Cloud app helps dairy farmers monitor the cows’ wellbeing

Research and innovation are central to DeLaval and there is a strong focus on digital services, with the aim of helping dairy farmers improve decision making, increase efficiency, and strengthen the focus on animal welfare.

The dairy farm of today can be seen as a high-tech hub in a company that is active 24/7, 365 days a year – where animal wellbeing and efficiency are two important building blocks in making the farm profitable and productive.

Farms with DeLaval equipment now have both hardware and digital solutions, where cows are tagged with sensors that gather valuable data. Data analysis results in better decision support for operating the farm at maximum capacity and a strong focus on animal wellbeing.

DeLaval’s core operations involve creating milking equipment for dairy farmers. Building digital solutions and becoming even more of a service provider creates a different challenge in tech, organization, and culture.

With the goal of offering digital services in parallel with creation of the machines that DeLaval provides to its customers, a program was initiated in order to renew and create the next generation of information platform.

DeLaval needed a collaboration partner that could meet requirements on a high pace of productivity, scalable and flexible work, and a guaranteed fast time to market. Knowit was hired and was given the assignment to create the first application for the platform.

An agile team from Knowit with competence in cloud-based development, IoT, AWS, and Scrum developed a solution that aggregates all the data and compares them with other available data, producing data and analyses that are useful for the farmer in their daily work. DeLaval also has an in-house innovation team that builds algorithms for predictions based on the sensor data, using machine learning.

In the newly developed app, all cows are IoT-connected to AWS, where the data is organised and machine learning is used to produce reliable information and predictions. Methods that were used during development include: Node.JS, Python, Type Script, AWS Greengrass (IoT) MQTT, Lamda, Dynamo DB, and S3.

There is now a real-time solution in place, in the form of an application that helps the dairy farmer retain a focus on the cows’ wellbeing. The app informs the farmer if a cow is eating too much or too little, shows irregular behavior, or is getting sick.

The solution also helps predict when a cow is ready for insemination, which is a huge help to the farmer. Through such insights from the system, dairy farmers can decrease their veterinary costs and get valuable, actionable information that can contribute to improved milk production, increased efficiency and sustainability, and time savings.

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