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.

1. 01Limited connectivity and high costs for deploying precision agriculture technology over large farmland.
2. 02Sustainability pressures and environmental challenges, such as climate change and resource depletion.
3. 03Inefficient manual monitoring of field conditions and crop health.
4. 04Need for proactive decision-making to increase productivity.

1. 01Deployed Microsoft Azure FarmBeats combining AI, IoT sensors, and drone imagery.
2. 02Used TV White Space networking to extend Internet coverage affordably across the farm.
3. 03Implemented cloud-based aggregation and analysis of sensor data with precision heatmaps.
4. 04Planned integration of edge machine learning and connected robots for future operations.

1. 01Achieved 90% reduction in physical hardware costs for monitoring.
2. 02Enabled data-driven decision-making with near real-time insights.
3. 03Expanded precision agriculture coverage despite sparse connectivity.
4. 04Improved farm productivity and sustainability outcomes.

• Enabled precision agriculture monitoring at scale
• Enabled data-driven farm decisions
• Reduced monitoring hardware costs
• Improved farm sustainability outcomes