Implementation of IoT-Based Air Quality Monitoring in Urban Universities: A Case Study in Maiduguri LGA, Borno State
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Background of the Study :
Air quality is a major environmental and public health concern, particularly in urban areas where industrial activities and vehicular emissions contribute to pollution. University campuses in urban settings, such as those in Maiduguri LGA, Borno State, are not immune to these challenges. Poor air quality can adversely affect the health of students and staff, disrupt academic activities, and increase maintenance costs for campus facilities. IoT-based air quality monitoring systems offer a modern solution by continuously tracking key pollutants such as particulate matter (PM2.5, PM10), carbon monoxide, and nitrogen dioxide. These sensors collect real-time data and transmit it to a centralized platform for analysis and visualization (Ibrahim, 2023). The system will employ wireless communication and cloud computing to ensure data is accessible in real time, enabling campus administrators to monitor environmental conditions and take prompt action when pollution levels exceed safe thresholds. Previous studies have demonstrated that continuous air quality monitoring can significantly improve environmental management and public health outcomes (Olu, 2024). This study aims to implement an IoT-based air quality monitoring system on a university campus in Maiduguri LGA, focusing on sensor accuracy, data reliability, and system scalability. The research will involve deploying sensors across campus, developing data analytics algorithms, and evaluating the system’s performance over time. The ultimate goal is to provide a cost-effective, scalable solution that enhances environmental monitoring and supports data-driven decision-making for campus sustainability (Adeniyi, 2025).
Statement of the Problem :
Urban universities in Maiduguri LGA face significant air quality challenges due to high levels of industrial and vehicular emissions. Traditional methods of monitoring air quality are often sporadic and lack real-time data, which limits the ability of campus authorities to respond to pollution spikes effectively. The absence of a continuous monitoring system leads to delayed interventions, exposing students and staff to harmful pollutants and contributing to long-term health risks. Moreover, manual air quality assessments are labor-intensive and may not accurately capture the spatial and temporal variability of pollutants across campus. This gap hinders proactive environmental management and compromises campus sustainability efforts. There is a pressing need for an IoT-based air quality monitoring system that provides real-time, continuous data to facilitate prompt decision-making and effective pollution control. By leveraging advanced sensors and data analytics, such a system can help identify pollution hotspots and trends, enabling targeted interventions. This study seeks to address these issues by designing and implementing an IoT-based system tailored to the unique challenges of urban university environments in Maiduguri LGA. The research will evaluate the system’s performance in terms of data accuracy, response time, and overall impact on campus air quality management (Ibrahim, 2023; Olu, 2024).
Objectives of the Study:
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To implement an IoT-based air quality monitoring system on a university campus.
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To evaluate the system’s accuracy and responsiveness in real time.
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To provide recommendations for improving air quality management on campus.
Research Questions:
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How effective is the IoT system in monitoring air quality in real time?
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What improvements in data accuracy and response times are achieved?
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How does the system contribute to proactive air quality management and campus sustainability?
Significance of the Study :
This study is significant as it develops an IoT-based air quality monitoring system that enhances environmental management on university campuses. By providing continuous, real-time data on air pollutants, the system supports timely interventions and contributes to improved public health and campus sustainability. The findings offer a replicable model for urban universities facing similar air quality challenges (Adeniyi, 2025).
Scope and Limitations of the Study:
The study is limited to the design, implementation, and evaluation of the air quality monitoring system on a single university campus in Maiduguri LGA, Borno State, and does not extend to broader urban areas.
Definitions of Terms:
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Air Quality Monitoring: The continuous measurement of pollutants in the air.
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IoT (Internet of Things): A network of devices that collect and share data in real time.
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Real-Time Data: Immediate data processing and transmission as events occur.
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