Empowering Agriculture with Real-Time Insights!
Embrace the future of agriculture with Filahi! We are at the forefront of agricultural innovation, specializing in providing real-time reports and actionable insights to end-users through our advanced drone technology. By leveraging our meticulously developed models, we can precisely detect diseases, identify insects, and monitor crop health, enabling farmers and agricultural enterprises to make informed decisions swiftly and effectively.
Explore Our Solutions
Satellite
Satellite Observation
Satellite data collects detailed information to predict and compare crop health. Discovering early threats before they become issues. Allowing our users and pilots to get an overview of the critical crops that require immediate action or flight mission. Observations are updated weekly, providing key information to monitor crops remotely.
Drone
Drone Intelligence
Using state of the art high resolution cameras to map fields to the millimeter accuracy, leading the way for the first time to precise leaf imagery. We developed advanced deep learning models to detect growth stage, weeds, insects and diseases in real time over our cloud based platform.
Spraying
Drone Spraying
Our crop reports come up with spraying suggestions that not only save 90% of water but also up to 60% of pesticides or insecticides thanks to variable, autonomous and targeted spraying technology. A step forward for better chemical products management and decreased environmental impact.
Multispectral
MSAVI
MSAVI indicates the presence of vegetation in the early growth stages, especially when there is a lot of bare soil present.
Drone Monitoring
Real-Time Data Analysis for Drones
Real-time data analysis for drones means analyzing data from drones in real-time using advanced algorithms and machine learning models. This helps drone operators quickly make informed decisions and take immediate action. It is crucial for efficient and effective drone operations in industries like agriculture, construction, and surveillance.
Step 1
Utilize drones to capture images, and then send the captured images to a server for analysis.
Step 2
On the server, analyze the images to determine the percentage of weeds, insects, and diseases present.
Step 3
Based on the analysis, the model decides whether it needs to capture more images or move to the next location.
Ready!
Choose What type of images you would like to upload
Scouting Images
Non-overlapping images collected in different parts of the field at different altitudes with the purpose of getting leaf-level details.
Overlapping Images
Images collected with front and side overlap with the purpose of creating an orthomosaic, elevation map, plant health map, and prescription.
Stitched Map
Import a stitched map (GeoTIFF) from other tools, to generate plant health map, prescription, and more.
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