Agricultural IoT Data Platform

Headless Infrastructure for
Precision Agriculture

Modern farms are massive, distributed sensor networks. Stop fighting rigid database schemas that break every time you buy a new type of drone. Unify static farm telemetry with high-frequency microbiome metrics in one queryable graph.

Clone Agriculture Blueprint Read the Docs

The IoT Integration Nightmare

Ag-Tech teams often hardcode their databases to track specific metrics like "Rainfall" or "Temperature." But when the farm upgrades to advanced Nitrogen sensors or Drone-based spectral cameras next season, the entire backend breaks.

✗ Relational databases require costly migrations just to add a new 'Nitrogen ppm' column.
✗ Time-series metrics are usually siloed away from physical geography data (Zones).
✗ Proving 'Organic' status to auditors is nearly impossible without immutable logs.
✗ Data scientists struggle to merge disjointed drone and soil datasets for yield forecasting.

Hierarchical Farm Schemas

Omnismith's flexible reference attributes allow you to map the physical reality of a farm perfectly. Nest thousands of "Soil Sensor Nodes" under specific "Agricultural Zones" to aggregate data geographically.

✓ Dynamic Scaling: Add entirely new sensor templates without writing backend code.
✓ Geographic Rollups: Query metrics based on the Parent Zone.
✓ Hybrid State: Track static firmware versions alongside continuous telemetry.

Template: Agricultural Zone

Zone Name String

Crop Type List — Wheat / Soy / Corn

USDA Organic Certified Boolean

Expected Yield Target Number

Template: Soil Sensor Node

Node ID String (Unique)

Deployed Zone Reference → Agricultural Zone

Nitrogen (ppm) Metric (Time-Series)

Soil Moisture (%) Metric (Time-Series)

Agronomy & Yield Forecasting

Transform raw sensor data into actionable agronomy insights. The built-in AI Assistant can autonomously fetch historical soil metrics and generate yield forecasts directly in your workspace.

Omnismith Copilot

Yield Analytics

YOU

How is the moisture trend looking for "Sector 7G" over the last week? Will it hit the expected wheat yield target?

Tool Call: search_entities

{ "template_id": "agri_zone_xyz", "query": "Sector 7G" }

Tool Call: get_entity_chart

{ "entity_id": "zone-7g-id", "metrics": ["soil_moisture_pct"], "time_range": "last_7d" }

Over the last 7 days, Sector 7G has seen a steady 12% drop in soil moisture, falling below the optimal 35% threshold for Wheat.

If irrigation is not increased within the next 48 hours, the predictive model indicates a 15% reduction from your expected yield target. I recommend activating the drone drip systems immediately.

Organic Certification Logs

Achieving and maintaining USDA Organic certification is a paperwork nightmare. Omnismith acts as an unalterable system of record, logging every chemical or action applied to a specific zone.

✓ Prove to auditors that no synthetic pesticides were applied.
✓ Track exactly who certified a zone and when.
✓ Export comprehensive, immutable history reports instantly.

Sector Audit Ledger

certifier@usda.gov 3 weeks ago

Changed USDA Organic Certified: False → True

agronomist@farm.com 2 months ago

Changed Crop Type: Soy → Wheat

Scalable IoT Metric Ingestion

Use the standard REST API to seamlessly push thousands of data points per minute from field sensors, drones, or automated weather stations.

# Python: Farm gateway cron job pushing sensor data

import requests

# Direct ingestion to the specific sensor entity
url = "https://api.omnismith.io/v1/entities/SENSOR_NODE_UUID/metrics"
headers = {
    "Authorization": "Bearer omni_farm_gateway_token_xxx",
    "Content-Type": "application/json"
}

data = {
    "attribute_values": [
        { "attribute_id": "nitrogen_ppm", "value": 45.2 },
        { "attribute_id": "soil_moisture_pct", "value": 22.8 }
    ]
}

requests.post(url, headers=headers, json=data)
# 202 Accepted