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...
Saved in:
Main Authors: | , |
---|---|
格式: | Book Section |
語言: | English |
出版: |
Faculty of Computer and Mathematical Sciences
2023
|
主題: | |
在線閱讀: | https://ir.uitm.edu.my/id/eprint/93858/1/93858.pdf https://ir.uitm.edu.my/id/eprint/93858/ |
標簽: |
添加標簽
沒有標簽, 成為第一個標記此記錄!
|
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/ |
_version_ |
1800726581946089472 |