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Predictive Analytics and Big Data in Forecasting Recycling Trends
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Author(s): Aparna Unni (Chandigarh University, India)and Harpreet Kaur Channi (Chandigarh University, India)
Copyright: 2025
Pages: 34
Source title:
AI Technologies for Enhancing Recycling Processes
Source Author(s)/Editor(s): Debasis Mitra (Graphic Era University (Deemed), India), Tanupriya Choudhury (University of Petroleum and Energy Studies, Dehradun, India), Ayush Madan (Universiti Malaysia Terengganu, Malaysia), Sourav Chattaraj (Siksha ‘O’ Anusandhan University (Deemed), India)and Marika Pellegrini (University of L'Aquila, Italy)
DOI: 10.4018/979-8-3693-7282-1.ch010
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Abstract
Predictive analytics and big data enhance recycling by analyzing social media, sensors, and municipal data. Advanced algorithms manage resource allocation and operations, forecasting trends from population growth and economic factors. Machine learning identifies patterns and predicts future recycling rates. In India (2010-2024), Python's Pandas and Scikit-learn used linear regression to forecast recycling trends, showing annual increases. Residuals analysis confirms model accuracy, suggesting that recycling strategies are effective and room for improvement exists.
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