Background of the study:
Effective waste management is critical for maintaining urban hygiene and environmental sustainability, particularly in densely populated areas like Sokoto North LGA, Sokoto State. Traditional garbage collection systems often rely on fixed schedules and manual monitoring, which can lead to inefficient collection routes, delayed pickups, and unsanitary conditions. The investigation into an IoT‐based smart garbage collection system offers a novel solution to these challenges by leveraging sensor networks, real‐time data analytics, and wireless communication to optimize waste collection processes (Ibrahim, 2023). These systems deploy sensors in waste bins to monitor fill levels and transmit data to a centralized management platform. This data is then analyzed to determine the optimal collection routes and schedules, reducing fuel consumption and operational costs while ensuring that bins are emptied before they overflow (Adeniyi, 2024). Furthermore, real‐time monitoring enables prompt detection of issues such as illegal dumping or bin vandalism, allowing for immediate corrective actions. The system’s scalability and integration with mobile applications also promote community engagement by providing residents with real‐time information about garbage collection schedules. Overall, the adoption of IoT‐based garbage collection systems contributes to improved urban sanitation, reduced environmental pollution, and enhanced public health, aligning with global trends towards smart city initiatives (Udo, 2025).
Statement of the problem:
Urban areas in Sokoto North LGA suffer from inadequate waste management due to traditional garbage collection methods that are inflexible and inefficient. The reliance on fixed collection schedules and manual bin monitoring often results in overflowing waste containers, leading to unsanitary conditions and increased health risks for residents (Ibrahim, 2023). The absence of real‐time data and automated route optimization exacerbates these issues, as collection trucks may follow inefficient routes, causing delays and increased fuel consumption. Financial and logistical constraints further hinder the implementation of effective waste management strategies, leaving communities with fragmented and unreliable garbage collection services (Adeniyi, 2024). This inefficiency not only degrades urban aesthetics but also contributes to environmental pollution and public health hazards. Without the integration of an IoT‐based system that provides continuous monitoring and adaptive scheduling, the current waste management practices remain inadequate, undermining efforts to achieve a clean and sustainable urban environment. Therefore, there is an urgent need to develop a smart garbage collection system that leverages real‐time data to improve operational efficiency, reduce waste overflow, and enhance community well‐being (Udo, 2025).
Objectives of the study:
To design an IoT‐based system for real‐time monitoring of waste bin fill levels.
To evaluate the impact of the system on optimizing garbage collection routes and schedules.
To propose strategies for integrating the system with existing urban waste management frameworks.
Research questions:
How effective is the IoT‐based system in providing real‐time data on waste bin fill levels?
What improvements in collection efficiency and route optimization can be observed after system implementation?
How can the system be integrated with current waste management practices to enhance urban sanitation?
Significance of the study:
This study is significant as it presents an innovative, data‐driven approach to urban waste management. By enabling real‐time monitoring and adaptive scheduling, the IoT‐based system can reduce waste overflow, optimize collection routes, and improve public sanitation, contributing to a cleaner and healthier urban environment in Sokoto North LGA.
Scope and limitations of the study:
This study is limited to the investigation and evaluation of an IoT‐based smart garbage collection system in Sokoto North LGA, Sokoto State. It does not extend to other urban waste management systems or rural areas.
Definitions of terms:
IoT (Internet of Things): A network of interconnected devices that exchange real‐time data.
Smart Garbage Collection: A technology‐driven system that automates waste monitoring and collection scheduling.
Waste Management: The process of collecting, processing, and disposing of waste materials.
Background of the Study
Mobile money has revolutionized business transactions, especially in developing economies, where ac...
Background of the Study
Biometric authentication has gained traction as a secure and efficient method for verifying user identities in fi...
ABSTRACT:- Harmful background radiation in our environment has been identified as one of the primary causes of va...
Background of the Study:
Vocational education is increasingly recognized as a catalyst for technological advancement, parti...
Abstract: This study investigates the efficacy of storytelling as a pedagogical tool in early childhood educ...
Background of the Study
Early intervention programs are designed to identify and address developmental delays in children as soon as possibl...
Abstract: This study examines the influence of organizational culture on project management practices, aimin...
Chapter One: Introduction
BACKGROUND OF THE STUDY
According to Hornby (1984), the word "secretary" is derived from the...
Background of the Study
In the digital banking era, online security is a major determinant of customer confidence. Citibank Nigeria has a...