AI-Enhanced Dairy Farm Monitoring
Prudent Partners supported a dairy automation company by annotating complex surveillance footage for cattle behavior, movement, and workflow tracking. The project enabled precision AI monitoring and improved operational efficiency across dairy farm environments.
Case Details
Clients: Pixel Art Company
Start Day: 13/01/2024
Tags: Marketing, Business
Project Duration: 9 Month
Client Website: Pixelartteams.com
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Executive Summary
A leading dairy software and analytics provider partnered with a video annotation team to enhance AI monitoring of dairy farm workflows. By annotating real-world farm footage, AI was trained to detect deviations in milking protocols, aggressive cow handling, and inconsistencies in employee behavior. This provided farm owners with actionable insights to improve animal welfare, ensure compliance, and streamline operations.
Introduction
Background
In large-scale dairy farms, even minor deviations in protocol can harm cattle, reduce milk quality, and incur economic losses. The client aimed to equip AI systems with the ability to detect both subtle and critical violations during milking routines, including improper handling techniques and aggressive interactions, through precise human-verified video annotation.
Industry
Dairy Farming / AgTech / AI-Powered Farm Analytics
Tools Used
Client-provided video annotation platform with real-time submission and review utilities
Products/Services
Video annotation services across three streams:
- General Workflow Monitoring: Detecting protocol deviations and mistreatment
- Targeted Employee Review: Focused analysis of employees with prior inconsistencies
- Routine Quality Assessment: Measuring time spent per milking stage and adherence to defined procedure timelines
Challenge
Problem Statement
AI models struggled to detect violations due to suboptimal camera angles, dust-covered lenses, or workers stepping out of frame.
Impact
- Missed training opportunities
- Reduced animal health and welfare
- Inefficiencies in milking routines
- Lack of actionable data for farm management
Solution
Overview
Human annotators verified and labeled farm footage, flagging moments of concern and deviations from protocol with precise timestamps and contextual notes.
Implementation Approach
- Annotators reviewed hours of footage across all three project goals
- Identified 26+ types of milking protocol deviations, including:
- Manual detaches
- Reuse of towels across cows
- Skipped sanitation steps
- Aggression or unsafe behavior toward cows
- Marked timestamps and behavioral context for each incident
- Evaluated employee performance on speed, timing, and consistency
- Used real-time submission with QA reviews for feedback and calibration
Tools & Resources Used:
- Client-developed annotation software
- Dynamic task assignment for real-time video analysis
- Feedback loop and QA sampling to ensure consistency
Results
Outcome
The AI system, enhanced by detailed human annotations, could detect harmful behavior and protocol breaches even under poor visibility or partial camera obstruction.
Benefits
- Improved AI Precision: Accurately detected subtle procedural deviations
- Behavioral Insights: Provided detailed analytics on employee performance and interactions
- Animal Welfare: Reduced stress and potential injury to cows
- Operational Efficiency: Standardized timing and streamlined routines across shifts
Conclusion
Summary
Structured human-in-the-loop video annotation enabled AI to act as a vigilant observer on the dairy floor, spotting mistakes, protecting animals, and empowering managers with data-driven insights.
Future Plans
Expand AI monitoring to feeding, herd movement tracking, and early detection of cattle health issues using the same annotation and analytics workflow.
Call to Action
Agri-tech companies and dairy operations can adopt structured video annotation workflows to improve labor efficiency, animal welfare, and operational reliability. Partnering with expert teams accelerates AI trust, quality control, and farm performance.