| Title |
SmartClean: Smart City Street Cleanliness System Using Multi-Level Assessment Model |
| ID_Doc |
40852 |
| Authors |
Li, WR; Bhushan, B; Gao, J; Zhang, PC |
| Title |
SmartClean: Smart City Street Cleanliness System Using Multi-Level Assessment Model |
| Year |
2018 |
| Published |
International Journal Of Software Engineering And Knowledge Engineering, 28, 11-12 |
| DOI |
10.1142/S0218194018400272 |
| Abstract |
Advancements in mobile, cloud computing and other techniques have made the world even smaller and connected like never before. It has become a challenge and an opportunity for cities to leverage these growing technologies to solve real city administration problems. Cities are in the transformation to become state-of-the-art smart cities using these technologies. This paper is about the automation of street cleanliness assessment in near real-time. It answers the question of how can we assess the status of streets in a more efficient and effective way. To address the problem, this paper proposes a multi-level assessment system on how the cleanliness status of streets is collected using mobile stations. They are connected via city network, analyzed in the cloud and presented to city administrators online or on mobile. The real case studies show the usability and feasibility of our system. This also gives opportunities for city residents to participate and contribute to making the city a better place. |
| Author Keywords |
Street cleaning; litter detection; machine learning; cloud computing |
| Index Keywords |
Index Keywords |
| Document Type |
Other |
| Open Access |
Open Access |
| Source |
Science Citation Index Expanded (SCI-EXPANDED); Conference Proceedings Citation Index - Science (CPCI-S) |
| EID |
WOS:000455945400013 |
| WoS Category |
Computer Science, Artificial Intelligence; Computer Science, Software Engineering; Engineering, Electrical & Electronic |
| Research Area |
Computer Science; Engineering |
| PDF |
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