Australian Consolidated Milk transforms sustainable dairy farming with IoT and AI

Australian Consolidated Milk (ACM) partnered with Advance Computing and WaterForce to implement Microsoft Project FarmBeats, leveraging IoT and AI technologies to increase food production sustainably. The project deploys IoT sensors, low-cost Windows IoT devices, and drones driven by Azure Cloud and Azure IoT Edge to gather and analyze data from fields and livestock. The system ensures precise monitoring of soil, crops, and milk temperature, with real-time notifications to farmers for rapid corrective actions. By overlaying WiFi signals over unused TV channels (TV white spaces), even remote areas can transmit sensor and drone data to the cloud, overcoming rural connectivity barriers. Advance Computing helped ACM automate milk quality monitoring, resulting in reduced waste and higher quality control. WaterForce’s SCADAFarm system was used by New Zealand’s Blackhills Farm to manage water resources efficiently, customizing irrigation in real time. Another example is Kagome, an Australian tomato producer, using IoT-based solutions for automating shipment tracking and operational transparency, delivered via Advance Computing. The technology mix, focused on Azure Cloud, Azure IoT Edge, Computer Vision, and AI, helps optimize water usage, power consumption, crop yield, and environmental sustainability. The outcome is a dramatic improvement in operational efficiency, traceability, and environmental impact across multiple Australian farms.

Industry
Agriculture
Location
Australia
Published
March 2019

Reported outcomes

Strategic outcomes

Customer experience & trustReduced milk spoilage and wasteNew product / capabilityEnabled real-time farm monitoringScale & capacityExpanded connectivity for remote farmsSustainability & ESGImproved resource efficiency and yield

Primary read

Use case focus

Showing 3 of 4

  • 1Precision Dairy Monitoring and Notification
  • 2Automated Irrigation Optimization Using IoT Sensors
  • 3Crop and Livestock Tracking with AI and Computer Vision
  • Need to sustainably increase food production to feed a growing population.
  • Quality control issues such as milk spoilage due to incorrect temperature handling.
  • Water scarcity and inefficient irrigation practices on large farms.
  • Lack of real-time insights and operational transparency in remote rural areas.
  • Deployment of Azure Cloud with Azure IoT Edge and low-cost Windows IoT sensors to capture and analyze agricultural and livestock data.
  • Use of drones and computer vision for real-time farm mapping and monitoring.
  • Overlaying WiFi signals over TV white spaces to enable rural IoT connectivity.
  • Real-time data-driven notifications for milk temperature, irrigation systems, and shipment tracking.
  • Reduced milk spoilage, saving up to $10,000 per spoiled load and mitigating environmental impact.
  • Automated, real-time notifications enable rapid anomaly responses and reduce human intervention.
  • WaterForce’s system reduced water and power usage while increasing yield at Blackhills Farm.
  • Kagome’s automated traceability solution paid for itself five times over in the first season.
Architecture

IoT sensors, drones, and animal trackers collect environmental and livestock data across farms. WiFi signals over TV white spaces carry the data to on-premises PCs running Azure IoT Edge, which processes with Project FarmBeats AI and Computer Vision. Data is then transmitted to Azure Cloud for analysis and remote monitoring. Real-time notifications are sent to farmers, and irrigation systems are managed by SCADAFarm for water efficiency. Shipment traceability is managed with farm, vehicle, and loading bay IoT systems, all reporting centrally.

Implementation partners2
Sources & evidence2
Groundedness: Unavailable

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