Enhancing Maize Cultivation with Intelligent Decision Support: IoT, Deep Learning, and Blockchain Integration for Land Data Analysis

Maize cultivation is essential for global food security and economic growth, yet it is complex with difficulties owing to climate change and resource constraints. Traditional agricultural methods frequently result in optimum productivity, resource usage, and sustainability. Hence described a novel method to enhance maize production that combines IoT, deep learning, and block chain technology. Existing methods are incapable of providing real-time data-driven insights, resulting in poor crop management. The proposed method makes use of IoT sensors to capture continuous data, deep learning for predictive analytics, and blockchain for secure data administration. The integration empowers farmers with intelligent decision support. Following the insights provided by the recommendation model, the study shows consistent gains in agricultural output of 24%, reduced resource usage and sustainability over three batches. The integrated system exceeds the existing system in terms of accuracy with 92.5% and F1 score of 0.915. These findings illustrate the system's ability to greatly improve maize production methods, eventually contributing to food security and sustainable agriculture.