Analysis of IoT‐Based Smart Urban Air Pollution Reduction Systems in Kano Municipal LGA, Kano State
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Background of the study
Urban air pollution poses significant health and environmental risks in rapidly developing cities. In Kano Municipal LGA, increased industrial activity and vehicular emissions have led to deteriorating air quality, which impacts public health and overall quality of life. IoT‐based smart urban air pollution reduction systems have emerged as a cutting‐edge solution to address this challenge by integrating a network of sensors, data analytics, and automated control measures to monitor and mitigate pollutant levels in real time (Adeola, 2023; Chinaza, 2023). These systems continuously measure air quality indices—such as particulate matter, nitrogen oxides, and volatile organic compounds—and relay the data to centralized platforms where advanced algorithms analyze the information. This real-time monitoring allows for dynamic adjustments in traffic control, industrial emissions, and urban planning to reduce harmful pollutants. Moreover, the deployment of IoT devices across various urban hotspots can provide spatially granular data, helping policymakers identify pollution sources and evaluate the effectiveness of mitigation strategies. With increasing public awareness and governmental initiatives toward sustainability, the integration of IoT technologies into urban air quality management systems is viewed as an essential step towards creating healthier urban environments (Ibrahim, 2024). These systems also facilitate community engagement through mobile applications that provide live updates on air quality, enabling citizens to make informed decisions about outdoor activities. Despite these promising features, challenges such as high deployment costs, sensor calibration issues, and data security remain. Furthermore, harsh climatic conditions may affect sensor performance, thereby necessitating robust design and maintenance protocols. In view of these factors, there is an urgent need for a comprehensive evaluation of IoT‐based smart urban air pollution reduction systems, their operational effectiveness, and their adaptability to local conditions in Kano Municipal LGA. This study seeks to analyze these systems, propose optimization strategies, and recommend policy measures to achieve sustainable urban air quality improvements (Adeola, 2023; Ibrahim, 2024).
Statement of the problem
Kano Municipal LGA has experienced a steady increase in urban air pollution, driven primarily by rapid urbanization, increased vehicular emissions, and industrial activities. Traditional methods for monitoring air quality have proven insufficient due to delayed reporting and a lack of spatial precision. The absence of real-time data prevents timely interventions, thereby exacerbating health risks and environmental degradation. While IoT-based smart urban air pollution reduction systems promise real-time monitoring and dynamic mitigation, their implementation faces significant challenges. High initial investment, sensor degradation due to harsh weather conditions, and issues related to data integration and cybersecurity have hindered widespread adoption. Additionally, there is a notable gap in the integration of data from heterogeneous sensor networks, leading to fragmented monitoring efforts. The current infrastructure in Kano Municipal LGA is not fully equipped to support the continuous data flow required for effective system operation. As a result, decision-makers lack reliable, real-time insights to inform policy and emergency responses, and the benefits of IoT-driven solutions remain largely theoretical. This study aims to address these gaps by evaluating the technical, operational, and economic challenges of implementing IoT-based air pollution reduction systems in the region, and by proposing a framework that enhances data accuracy, system reliability, and overall urban air quality management (Chinaza, 2023; Ibrahim, 2024).
Objectives of the study
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To assess the operational effectiveness of IoT-based air pollution reduction systems.
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To identify technical and infrastructural challenges affecting sensor performance and data integration.
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To propose optimization strategies and policy recommendations for sustainable air quality management.
Research questions
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How effective are IoT-based systems in reducing urban air pollution in real time?
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What technical challenges hinder the reliable operation of these systems in Kano Municipal LGA?
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How can system integration and data security be enhanced to improve overall performance?
Significance of the study
This study is significant as it explores innovative IoT-based solutions to combat urban air pollution in Kano Municipal LGA. The findings will inform policymakers and urban planners on effective strategies for real-time monitoring and mitigation, contributing to improved public health and environmental sustainability. By addressing technical and infrastructural challenges, the research supports the development of robust, data-driven policies for sustainable urban development (Adeola, 2023; Ibrahim, 2024).
Scope and limitations of the study
The study is limited to IoT-based air pollution reduction systems in Kano Municipal LGA. Limitations include high deployment costs, sensor calibration challenges, and potential data security issues.
Definitions of terms
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IoT (Internet of Things): A network of interconnected devices that exchange real-time data.
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Air Pollution Reduction System: A technological system designed to monitor and mitigate urban air pollutants.
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Real-Time Monitoring: Continuous data collection and analysis as events occur.
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