ISSN (Online) : 2456 - 0774

Email : ijasret@gmail.com

ISSN (Online) 2456 - 0774


CITY CLEANLINESS DETECTION USING GEO-TAGGED STREET IMAGES

Abstract

Abstract:- Advancement in mobile, cloud technologies and IoT has 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 state to become state of the art smart-city 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 more efficiently and effectively. In order to address the problem, this paper proposes a multiple-level assessment service system on how the cleanliness status of streets is collected using mobile stations, connected via city network, analysed in the cloud and presented to city administrators online or on mobile. The real applications show the usability and feasibility of our system. This also gives opportunities to city residents to participate and contribute towards making the city a better place.
Keywords- Smart City, Street Cleaning, Litter Detection, Machine Learning, Cloud Computing, Dashboards.

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Paper Submission Open For March 2024
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