Optimizing Fertilization Through IoT: A Smart Approach for Agriculture

Precision agriculture is a forward-thinking and smart method of cultivating crops that involves the meticulous control of vital factors like nutrients, air, temperature, water, and ongoing surveillance throughout the entire farming process. In this research work, we propose an IoT-based model focused on fertilization detection, aiming to accurately predict the optimal quantity of fertilizer required for crops. The model operates through three key phases: acquisition, transformation, and analysis. During the data acquisition phase, relevant data is collected, capturing vital parameters essential for fertilization. The collected data undergoes change, wherein it is appropriately formatted and migrated to a cloud platform to ensure compatibility and accessibility. Subsequently, a comprehensive analysis is conducted, unveiling valuable insights. Based on this analysis, an appropriate response is generated and communicated back to the farmer, providing practical guidance for implementation within their specific cultivation region. This model will contribute to sustainable agricultural practices and empowers farmers with the tools to achieve enhanced productivity and profitability.