Agriculture · Plantation operations
Repeat treatment, tree by tree.
Immature palms do not always need the same intervention at the same time. DroneDash shapes each plantation job around selected trees, an approved treatment plan and field evidence that can carry into the next cycle.
Technology at work
Our technology, working tree by tree.
DroneDash connects crop observation, tree location, analysis and targeted treatment. Our multispectral camera helps reveal differences in crop condition. See n Locate identifies individual trees with geospatial context. AgriSense 2.0 is being shaped to bring available observations and recurring field records into a review workflow. Agronomists approve treatment plans before field teams carry out targeted spraying.
Multispectral Camera
Captures crop observations in four spectral bands. Vegetation indices help highlight differences in canopy condition and identify areas for closer inspection.
Explore technologySee n Locate — AI Vision
Identifies individual trees and connects detections with geospatial information, helping teams locate the palms selected for inspection or treatment.
Explore technologyAgriSense 2.0
Brings available crop observations and recurring field records into a review workflow for inspection, approved treatment planning and follow-up.
Explore technologyNo-Mapping Point-to-Point treatment
Uses prepared treatment points to direct spraying to designated trees without requiring a separate mapping flight before every job.
Explore technology- 01Observe
- 02Locate
- 03Assess
- 04Treat
- 05Review
Potential applications
Use cases
Questions a pilot could explore by connecting DroneDash technology with field work and reviewable records. These are proposed workflows, not customer case studies or achieved outcomes; unverified integrations require implementation and validation.
Why do some growing sites produce better fruit while others produce more fruit?
01 · Pineapple quality and yield
Compare growing conditions, repeat crop observations, application records and harvest grading to guide agronomist-led inspection and testing.
Workflow, decisions & evidenceWhich palms need attention, what was approved and carried out, and what changed by the next visit?
02 · Palm treatment and follow-up
Connect reviewed tree selections, approved field action and later observations without automating the agronomist’s decision.
Workflow, decisions & evidenceWhat is growing where and how is each block or tree changing?
03 · Living plantation record
Build a permissioned, date-stamped record of locations, observations, visits and harvest history for recurring review.
Workflow, decisions & evidenceCan an operator review what was planned, done and checked?
04 · Treatment verification
Reconcile the approved job with available logs, operator observations and follow-up inspection, making evidence gaps explicit.
Workflow, decisions & evidenceWhat plantation evidence can owners share with independent reviewers?
05 · Digital plantation evidence for agricultural asset verification
Concept / potential applicationOrganise permissioned field evidence for separate independent checking; any future on-chain connection remains outside DroneDash’s field-evidence role.
Workflow, decisions & evidenceThe operating challenge
Return to the trees that need the work.
Young plantation blocks require recurring field attention while individual palms develop at different rates. A practical operation needs to identify the selected trees, reach them efficiently and preserve enough context for the next visit.
The focus is not a catalogue of aircraft and sensors. It is a repeatable job that gives field teams a clear treatment list and gives agronomists a record they can review over time.
How a No-Mapping P2P job runs
Selected points. One approved dose. A practical return visit.
Field teams prepare and review the trees selected for treatment. The aircraft follows those treatment points without requiring a separate remapping flight before every job, making the approach suited to recurring work across plantation blocks.
Every job follows an approved operating plan. Its dosage is fixed before takeoff and is not changed autonomously in flight.
Explore No-Mapping P2PAI Vision in flight
See the mission as it happened.
The footage shows AI Vision detecting and scoring multiple palm targets during flight. The adjacent panel is a separate GPS record of the aircraft’s mission route; it does not represent GPS coordinates assigned to each visual detection.
Recurring tree-level records
Give the next field cycle its context.
AgriSense 2.0 is being developed to connect field observations, recorded treatment activity and follow-up context across visits. Agronomists review the available evidence and approve treatment plans; managers and field teams record what was planned and carried out.
Over successive visits, the record helps teams ask practical questions: which trees were selected, what was done, what changed and where the next inspection should focus.
Explore AgriSense 2.0Field pilot
Measure the operation, not the promise.
Define the block, treatment target and operating constraints, then agree how the pilot will be measured. No assumed savings or invented benchmarks—only evidence from the field.
- Target accuracy
- Chemical and water use
- Field throughput
- Operating cost
- Post-treatment response
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