Please use this identifier to cite or link to this item: https://repositorio.uti.edu.ec//handle/123456789/3354
Title: Prototype System of Geolocation Educational Public Transport Through Google Maps API
Authors: Salazar, Franklin
Naranjo-Ávalos, Hernán
Buele, Jorge
Pintag, Marco
Buenaño, Edgar
Reinoso, Cristina
Urrutia-Urrutia, Pilar
Varela-Aldas, José
Issue Date: 2020
Publisher: Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Volume 12254 LNCS, Pages 367 - 382. 20th International Conference on Computational Science and Its Applications, ICCSA 2020. Cagliari. 1 July 2020 through 4 July 2020
Abstract: Urban traffic complications in most underdeveloped countries and congestion in all metropolitan areas has become a daily problem with a difficult solution. Disorganized mobility of drivers and pedestrians along with the increase in travel time, non-compliance with schedules, air pollution and intolerable sound levels, have harmful effects on human health. Therefore, this research describes a geolocation system of urban transport through a mobile application developed on the Xamarin platform. Drivers send the latitude and longitude points when starting a route, this data will be sent to the SQL SERVER online database server, using the SmarterASP.NET platform. By developing the geolocation system in ASP.NET, the coordinates are available to users in an interval of 5 s. The developed interface shows a location map, where the route in real time is presented. It also shows the administration of users, drivers, buses, assignment of routes, assignment of buses and registration of static routes. Being a prototype system, the university transport system has been taken as an object of study to corroborate its correct operation with the respective experimental tests. Satisfaction surveys have also been carried out on a group of 300 people, among students and university teachers and their validation is carried out through the Technological Acceptance Model (TAM). To interpret the results, Kendall Tau-b correlation analysis was used, obtaining positive correlation values with a high significance value. © 2020, Springer Nature Switzerland AG.
URI: https://link.springer.com/chapter/10.1007/978-3-030-58817-5_28
http://repositorio.uti.edu.ec//handle/123456789/3354
Appears in Collections:Artículos Científicos Indexados

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