Drone-Assisted Climate Smart Agriculture (DACSA): The design of the groundwork flow data for drone operations

The success of precision farming hinges on effective ground support and workflow. In pursuit of this, we undertook a thorough requirement study of the system necessary for precision farming and developed a precision farming data flow model in ground support. The prototype hardware ground support and conceptual data flow provided valuable guidance in the successful realization of Drone-Assisted Climate Smart Agriculture (DACSA). Using open-source software to accommodate a range of data processing algorithms becomes crucial in operationalizing ground support for precision farming. This study has culminated in a comprehensive prototype model for precision farming operations that can be executed with confidence. The management system of flow data for precision farming has been drawn, this platform is specifically crafted to streamline agriculture operations by transforming diverse inputs into useful spatial data. To maintain the growth of the database, it is necessary to incorporate it in the entire crop cycle. The integration of this database can significantly enhance the precision of predicting plant performance. While this innovative approach is still in progress, it has already demonstrated its potential in supporting informed decision-making. For the next, it is imperative that we prioritize research aimed at creating decision-support algorithms that can effectively gather and blend information pertaining to soil, crops, and weather into actionable maps. These maps must incorporate location-specific data and be utilized by agricultural professionals for on-site decision-making. Moreover, they must be well-suited for drone usage in tasks such as monitoring, mapping, or spraying.