From oil palm estates to controlled-environment farming, Acta deploys low-power sensor networks and AI models that turn soil, weather and canopy data into daily operating decisions — irrigation, fertigation, pest pressure and yield forecasting.
The challenge
- Large estates with limited connectivity and few field staff
- Irrigation and fertiliser applied on schedule rather than on need
- Pest and disease detected late, after visible damage
- Yield forecasting based on historical averages
Outcomes
- Water and fertiliser applied where the data says it is needed
- Earlier intervention on pest and disease pressure
- Block-level yield visibility for planning and financing
How Acta delivers
01
Solar-powered soil moisture, EC and micro-climate nodes across blocks
02
Long-range LoRaWAN backhaul designed for plantation topography
03
AI models correlating weather, soil and canopy imagery to yield
04
Drone and camera imagery scored for stress and pest indicators
05
Mobile alerts in the language the field team actually uses
Technology stack
LoRaWAN gateways and solar sensor nodes
Satellite and drone imagery pipelines
Time-series data platform with agronomic models
Offline-tolerant mobile field application
Related industries
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