| Popis: |
At present, the time, labor, and inaccuracies in plant and seedling care make feasibility a major concern in large-scale agricultural operations. Developments in Internet of Things (IoT) technology and image classification by deep learning have made it possible to monitor various aspects of plant conditions, but an integrated solution that combines IoT sensor data, high-resolution imagery, and manual intervention data in a synchronized time-series database environment has not yet been brought to market. In this paper, we propose such an integrated solution. The overall system architecture is outlined, as well as the individual components including sensors, drone imagery, image processing, database framework, and alerting mechanism. These components are brought together and synchronized in a time-series database. By synchronizing all the variables, this solution presents a comprehensive view and better means for intervention. Finally, opportunities for research and specific component improvements are identified. |
