Sustainable Waste Management System Using Artificial Intelligence and Satellite Communication: A Case Study
Tasnim Binte Shiraj, Sadia Tasnim Nishat, F. Chowdhury, Umma Habiba Easha, Afrida Israt Jahan, Jayed Arif, Md Hossam-E-Haider · 2024
The Deep learning (DL) models of Artificial intelligence is becoming a necessary component of modern solid waste management (SWM) system design and planning against a rapidly advancing backdrop. To highlight the problems and obstacles associated with utilizing integrated technologies and satellite-based systems, this study provides a critical analysis of the existing SWM methods across South Asia. DL models and image Datasets can enhance the performance of the previous prototypes. There are three categories in which dataset description and preprocessing are categorized: Datasets in waste management, dataset preprocessing in waste management, and solid waste monitoring and management using RFID, GIS and GSM. The technologies discussed in the methodology section constitute the foundation for the satellite technology and AI-based SWM systems reviewed in this article. To make it easier to plan and create a sustainable new system, this review may help the reader understand the fundamentals of the pre-trained DL models also known as transfer learning that are now in the trend. Also image processing models DL and transfer learning models through satellite communication, and their application in SWM.