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Agriculture

§ Agriculture

Precision farming, autonomous.

AI-powered crop monitoring and autonomous farm equipment running independently in the field.

§ Why edge AI

The case for running it on the asset.

Connectivity in a 200-hectare field is unreliable, expensive, and slow. AI has to run on the tractor, the drone, or the soil sensor — not in someone's data center. The E1M-AEN handles always-on environmental sensing at sub-1 mW; the V2N adds AI vision for autonomous spraying, weed detection, and yield estimation; all in industrial-temperature packages that survive a Swedish winter.

§ The constraint

Field-deployed sensors can't phone home every minute on solar power. Tractors run faster than the cellular tower can stream. Crop-detection latency is measured in centimetres of travel.

Cloud round trip

sensor → uplink → inference → downlink → action

On-module

sensor → on-module inference → action

Sensor

Crop camera feed

On-module inference

E1M-AEN

Action

Per-plant treatment decision

§ Recommended modules

Pick the AI compute that fits.

§ Reference examples from the Alp SDK

Code you can fork and ship.

Every example is real C/C++ in the open-source alp-sdk repo. Clone, change the SKU in board.yaml, build.

§ Built for this vertical

Why E1M wins here.

<1 mW always-onIP67-ready · sealed carrier−40 to +85 °C

§ Get building

Ready to ship agriculture with E1M?