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

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...

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Main Authors: Zulkefli, Imran Fikri, Shahbudin, Fadilah Ezlina
格式: Book Section
語言:English
出版: Faculty of Computer and Mathematical Sciences 2023
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在線閱讀:https://ir.uitm.edu.my/id/eprint/93858/1/93858.pdf
https://ir.uitm.edu.my/id/eprint/93858/
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機構: Universiti Teknologi Mara
語言: English
id my.uitm.ir.93858
record_format eprints
spelling my.uitm.ir.938582024-05-28T01:36:15Z https://ir.uitm.edu.my/id/eprint/93858/ Rider parking guidance using location-based services and crowdsourcing / Imran Fikri Zulkefli and Fadilah Ezlina Shahbudin Zulkefli, Imran Fikri Shahbudin, Fadilah Ezlina Integer programming 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. Faculty of Computer and Mathematical Sciences 2023 Book Section NonPeerReviewed text en https://ir.uitm.edu.my/id/eprint/93858/1/93858.pdf Rider parking guidance using location-based services and crowdsourcing / Imran Fikri Zulkefli and Fadilah Ezlina Shahbudin. (2023) In: International Jasin Multimedia & Computer Science Invention and Innovation Exhibition (i-JaMCSIIX 2023). Faculty of Computer and Mathematical Sciences, Kampus Jasin, p. 16. (Submitted)
institution Universiti Teknologi Mara
building Tun Abdul Razak Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Teknologi Mara
content_source UiTM Institutional Repository
url_provider http://ir.uitm.edu.my/
language English
topic Integer programming
spellingShingle Integer programming
Zulkefli, Imran Fikri
Shahbudin, Fadilah Ezlina
Rider parking guidance using location-based services and crowdsourcing / Imran Fikri Zulkefli and Fadilah Ezlina Shahbudin
description 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.
format Book Section
author Zulkefli, Imran Fikri
Shahbudin, Fadilah Ezlina
author_facet Zulkefli, Imran Fikri
Shahbudin, Fadilah Ezlina
author_sort Zulkefli, Imran Fikri
title Rider parking guidance using location-based services and crowdsourcing / Imran Fikri Zulkefli and Fadilah Ezlina Shahbudin
title_short Rider parking guidance using location-based services and crowdsourcing / Imran Fikri Zulkefli and Fadilah Ezlina Shahbudin
title_full Rider parking guidance using location-based services and crowdsourcing / Imran Fikri Zulkefli and Fadilah Ezlina Shahbudin
title_fullStr Rider parking guidance using location-based services and crowdsourcing / Imran Fikri Zulkefli and Fadilah Ezlina Shahbudin
title_full_unstemmed Rider parking guidance using location-based services and crowdsourcing / Imran Fikri Zulkefli and Fadilah Ezlina Shahbudin
title_sort rider parking guidance using location-based services and crowdsourcing / imran fikri zulkefli and fadilah ezlina shahbudin
publisher Faculty of Computer and Mathematical Sciences
publishDate 2023
url https://ir.uitm.edu.my/id/eprint/93858/1/93858.pdf
https://ir.uitm.edu.my/id/eprint/93858/
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