HydroClawNics

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  Hydroclawnics Cover art

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  Hydroclawnics logo

Modern hydroponic farms generate constant sensor data across hundreds of pods... but existing tools just display it. They don't act, explain, or learn. Hydroclawnics changes that. We built an autonomous agent powered by NVIDIA NemoClaw and Nemotron 3 Super that reads live sensor data from every pod, reasons about crop health using species-specific target ranges for lettuce, tomato, basil, and spinach, and calls physical control functions to keep plants alive. Whether that be fan speed, heater, cooler, humidifier, or pH dosing, our agent's actions can be the defining moment between a healthy plant and one that needs to be discarded. Every decision streams to a live reasoning feed so operators understand exactly why the agent acted. The system runs on a hybrid architecture: one physical pot with real Arduino sensors, and 200 simulated pods running as a drop-in replacement. Flipping a single environment variable switches between hardware and simulation — the agent never knows the difference. Nemotron 3 Super's 1M token context window means the agent can supervise 500+ pods in a single reasoning cycle (the scale of a real commercial greenhouse) while only activating 12B parameters per token for fast, efficient inference on Brev. With multiple subagents, this could possibly be expanded further.

Built for three Hack-A-Claw tracks:

Cloud Track - full deployment on NVIDIA Brev with CI/CD pipeline NemoClaw Bonus - agent orchestration and security sandbox via OpenClaw Santa Cruz - Hydroponics is currently the most human-reliant field of agriculture, and bringing autonomous agents to monitor plants for people massively reduces the cost of mistakes and timeliness.

Tech stack: NemoClaw / OpenClaw · Nemotron 3 Super · NVIDIA Brev · FastAPI · React · Three.js · WebSocket · Arduino

Built With

• arduino
• fastapi
• nemoclaw
• nemotron
• nemotron-3-super
• nvidia
• nvidia-brew
• openclaw
• react
• three.js
• websocket