Development of an IoT‐Based Smart Real‐Time Crop Disease Identification System in Wukari LGA, Taraba State
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Background of the study
Agriculture in Wukari LGA is a cornerstone of the local economy, yet crop diseases continue to threaten productivity and food security. Traditional disease identification methods are often slow, labor-intensive, and reliant on expert diagnosis, leading to delays in treatment and significant yield losses. The advent of IoT-based smart real-time crop disease identification systems offers a transformative solution by integrating advanced sensor technology, image processing, and artificial intelligence to monitor crop health continuously. These systems utilize high-resolution cameras, environmental sensors, and machine learning algorithms to detect early signs of disease by analyzing visual and climatic data (Bello, 2023). By providing real-time alerts and diagnostics, farmers can implement timely interventions to mitigate disease spread, thereby reducing losses and improving crop yield. The integration of these systems into the agricultural workflow also facilitates the collection of extensive datasets that can be used to predict disease outbreaks and optimize treatment strategies (Ibrahim, 2024). In Wukari LGA, where resource limitations often impede rapid disease management, such innovations represent a significant advancement in sustainable agriculture. However, the adoption of IoT-based disease identification systems is not without challenges. High costs, technical complexity, and the need for continuous system calibration are among the hurdles that must be overcome (Chinaza, 2025). This study aims to develop and evaluate an IoT-based smart real-time crop disease identification system tailored to the specific needs of farmers in Wukari LGA, focusing on its effectiveness in early disease detection, operational feasibility, and potential to enhance overall agricultural productivity.
Statement of the problem
Farmers in Wukari LGA frequently struggle with delayed and inaccurate diagnosis of crop diseases due to the limitations of traditional identification methods. These conventional approaches are often characterized by manual field inspections and expert consultations that are time-consuming and costly, leading to delayed interventions and significant crop losses (Ibrahim, 2024). The absence of a real-time monitoring system exacerbates the situation, allowing diseases to spread rapidly before effective measures can be implemented. Although IoT-based smart systems offer the potential for immediate detection and early warning, their deployment is hampered by issues such as high initial costs, limited technical expertise among local farmers, and the need for robust connectivity in rural areas (Bello, 2023). Moreover, the variability in environmental conditions and crop types in Wukari LGA adds to the complexity of developing a one-size-fits-all solution. This study seeks to investigate these challenges and explore the feasibility of implementing an IoT-based smart real-time crop disease identification system. By evaluating the system’s accuracy, responsiveness, and operational challenges, the research aims to provide actionable recommendations for optimizing its deployment in the local agricultural context (Chinaza, 2025).
Objectives of the study
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To design a prototype IoT-based crop disease identification system.
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To evaluate the system’s accuracy and responsiveness in early disease detection.
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To identify operational challenges and propose strategies for effective implementation.
Research questions
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How accurately does the IoT-based system identify crop diseases in real time?
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What technical challenges are encountered during system deployment?
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How can the system be optimized to suit local agricultural conditions?
Significance of the study
This study is significant for advancing agricultural practices in Wukari LGA by integrating IoT-based real-time disease identification systems. The insights gained will aid farmers in early detection and management of crop diseases, thereby improving yields and contributing to food security and economic stability (Bello, 2023; Chinaza, 2025).
Scope and limitations of the study
The study is limited to IoT-based crop disease identification systems in Wukari LGA. Limitations include high setup costs and connectivity issues.
Definitions of terms
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IoT (Internet of Things): A network of devices that collect and transmit data automatically.
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Crop Disease Identification: The process of detecting and diagnosing diseases affecting crops.
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Real-Time Monitoring: Continuous surveillance and analysis of crop conditions as they occur.
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