Stewart Dairylands advances sustainable farming with IoT and AI-driven monitoring
Stewart Dairylands, a major farming enterprise in New Zealand, faced the challenge of increasing productivity and sustainability despite sparse connectivity and budget constraints. To overcome these, Stewart Dairylands partnered with Microsoft and Aware Group to deploy Microsoft Azure FarmBeats, an end-to-end AI and IoT agriculture platform. FarmBeats collected sensor and drone-based data to monitor soil moisture, temperature, and crop health, even across large, hard-to-connect tracts of land using a TV White Space network. By combining sparse sensor deployment with regular drone flights, the solution produced precision heatmaps and insights for managing crops and livestock more proactively. All data is aggregated securely in the cloud for advanced analysis using machine learning, allowing farmers to optimize irrigation, fertilization, and operational decisions. The project reduced hardware costs by 90 percent and demonstrated the viability of data-driven precision agriculture at scale. Future plans include expanding the platform with edge machine learning and farm robotics for further automation and environmental benefits.
- Organization
- Stewart Dairylands
- Industry
- Agriculture
- Location
- New Zealand
Reported outcomes
−90%
costCost savings
Strategic outcomes
Catalog median for cost savings deployments: −45% across 345 reported metrics. Compare benchmarks →
Primary read
Use case focus
Showing 2 of 2
- 1IoT-based Precision Farm Monitoring
- 2Drone-Enhanced Agricultural Analytics
- Limited connectivity and high costs for deploying precision agriculture technology over large farmland.
- Sustainability pressures and environmental challenges, such as climate change and resource depletion.
- Inefficient manual monitoring of field conditions and crop health.
- Need for proactive decision-making to increase productivity.
- Deployed Microsoft Azure FarmBeats combining AI, IoT sensors, and drone imagery.
- Used TV White Space networking to extend Internet coverage affordably across the farm.
- Implemented cloud-based aggregation and analysis of sensor data with precision heatmaps.
- Planned integration of edge machine learning and connected robots for future operations.
- Achieved 90% reduction in physical hardware costs for monitoring.
- Enabled data-driven decision-making with near real-time insights.
- Expanded precision agriculture coverage despite sparse connectivity.
- Improved farm productivity and sustainability outcomes.
Architecture
Azure FarmBeats ingests data from IoT sensors and drones, transmits it over a TV White Space (TVWS) network to cover remote farmland, and aggregates it securely in the cloud. Machine learning models analyze this data to create precision heatmaps and summary insights for agricultural management. The system integrates with planned edge machine learning devices and robotics for further automation.
Implementation partners1
Sources & evidence2
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