Optimization of IoT‐Based Smart Automated Waste Segregation Systems in Wudil LGA, Kano State
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Background of the study:
Effective waste management is crucial for environmental sustainability and public health, yet traditional waste segregation methods in many urban settings remain inefficient and labor-intensive. In Wudil LGA, Kano State, waste segregation at source is often compromised by manual sorting practices that lead to contamination of recyclable materials and inefficient resource recovery. The optimization of an IoT‐based smart automated waste segregation system can revolutionize waste management by integrating sensors, machine vision, and real-time data analytics to accurately identify and separate different types of waste (Ibrahim, 2023). Such systems employ cameras and spectral sensors to classify materials—such as plastics, metals, and organic matter—automatically directing them into appropriate bins. The continuous data collection facilitates real-time adjustments to the sorting process and helps in monitoring segregation efficiency. Additionally, the system can generate reports on waste composition and performance metrics, enabling waste management authorities to optimize collection routes and recycling processes (Adeniyi, 2024). This technological innovation not only improves recycling rates and reduces landfill use but also contributes to energy savings and decreased operational costs. The IoT-based system supports sustainable waste management practices by minimizing human error and ensuring consistent, high-quality segregation, which is vital for environmental conservation and resource efficiency (Udo, 2025). The implementation of such a system in Wudil LGA can serve as a model for other urban areas, fostering a cleaner and more sustainable environment.
Statement of the problem:
Waste management in Wudil LGA is hindered by traditional, manual segregation processes that result in high contamination rates and inefficient recycling. The reliance on human labor for sorting waste leads to inconsistent segregation, where recyclable materials are often mixed with non-recyclables, reducing their value and increasing disposal costs (Ibrahim, 2023). Inadequate waste segregation contributes to environmental degradation and increased landfill burdens, while the absence of real-time monitoring prevents timely interventions to correct sorting errors. Financial limitations and the lack of advanced sorting technology further exacerbate the issue, making it difficult to achieve efficient waste management. The manual approach is also time-consuming and prone to errors, which can lead to operational delays and increased costs. Without an automated system that leverages IoT technology to accurately segregate waste in real time, the local government and waste management agencies are unable to optimize recycling processes and reduce environmental impact (Adeniyi, 2024). Addressing these challenges is critical to improving resource recovery rates, reducing landfill usage, and promoting sustainable urban waste management practices in Wudil LGA (Udo, 2025).
Objectives of the study:
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To design an IoT-based automated waste segregation system for real-time classification of waste.
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To evaluate the system’s effectiveness in improving segregation accuracy and recycling rates.
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To propose integration strategies for incorporating the system into existing waste management frameworks.
Research questions:
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How effective is the IoT-based system in classifying and segregating waste in real time?
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What improvements in recycling efficiency and reduction in contamination are observed after implementation?
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How can the system be integrated with current waste management practices to optimize resource recovery?
Significance of the study:
This study is significant as it introduces an automated, IoT-based solution to enhance waste segregation in urban areas. Improved segregation leads to higher recycling rates, reduced landfill use, and better resource management. The findings will support policymakers in adopting sustainable waste management practices and promote environmental conservation in Wudil LGA.
Scope and limitations of the study:
This study is limited to the development and evaluation of an IoT-based smart automated waste segregation system in Wudil LGA, Kano State. It does not extend to other waste management solutions or different regions.
Definitions of terms:
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IoT (Internet of Things): A network of devices that communicate real-time data.
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Waste Segregation: The process of sorting waste into different categories for recycling or disposal.
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Automated System: A technology-driven system that performs tasks with minimal human intervention.
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