Big Data Analytics in Organic Waste Recycling: Trends, Challenges, and Opportunities

Organic waste, comprising biodegradable material from households, agriculture, institutions, and commercial activities, forms a significant fraction of global municipal solid waste. Inefficient disposal of organic waste leads to severe environmental problems, including methane emissions, soil and water pollution, and adverse public health impacts. With increasing urbanization and industrialization, managing organic waste sustainably has become an urgent global priority. Recent technological innovations—particularly big data analytics transforming organic waste recycling by enabling real-time monitoring, predictive modelling, and optimization of recycling operations. This research paper examines the global, national, and state-level (Andhra Pradesh) perspectives on organic waste recycling, analyzes emerging trends, identifies key challenges, and highlights future opportunities for integrating data-driven approaches in waste management. Using a qualitative literature review, the study finds that while advanced technologies offer substantial efficiency gains, issues such as poor source segregation, inadequate infrastructure, and inconsistent regulations remain major barriers. It concludes with recommendations for policy, technology adoption, and community engagement to enable the effective use of big data analytics in organic waste recycling. Key Words: Organic waste, big data analytics, qualitative literature review, policy,