| Title |
Mobile IoT-RoadBot: An AI-powered Mobile IoT Solution for Real-Time Roadside Asset Management |
| ID_Doc |
43603 |
| Authors |
Forkan, ARM; Kang, YB; Marti, F; Joachim, S; Banerjee, A; Milovac, JK; Jayaraman, PP; McCarthy, C; Ghaderi, H; Georgakopoulos, D |
| Title |
Mobile IoT-RoadBot: An AI-powered Mobile IoT Solution for Real-Time Roadside Asset Management |
| Year |
2022 |
| Published |
|
| DOI |
10.1145/3495243.3558271 |
| Abstract |
Timely detection of roadside assets that require maintenance is essential for improving citizen satisfaction. Currently, the process of identifying such maintenance issues is typically performed manually, which is time consuming, expensive, and slow to respond. In this paper, we present Mobile Io-TRoadBot, a mobile 5G-based Internet of Things (IoT) solution, powered by Artificial Intelligence (AI) techniques to enable opportunistic real-time identification and detection of maintenance issues with roadside assets. The Mobile IoT-RoadBot solution has been deployed on 11 bin service (waste collection) trucks in the western suburbs of Melbourne, Australia, performing real-time assessments of road-side assets as they service areas within the local government. We present the architecture of Mobile IoT-RoadBot and demonstrate its capability via an online 'points of maintenance' (PoMs) map. |
| Author Keywords |
Mobile 5G; IoT; Roadside Asset Management; Smart City |
| Index Keywords |
Index Keywords |
| Document Type |
Other |
| Open Access |
Open Access |
| Source |
Conference Proceedings Citation Index - Science (CPCI-S) |
| EID |
WOS:001085836000101 |
| WoS Category |
Computer Science, Theory & Methods; Telecommunications |
| Research Area |
Computer Science; Telecommunications |
| PDF |
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