DroneDash technology
From field imagery to decisions farmers can act on.
See n Spray brings AI navigation, tree geolocation and multispectral analysis together during flight. AgriSense connects what is observed with approved actions and follow-up. LIBS appears lower down as a separate concept.
The flight workflow
See. Locate. Analyse—as the drone operates.
DroneDash combines AI navigation, tree geolocation and multispectral analysis during flight. As individual trees are located, the system analyses their spectral observations without a separate post-flight processing step. An ambient-light sensor measures illumination to support the analysis.
- Left — Multispectral analysis during tree geolocation
- Top right — Ambient light sensing
- Middle right — Drone position and attitude
- Bottom right — Tree map and geolocation
This demonstration shows navigation and sensing; spray activation is not shown.
In flight · See n Locate navigation and tree geolocation
Find the target. Know where it is.
DroneDash built See n Locate using a dataset of more than six million data points, including AI training data and digitised trees across different ages and conditions. The system identifies multiple targets in field imagery and presents them alongside relevant geospatial information, so operators can review what was detected and where action may be needed.
Within See n Spray, AI Vision supports the aircraft’s self-navigation and geolocates trees as it flies.
In a plantation, this supports individual tree inspection and selective treatment. The same approach can be adapted to other crops and field tasks where both the target and its location matter.
Value Target detection, visual evidence and geospatial context for field decisions.
In flight · In-house four-band camera
See crop condition as you capture it.
DroneDash’s in-house multispectral camera processes imagery during capture, displaying vegetation indices to help clients review crop-condition indicators in the field—without waiting for a separate post-flight processing step.
The system can combine these observations with geospatial information to support tree-level inspection.
Within See n Spray, the camera’s readings are analysed as each tree is geolocated, as shown in the flight demo above.
Vegetation colours are indicators, not a disease diagnosis.
After the flight
Review observations, assign follow-up and compare visits.
Flight observations hand off to AgriSense, where teams review each tree, assign follow-up for agronomist approval and compare the next visit.
See AgriSense 3.0
Emerging capability
Understand the soil’s elemental composition.
DroneDash is exploring Laser-Induced Breakdown Spectroscopy (LIBS) to bring elemental sensing into agricultural field assessment.
LIBS directs a short laser pulse onto a small spot on a sample, creating a tiny plasma. The light emitted reveals signatures of the elements present. With suitable calibration, this can help assess selected nutrient-related elements and variations in soil composition.
Our development direction is to connect these measurements with geospatial information and AgriSense 2.0. This would allow farmers to review soil composition alongside crop imagery, soil-sensor readings and weather data when planning sampling and fertiliser application.
Intended value More detailed soil information to support targeted assessment and nutrient management.
Development focus Field sampling, calibration against laboratory results, and integration with DroneDash’s sensing and analysis platform.
From technology to field work.
Explore No-Mapping P2P as a treatment method, with an approved plan and prepared treatment points.
No-Mapping P2P