1.1 Background of the Study
Waste management is a critical issue in urban areas, with improper disposal leading to environmental pollution, health risks, and urban degradation. Kaduna State faces significant waste management challenges due to rapid urbanization, population growth, and limited resources for waste collection and recycling.
Artificial Intelligence (AI)-based solutions have emerged as a promising approach to improving waste management efficiency. AI-driven tools, including smart bins, route optimization algorithms for waste collection, and recycling automation, can enhance waste segregation, reduce operational costs, and minimize environmental impact (Idris & Yusuf, 2024). This study explores the prospects and challenges of implementing AI-based waste management solutions in Kaduna State, focusing on the role of the Kaduna Environmental Protection Agency (KEPA).
1.2 Statement of the Problem
Inefficient waste management practices in Kaduna State contribute to environmental degradation and public health challenges. Traditional methods are labor-intensive and often fail to address the complexities of urban waste management. AI-based solutions offer innovative approaches, yet their adoption in Kaduna is limited by various factors. This study investigates the prospects and challenges of applying AI in waste management in Kaduna State.
1.3 Objectives of the Study
1.4 Research Questions
1.5 Research Hypothesis
1.6 Significance of the Study
The study underscores the transformative potential of AI in addressing waste management challenges. Its findings are relevant to environmental policymakers, waste management agencies, and technology developers striving for sustainable urban development in Nigeria.
1.7 Scope and Limitations of the Study
The study focuses on the application of AI-based waste management solutions in Kaduna State. It does not cover other Nigerian states or non-AI-based waste management practices. Limitations include data accessibility and the limited implementation of AI technologies in waste management in Nigeria.
1.8 Operational Definition of Terms
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Chapter One: Introduction
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