| Title |
CitySolution: A complaining task distributive mobile application for smart city corporation using deep learning |
| ID_Doc |
38761 |
| Authors |
Shama, F; Aziz, A; Deya, LBM |
| Title |
CitySolution: A complaining task distributive mobile application for smart city corporation using deep learning |
| Year |
2024 |
| Published |
|
| DOI |
10.1016/j.softx.2024.101829 |
| Abstract |
The lack of an automated online platform for reporting citizens' complaints, coupled with the city corporations' struggles in managing them, presents significant challenges. Furthermore, the availability of resources is very limited to higher authorities for monitoring progress. The primary objective of this paper is to develop two Android applications and to categorize complaints automatically using a deep learning model created on the Teachable Machine. With the citizen-oriented application, individuals can easily report complaints by capturing pictures of their municipal issues. The authority version of the application provides categorized complaints, along with location and status details. Higher authorities can monitor the municipal progress, thereby enhancing transparency, and efficiency and promoting smart city development on a nationwide scale. |
| Author Keywords |
Mobile application; Image classification; Deep learning; Teachable machine |
| Index Keywords |
Index Keywords |
| Document Type |
Other |
| Open Access |
Open Access |
| Source |
Science Citation Index Expanded (SCI-EXPANDED) |
| EID |
WOS:001285605100001 |
| WoS Category |
Computer Science, Software Engineering |
| Research Area |
Computer Science |
| PDF |
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