AI Assisted Drone Crop Monitoring
Centralize and analyze all field-specific data to make informed decisions and enhance field transparency year-round.
Receive, transmit, and analyze all field-specific information in one place, enhancing transparency and enabling well-informed decision-making throughout the year.
Create customized management zones based on your operational needs, leveraging current biomass maps and historical yield potential data to optimize field activities and monitor performance effectively.
Using a detailed analysis of soil, elevation, and historical yield data, create variable rate seeding maps tailored to each zone of your field.
These customizable maps are compatible with most terminals, allowing you to optimize seeding density for cost savings and improved harvests.
This approach reduces seeding costs in low-performing zones and increases productivity in high-potential areas, leading to higher overall yields.
With a geodata backed nutrient management system, you can precisely optimize the timing and dosage of nutrients for your crops using a combination of satellite data, growth-stages models, and historical field data.
By integrating these insights with your field history, you achieve precise and efficient nutrient distribution for better crop health and productivity.
This technology ensures that your plants receive the right nutrients at the right time, increasing efficiency and improving yield outcomes.
While traditional methods of field monitoring provide valuable insights, they often require significant manual effort and may not always capture real-time changes effectively. This is where automated drone monitoring comes into play. Drones equipped with sophisticated sensors and imaging technology can survey large areas quickly and accurately, providing up-to-date information on crop health, soil conditions, and pest activity. By integrating automated drone monitoring with systems, farmers can receive real-time alerts and actionable insights, enabling them to respond swiftly to emerging issues and optimize their field management strategies further.
Automated drones eliminate the guesswork and labor-intensive nature of conventional monitoring methods, offering a precise, efficient, and scalable solution for modern agriculture.
Drone Monitoring
Drones can quickly monitor of vast areas, unobstructed by terrain or ground weather conditions. The image and video data generated rapidly reaches terabytes of data, making manual analysis and evaluation costly or even impossible. This problem only intensifies you deploy drone swarms and the multi spectral imaging data gathered exceeds the human-visible RGB light range.
In such cases, a project requires automated analysis for full scalability.
In preparation for the final, fully automated and scaled production run, the project team must train AI models to extract the relevant information from image and or video data, removing the need to store the raw video material and eliminating the need for manual evaluation in most cases.
The team must provide reliable and extensive ground truth data, deduced from a subset or pre-run of the final images. During this first step of the automation process, team members use HS Analysis’ HSA KIT for the dataset creation.
HSA KIT Supports Annotations
But the software does not stop at the annotations, it also allows for individualized and optimized data display settings. For example, an annotator may choose to adjust the settings of individual colors and/or channels using HSA KITs histogram to better view features within the image. Whilst not influencing the actual raw data, adjusted histogram settings will not only help the user, but also the semi-annotated annotation tools.
Furthermore, once team members determine beneficial presets, they can “freeze” these in place and wrap them up as a HSA KIT module. Here, collaborating team members preserve the settings and pass them on between each other, allowing for quick entry of new members and reproducible results.
Should it be too early to fixate the settings in a module, users may export settings and share them. This is also used to store different reusable profiles.
HSA KIT assists the annotation process with its annotations tools, that range from fully manual over semi-automatic to AI-supported annotation tools. Depending on the specifics of the objects to detect, the annotator team can leverage an objects shape, color, or combination of both for accelerated dataset creation.
Specifically, HSA KITs intuitive and performant interface allows the annotators to begin work right away without much introduction.
Flexible Deployment Options
Speaking of team collaboration, some project scopes will require teams too large for a single location. Alternatively, your drone swarms might deploy not only locally but within the greater region, or even globally. Annotators may need region specific knowledge and thus work in a distributed manner.
HSA KIT accounts for this. It is an integrated web application and runs on most browsers and operating systems. Additionally, it can be deployed locally, as a Docker container, and using Kubernetes, whatever fits the requirements most. For large scale applications such as this one, administrators prefer the Kubernetes variant and keep all data in a single, self-hosted data center and profit of speed by proximity and scalability factors.
Integration Into Own Systems
HSA KIT provides the full capabilities of AI training: ground truth data (GTD) generation, model training, model execution. In some occasions you may only want a specific subset of these features. In this case, the GTD generation was the primary interest.
Using HSAs API, the distributed annotations could be collected in a central location and further processed using HSA-external tools, without limitations. Even though full processing within HSA KIT is recommended, integration into external infrastructure was completed and appropriate documentation provided.