Use Case Update: Poultry Chain management

By Stanislas Demeestere -

This use case aims to optimise poultry chain management in all its aspects. Broken down into three distinct levels, the team has made strides in the development of the 'Smart Farm Assistant', with which the in-farm operations are made more efficient. The first data coming out of the project are promising, but continued developments in sensors and other technology create the needs for the processing of data to catch up.

Positive results

Poultry Chain Management, bases itself around three critical points which define the efficiency and the product quality of the poultry production chain. These three stages are the farm level, logistics, and the processing plant level. All three share the goal of optimising the different aspects of the poultry production chain, each in a different way.

The added efficiency of all three stages under the use case, has provided with a 20% increase of class A birds. Average weight went up by 10%, feed waste down by another 10%, and the use of antibiotics went down a promising 15%. however good these results are, and however much they prove the validity of IoT-based solutions for agricultural challenges, more can be done, and one major such stride has recently been taken in the farm operations. 

Optimising farm operations 

The Smart Farm Assistant, developed under this use case, deals with one of the three areas in which the use case wants to enhance the efficiency and product quality of the poultry production chain: the farm level. Smart Farm Assistant uses a Poultry Growing Early Warning System, which has been released in one farm, and is working steadily in all other farms. In improving this system, environmental sensors have been changed to better transport monitoring and to avoid the loss of data due to bad internet or remote connectivity. The collection of data is then shared with the entire chain, including farm data, the loading process, transport, and meat quaity. This aggregate of information is consequently analysed, and indicators are extracted for each phase.

One example of these new and improved environmental sensors, is the move away from static scales, towards the use of dynamic scales. Although it seems like a small thing, these new scales are wireless, battery-powered and can easily be moved around the farm. This increases efficiency quite a bit, and contributes to reaching the end goals of the use case.

With all this new and improved data flooding in, there are new challenges in receiving and processing data in an organised way, which allows for easier data analysis.

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