Uberwasted App for Reporting and Collecting Waste Using Location Based and Deep Learning Technologies

Nguyen, B. ORCID: https://orcid.org/0000-0002-2260-8186, Tan, D.H., Dieu, H.V.T., Khac, D.N., & Dinh, H.T. (2020). Uberwasted App for Reporting and Collecting Waste Using Location Based and Deep Learning Technologies. In: Future Data and Security Engineering. Big Data, Security and Privacy, Smart City and Industry 4.0 Applications. Eds. Dang, T.K., Kung, J., Takizawa, M., & Chung, T.M., pp. 178-188 Springer. 10.1007/978-981-33-4370-2_13.

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Abstract

Nowadays, waste becomes one of the main air pollution sources. In this context, Uberwasted app is studied and developed as a mobile app that allows volunteers to report and to take part in waste collection based on location based technology and deep learning algorithms. First, a waste data management system has been built to store waste photo and descriptions, which are submitted by using the app. Furthermore, waste are classified by applying convolutional neural network model called “Resnet34”, then reported to network of volunteers the place to be collected based on location based technology. To proof of our conceptual approach, several typical implementation results will be illustrated.

Item Type:	Book Section
Uncontrolled Keywords:	CNN; Data collection; Mobile app; Resnet34; Volunteer; Waste
Research Programs:	Air Quality & Greenhouse Gases (AIR)
Depositing User:	Luke Kirwan
Date Deposited:	21 Dec 2020 09:08
Last Modified:	27 Aug 2021 17:34
URI:	https://pure.iiasa.ac.at/16946

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