Investigation into IoT-Based Smart Greenhouse Control Systems in Makurdi LGA, Benue State
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- NGN 5000
Background of the study:
Greenhouse farming offers controlled environments for crop production, yet maintaining optimal conditions within these structures is challenging, particularly in regions like Makurdi LGA where climatic variability can affect yields. Traditional greenhouse management relies on manual adjustments for temperature, humidity, and light, leading to inefficiencies and inconsistent crop performance. IoT-based smart greenhouse control systems integrate sensor networks, automated actuators, and cloud computing to continuously monitor and adjust environmental parameters in real time (Aminu, 2023). These systems measure critical factors such as temperature, humidity, CO₂ levels, and soil moisture, then automatically control ventilation, irrigation, and shading to ensure ideal growing conditions (Ibrahim, 2024). By enabling proactive management and predictive maintenance, IoT systems can minimize resource wastage, enhance crop yields, and reduce labor costs. The integration of smart controls not only supports precision agriculture but also enables remote monitoring and management, providing farmers with timely alerts and data-driven insights (Udo, 2025). This technological innovation is crucial for ensuring sustainable agricultural practices in Makurdi LGA, where farmers face increasing pressure to maximize productivity and manage resources efficiently. The system’s real-time responsiveness ensures that crops are consistently grown in optimal conditions, thereby improving overall farm profitability.
Statement of the problem:
Farmers in Makurdi LGA face significant challenges in managing greenhouse environments due to the limitations of manual control systems. The inability to continuously monitor and adjust critical parameters leads to fluctuating conditions that can compromise crop health and yield (Aminu, 2023). Manual adjustments are often delayed and imprecise, resulting in over-irrigation, excessive heating, or inadequate ventilation. This lack of automation not only increases operational costs but also reduces the consistency and quality of produce. Financial constraints and limited technical expertise further inhibit the adoption of modern control systems. Consequently, greenhouse operations suffer from inefficiencies and suboptimal resource utilization, leading to economic losses for farmers (Ibrahim, 2024). Without a robust IoT-based system that provides real-time monitoring and automated adjustments, farmers will continue to struggle with environmental management, hindering efforts to achieve sustainable and profitable agriculture (Udo, 2025).
Objectives of the study:
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To design an IoT-based smart greenhouse control system for continuous environmental monitoring and adjustment.
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To evaluate the system’s effectiveness in improving crop yield and reducing resource wastage.
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To propose strategies for integrating the system into existing greenhouse farming practices.
Research questions:
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How effective is the IoT-based system in maintaining optimal greenhouse conditions?
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What improvements in crop yield and resource efficiency are observed with system implementation?
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How can the system be integrated with current greenhouse management practices?
Significance of the study:
This study is significant as it explores how IoT-based smart greenhouse control systems can transform agricultural practices in Makurdi LGA. By enabling real-time environmental adjustments, the system can increase crop productivity, reduce waste, and enhance sustainability, offering valuable insights for farmers and agricultural policymakers.
Scope and limitations of the study:
This study is limited to the investigation and evaluation of IoT-based smart greenhouse control systems in greenhouse farming in Makurdi LGA, Benue State. It does not extend to open-field agriculture or other regions.
Definitions of terms:
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IoT (Internet of Things): A network of devices that exchange real-time data.
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Greenhouse Control System: A system that automates the regulation of environmental conditions in a greenhouse.
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Precision Agriculture: Farming techniques that optimize inputs based on real-time data.
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