How about an agricultural drone that does not need an already prepared flight path to do its work on a field?
Because that is what two companies are proposing for the industry right now. Malaysian drone maker and services provider DroneDash Technologies has joined hands with GeodNet, to create GeoDash Aerosystems — a Singapore-incorporated joint venture developing a new class of agricultural spraying drones for large-scale, industrial farming operations.
GeodNet is a decentralised physical infrastructure network (DePIN) that builds a high-accuracy, blockchain-based GPS correction network, enhancing standard GPS from meter-level to centimeter-level precision. By utilising user-operated, rooftop "satellite mining" stations (nodes), it offers affordable Real-Time Kinematic (RTK) data for autonomous vehicles, drones, mapping, and robots
The two companies’ partneship stems from their view that conventional agriculture drones today require repeated manual pre-mapping before each deployment. And DroneDash should know, since they are in the business of manufacturing drone for the agriculture industry.
“Most agricultural spraying drones in operation today were adapted from general-purpose UAV platforms,” the companies said in a joint statement.
Before each deployment, operators must manually survey and map the field, generate static flight plans, and repeat the entire process whenever terrain, planting patterns, or canopy profiles change. In oil palm plantations and large-scale row-crop environments, this mapping overhead directly limits how many hectares a team can cover — and how quickly they can respond to emerging crop conditions.”
In response, GeoDash’s platform will use real-time AI Vision and centimetre-accurate RTK positioning to perceive, navigate, and adapt dynamically during flight.
The result should be faster deployment, lower operating costs, and continuous agronomic intelligence — from the same system that does the spraying.
“Agriculture does not need bigger drones — it needs smarter ones,” said Paul Yam, CEO, DroneDash Technologies and GeoDash Aerosystems.
“By removing repeated manual pre-mapping and integrating AI Smart Farming intelligence into every flight, we are turning spraying drones into tools that both execute operations and inform agronomic decisions. Plantation operators can move faster while improving consistency, efficiency, and outcomes.”
The operational constraints that the new GeoDash drone is set to solve include:
- Manual pre-survey and field mapping required before each deployment
- Static flight plans that must be recreated when terrain or canopy profiles change
- Limited adaptability to uneven terrain and mixed-age crops
- Repeated mapping cycles after replanting, pruning, or erosion events
According to the developers, GeoDash Aerosystems’ drone architecture removes pre-mapping from the deployment workflow entirely. Using DroneDash’s proprietary AI Vision system, the aircraft performs real-time perception of plantation structure, canopy height, and terrain features during flight.
In this, GeodNet’s RTK correction network will be instrumental in delivering centimetre-level positional accuracy throughout each mission, in several aspects of the spraying process that include:
- Deployment without pre-mapping or manual mission surveys
- Dynamic interpretation of rows, trees, and operational zones
- Continuous altitude and spray-rate adjustment over variable terrain
- Rapid redeployment after replanting or field reconfiguration
- Tree-level and zone-specific variable-rate application
“When centimetre-level RTK positioning is combined with real-time perception and backend analytics, autonomy becomes predictable and reliable,” said Mike Horton, Founder, GeodNet and Co-Founder, GeoDsh Aerosystems.
“GeoDash Aerosystems demonstrates how precision positioning infrastructure can enable both accurate operations and continuous data-driven agriculture management.”
Situational awareness is generated dynamically during flight — not through a separate pre-deployment process. Each aircraft maintains geofencing controls, safety constraints, and full operational data logging for regulatory compliance and audit traceability.
The new drone is integrated with DroneDash’s AI Smart Farming backend, which transforms every operational flight into a continuous data-collection activity. Spraying missions generate field data used to produce:
- Canopy density and uniformity analysis
- Crop stress and anomaly detection
- Zone-level health scoring
- Spray effectiveness validation
- Terrain and drainage profiling
- Historical trend analysis across blocks and seasons
“Backend AI analytics then deliver actionable decision support to plantation managers and agronomy teams,” the companies added.
“(Such as) early indicators of pest, disease, or nutrient stress; identification of underperforming zones; optimised spray timing and dosage; and data-informed planning for replanting and fertilisation. The drone functions as a continuous aerial intelligence layer, not a standalone spraying machine.”
GeoDash Aerosystems is targeting industrial agriculture markets where deployment speed, terrain adaptability, and precision matter most; like oil palm plantations in Southeast Asia; sugarcane, soybean, and corn operations in the United States; and palm, sugar, and broad-acre estates in South America.
The drone has been tested throughout 2025 and into early 2026 in collaboration with various farmers, and commercial deployment is targeted for the third quarter of 2026, following completion of manufacturing readiness and regulatory approvals.