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Smart Dairy Farming

Beyond smart —
the future of dairying built by AI

Core Tasks

Core Tasks of the Smart Dairy Complex

Smart-dairy infographic showing cow, barn, milking, and environmental data flowing into a big-data platform

01

Big-Data Collection

Building a data collection and sharing platform for comprehensive management and use of ICT data

Illustration of a cow wearing smart sensors and a productivity-growth graph

02

Higher Productivity

Establishing data-driven decision models (SOPs) for husbandry and breeding using ICT data

A cycle diagram linking health, breeding, feed, and productivity icons for longer productive life

03

Longer Productive Life

Expanding the use of biometric ICT data — yield, activity, rumination — and developing AI models

Big-Data Collection

From individual breeding, biometric, and veterinary records to milking data, husbandry costs, and pedigree/genomic evaluation, data spanning a cow's entire life cycle is gathered on a single platform. By integrating and standardizing once-scattered husbandry and management information, NatureFarm lays the foundation for data-driven precision management and scientific decision-making.

A diagram of dairy big-data collection items centered on the cow: insemination records, breeding records, calf info, biometric info, veterinary records, milking data, testing results, feeding, husbandry costs, herd management, shipment records, pedigree, genomic evaluation, and body weight/condition (BCS).

Complex Control Center

An integrated monitoring space where data collected from the barns, milking parlor, and environmental control systems is gathered in real time. Herd size and temperature/humidity per barn, milking-yield trends, and even individual activity and rumination can be checked on one screen — detecting anomalies early and supporting fast, data-driven decisions.

The smart dairy complex control system screen, monitoring barn CCTV, herd size/temperature/humidity/THI/ETI indicators per barn, herd size and output by breed, and daily milking-yield trends on one screen.

Equipment

ICT Equipment in Operation

BouMatic rotary milking machine: cows ride on circular stalls that rotate during milking.

Rotary Parlor Milking Machine

NatureFarm's 60-point rotary parlor is Korea's largest milking facility, able to milk up to 60 cows at once and up to 350 cows per hour.

During milking, it automatically collects and analyzes a range of data in real time — individual milk yield, milking time, conductivity, and cluster fall-off counts — to manage output.

The collected data links to the milking control system to quickly identify abnormal cows, serving as a core smart-dairy system that supports data-driven precision breeding, health care, and raw-milk quality improvement.

A heat-detection sensor collar worn around a cow's neck.

Heat Detector

Every cow wears an individual activity-monitoring system that collects and analyzes behavioral data around the clock.

Biometric signs that appear during estrus — increased activity, changes in rumination, and reduced rest — are analyzed with AI to detect heat early, so insemination can be done at the right time.

This lets farms manage breeding more accurately and efficiently than the old visual-observation method, improving breeding performance.

A screen measuring a cow's Body Condition Score (BCS) via 3D scan.

AI-Based BCS Measurement System

NatureFarm operates an AI image-analysis-based BCS (Body Condition Score) system to scientifically manage each cow's nutritional status and body-shape changes.

A 3D camera mounted on the milking machine captures body shape, and AI analyzes each cow's BCS in real time.

BCS data is analyzed together with other smart-livestock data — milk yield, rumination time, activity, and feed intake — for use in nutrition and breeding management, disease prevention, and tailored husbandry.

A milking control screen showing the rotary stall sequence board, parlor CCTV, and a thermal camera together.

AI Milking Control System

NatureFarm developed a milking control system that links the rotary parlor with AI image analysis, managing the entire milking process in real time — the status of all 60 stalls and milking progress by barn.

In particular, a "liner fall-off detection AI model" detects in real time when a liner detaches before milking is complete, reducing mastitis risk from incomplete milking and improving both cow health and raw-milk quality.

A cylindrical feed-pushing robot driving along the barn aisle, pushing and tidying feed.

AI-Based Feed-Pushing Robot

The feed-pushing robot drives autonomously along the barn's feed lane, automatically pushing feed that cows have nudged outward back within reach.

NatureFarm developed an AI feed-level analysis model to monitor the feed lane in real time. When AI determines that feed needs tidying, it automatically calls the robot to work at the optimal time.

A quadruped robot dog driving autonomously along the barn aisle, monitoring cows.

Robot Dog

The AI robot dog autonomously patrols all five barns, analyzing cows' health and behavior and monitoring barn conditions such as temperature and humidity and feed levels in real time.
Through R&D, it will evolve into a physical-AI platform that also performs tasks like cleaning water troughs and herding cows at milking time, setting a new standard for smart dairying.

A tower-type smart chiller: a large cylindrical raw-milk cooling and storage tank beside the smart machine room.

Smart Chiller

The tower-type smart chiller combines 34 tons of raw-milk storage capacity with rapid cooling, smart monitoring, and automatic cleaning — a core facility for maintaining raw-milk quality and safety.
With this advanced cooling system, NatureFarm systematically manages quality across the entire process from milking to storage and shipment, supplying fresh, safe raw milk to consumers.

Large HVLS circulation fans installed along an open barn ceiling, spinning in a row to ventilate the barn.

Smart Barn Environment Management

NatureFarm has built an environmental monitoring system that measures temperature, humidity, CO₂, NH₃, and airflow inside the barns in real time, managing the cows' environment around the clock.

Especially in hot seasons, it automatically runs ventilation fans and misters in response to temperature and humidity changes to lower the perceived temperature and minimize heat stress — a smart environmental-control system that minimizes summer drops in milk yield.

Research & Development

Participation in Smart-Livestock R&D

Based on high-quality data collected from 1,000 cows, NatureFarm works with leading Korean universities to develop the latest technologies for higher dairy productivity, through research projects under the Smart Farm Multi-Ministry Package Innovation Technology Development Program managed by the Smart Farm R&D Foundation.

A diagram of smart-dairy research partnerships with Chungnam National University, Chung-Ang University, and the National Institute of Animal Science. CNU handles data-driven precision husbandry and integrated ICT control research; CAU handles AI model development and smart-technology validation; NIAS handles livestock-data standardization and productivity research — aiming for industry-academia-research collaboration, smart-dairy innovation, sustainable dairying, and stronger K-dairy competitiveness.

2019 – 2022

Participation in ICT Data-Collection Device Development

  • Participation in developing data-collection devices for major ICT equipment deployed in Korea

Lead · Korea Dairy Committee

2024 – 2025

Field Validation of Bio-ICT Intelligent Husbandry Solutions

  • Building a database linking economic traits (lactation ability) and genetic information
  • Developing an individual milk-yield prediction model based on genetic information

Lead · Chungnam National University

2025 – 2027IN PROGRESS

Building and Validating an Unmanned Autonomous K-FARM Demo Barn

  • Developing an ICT-based integrated control solution for precision management of large farms
  • Developing an unmanned model for cow and barn observation using a robot dog
  • Field validation of a genetics-based individual milk-yield analysis and production-management solution
  • Field validation of a 3D-mesh-based automatic BCS measurement AI model

Lead · Chungnam National University

2025 – 2027IN PROGRESS

Commercializing a Generative-AI Smart Cattle Management System

  • Collecting cattle ICT data and husbandry records for generative-AI training, and developing an ontology
  • MCP-based conversational AI service — disease diagnosis, breeding management, nutrition consulting
  • Field validation of a multi-view camera-based individual-recognition AI model
  • Developing a Holstein Re-ID model that identifies cows without additional training

Lead · Chung-Ang University