Collect sensor data from agricultural equipment automatically

Purpose

1.1. Capture real-time sensor data (e.g., soil moisture, equipment diagnostics, weather conditions) from agricultural machinery for seamless integration into centralized monitoring, analytics, and decision-support systems.
1.2. Improve operational visibility, enable preventative maintenance, optimize yields, unify field data streams, and provide rapid insights for agronomic engineering teams and farm managers.
1.3. Eliminate manual transcribing, reduce data latency, enhance data integrity, and automate data distribution to downstream applications.

Trigger Conditions

2.1. New sensor reading captured by onboard device.
2.2. Scheduled polling interval completed (e.g., every 15 mins).
2.3. Event-driven anomaly or threshold breaches (e.g., critical temperature, equipment error).
2.4. Wireless transmission from the equipment-control unit.
2.5. Remote request from central data management system.

Platform Variants

3.1. AWS IoT Core
• Feature/Setting: Device Data Ingestion; configure MQTT topic for incoming payloads, enable rules engine for downstream routing.
3.2. Microsoft Azure IoT Hub
• Feature/Setting: Device-to-cloud messages; set up device identities and routes, manage endpoints for field gateway.
3.3. Google Cloud IoT Core
• Feature/Setting: MQTT/HTTP bridge; register device registry, activate telemetry topic publishing.
3.4. Siemens MindSphere
• Feature/Setting: Asset Management; create MindConnect integration, define sensor tags for live data sync.
3.5. John Deere Operations Center API
• Feature/Setting: Machines API; register machine endpoint, pull machine telemetry in JSON format.
3.6. CNH Industrial API Suite
• Feature/Setting: DataConnect API; configure authentication, access telemetry channel endpoints.
3.7. Climate FieldView Platform
• Feature/Setting: FieldView Drive; enable telematics device data sync, set webhook endpoint for streaming.
3.8. IBM Watson IoT Platform
• Feature/Setting: Device Management; set up device type, subscribe to sensor event messages.
3.9. Azure Logic Apps
• Feature/Setting: IoT Hub Trigger; create workflow on sensor event, route to storage or analysis pipeline.
3.10. SAP Leonardo IoT
• Feature/Setting: Device Connectivity; configure Thing Model, enable data collection rules for sensors.
3.11. PTC ThingWorx
• Feature/Setting: Asset Data Service; set up AlwaysOn protocol, configure property read triggers.
3.12. Kubos KubOS (Satellite & ground IoT)
• Feature/Setting: API Telemetry Endpoint; post data via gRPC or REST when telemetry pushed.
3.13. Bosch IoT Suite
• Feature/Setting: Device Management HTTP API; register equipment, post sensor batch data with authentication.
3.14. LoRaWAN Network Servers (e.g., The Things Network)
• Feature/Setting: Uplink Decoder; decode device payload, forward via integration Webhook.
3.15. Sigfox Cloud
• Feature/Setting: Callback Configuration; set POST/GET to automation endpoint on new device message.
3.16. Trimble Ag Software API
• Feature/Setting: Telematics API; set credentials, fetch raw field device telemetry periodically.
3.17. Kubota Connect Portal
• Feature/Setting: Data Streaming API; configure client credentials, receive JSON packets over websocket.
3.18. Ag Leader AgFiniti
• Feature/Setting: REST API; enable device data sharing, poll for latest sensor data logs.
3.19. Farmobile DataEngine Platform
• Feature/Setting: ingestor endpoint; facilitate live data push from Farmobile devices.
3.20. MQTT Open Source Broker (e.g., Eclipse Mosquitto)
• Feature/Setting: Topic Subscription; configure topic filters (e.g., “sensors/tractor/temperature”) and handle incoming payloads.

Benefits

4.1. Enables real-time field visibility and fast anomaly response.
4.2. Reduces manual data entry, freeing up engineering resources.
4.3. Standardizes and unifies diverse data streams for advanced analytics.
4.4. Supports predictive maintenance and lowers field equipment downtime.
4.5. Establishes scalable data infrastructure supporting future IoT expansion.