SmartHerd management: A microservices-based fog computing-assisted IoT platform towards data-driven smart dairy...

Area of Science:

• Agricultural Technology
• Computer Science
• Data Science

Background:

• The dairy industry can leverage Internet of Things (IoT), fog computing, cloud computing, and data-driven techniques to boost productivity through actionable insights.
• Improving farming practices, efficiency, and yield are key goals for modern dairy operations.

Purpose of the Study:

• To present SmartHerd, a fog computing-assisted IoT platform for real-time animal behavior analysis and health monitoring in dairy farms.
• To address challenges of constrained internet connectivity in remote farm locations using a microservices-oriented design.

Main Methods:

• Implementation of an end-to-end IoT platform utilizing fog computing principles.
• Deployment in a 6-month real-world dairy farm setting with wearable sensors on cows.
• Data classification and analysis performed on a fog-based platform for decision-making.

Main Results:

• SmartHerd provides actionable insights to farmers for improved animal welfare.
• An 84% reduction in data transferred to the cloud was achieved compared to traditional cloud-based approaches.
• The microservices-oriented design supports distributed computing and overcomes connectivity issues.

Conclusions:

• Fog computing-assisted IoT platforms like SmartHerd are effective for dairy farming, enhancing monitoring and reducing data transmission.
• The platform demonstrates significant improvements in data management and provides valuable insights for farm management and animal well-being.