dc.contributor.author	Noor Braik
dc.contributor.author	Khalid Jabr
dc.date.accessioned	2024-03-04T08:33:18Z
dc.date.available	2024-03-04T08:33:18Z
dc.date.issued	2023
dc.description.abstract	The world is currently facing a growing waste management crisis as more rubbish is throwed every day. This not only contributes to environmental contamination but also poses a threat to both human health and the welfare of wildlife. If we want to successfully address this issue, we must develop novel, creative methods for managing rubbish. The necessity to find a solution to the issue of improper and ineffective waste management techniques served as the inspiration for the ”Greeny” project. By sorting waste into classes including plastic, glass and other classes using machine learning, the initiative aims to increase the effectiveness and accuracy of trash management. As well as offering the authenticated users a point system, which basically will add points based on the waste type a user has dropped. User will be authenticated by 2 methods, either by scanning the QR code, or by entering his unique ID. Additionally, Greeny will keep users informed about the status of the bins, including the capacity for each bin, which will be stored into database, Therefore, it will alert authorities to empty it immediately if it fills up. By allowing for the correct recycling of various waste kinds, this not only benefits the environment by lowering the quantity of garbage that ends up in landfills but also encourages sustainability. In essence, With Greeny, people are encouraged to embrace sustainable behaviors, contribute to a cleaner environment, and adopt good trash disposal habits. In the end, this creative waste management approach may help create a community that is greener and more environmentally conscious. 1
dc.identifier.uri	https://hdl.handle.net/20.500.11888/18676
dc.supervisor	Dr. Manar Qamhieh
dc.title	Greeny

Greeny

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