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Paper short abstract:

This paper presents a Decision Support System that integrates multi-source data fusion and AI to forecast crop growth, yield, and profitability. Furthermore, the knowledge and experience gained during the development and implementation of this tool in collaboration with producers will be shared.

Paper long abstract:

This paper presents a Data-Driven Decision Support System that integrates remote sensing, multi-source data fusion, and Artificial Intelligence (AI) to forecast crop growth, yield, and profitability. Initiated in 2019, the project involved collecting data from 100-hectare fields using Unmanned Aerial Systems (UAS), weather stations, and satellite imagery. Through continuous collaboration with producers, we developed a decision support system capable of simulating future crop growth and development. These datasets were further utilized to inform crop management decisions and improve yield estimations. Our system can predict yield at least two months before harvest, enabling early profit calculations and informed marketing strategies. By incorporating "what-if" scenarios, the tool enhances risk mitigation and strengthens producers' trust in AI-generated insights. Over the past five years, we have actively engaged with local producers, refining the tool based on their feedback. This presentation will highlight the progress made in developing the decision support system and our efforts in implementing a User-Centered Design approach to improve adoption and build farmers' confidence in these AI-driven tools.