Real-time carpooling application based on k-NN algorithm: A case study in hashemite university

The current revolution of mobile technology in different aspects of community directs the researchers and scientists to employ this technology to identify practical solutions for daily life problems using mobiles. One of the major challenges in our developing countries is the public transportation system. Public transportation system is an essential requirement for the welfare of modern society and has a critical impact on the people productivities and thus on the entire economic development process. Therefore, different solutions had been investigated to find applicable solutions. Carpooling is one of the initiative solutions that based on the usage of a single shared car by a group of people heading to the same location on a daily basis. In addition, carpooling can be considered as an efficient alternative to overcome the limitations of the conventional transportation system with an easier, quicker and more environmentally friendly car journeys. This paper presents an intelligent carpooling mobile app to commute students of the Hashemite University. The proposed solution is founded on using data mining technique, and more specifically the k-Nearest-Neighbour (k-NN) technique. © Science and Information Organization.