Optimizing planting schedules and land use through advanced weather monitoring systems - Kravtsov Kirill; Kukartsev Vladislav (BIO Web of Conferences)
This article explores the development of an information system (IS) designed to monitor weather conditions and optimize planting schedules and land use for agricultural activities. Leveraging advanced modeling techniques, the system’s architecture and processes are meticulously mapped out to ensure clarity and efficiency. The system collects weather data from ground-based sensors, satellite imagery, and drones, which is then analyzed to provide actionable insights. Key components include the WeatherDataCollector, WeatherAnalyzer, PlantingScheduleOptimizer, and NotificationManager. Sequence diagrams illustrate the interactions between these components, from data collection to analysis and dissemination of recommendations. The system enhances decision-making for farmers, improving crop yields and optimizing land use while mitigating risks associated with adverse weather conditions. By integrating robust data management and analytical capabilities, the IS provides a scalable and reliable solution for modern agriculture, driving innovation and sustainability in the sector. This work underscores the transformative potential of technology in optimizing agricultural practices and land management.