Rider parking guidance using location-based services and crowdsourcing / Imran Fikri Zulkefli and Fadilah Ezlina Shahbudin

• Main Authors: Zulkefli, Imran Fikri, Shahbudin, Fadilah Ezlina
• 格式: Book Section
• 語言: English
• 出版: Faculty of Computer and Mathematical Sciences 2023
• 主題: Integer programming
• 在線閱讀: https://ir.uitm.edu.my/id/eprint/93858/1/93858.pdf; https://ir.uitm.edu.my/id/eprint/93858/
• 機構: Universiti Teknologi Mara

Food delivery services have become increasingly popular in Malaysia as more and more people choose the convenience of having their meals delivered directly to their homes or workplaces. However, one of the challenges faced by delivery riders is finding parking spots at shopping malls due to limited parking availability and complex mall layouts. To address this issue a mobile application has been developed specifically for food delivery riders. This application utilizes geofencing, geolocation technology and crowdsourcing to enhance its functionality. As riders approach a mall, they receive notifications about parking spots in that area. With the help of GPS data and other relevant information the application accurately tracks the real time location of the rider's device. This application shows directions to their destination which ensures efficient tracking of delivery routes and records their progress effectively. The development model used for this project follows four phases of Waterfall Model which are requirements analysis, design, implementation and testing. By incorporating geofencing and geolocation technology into the food delivery application it improves efficiency, reliability and overall enhances the experience, for riders.