabay<\/em><\/p>\n

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

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