CLIMATE CONTROL ▶▶▶
Combining sensors for better climate control
Outdated building standards, control systems and barn management approaches: Together they cause resource use within EU pig production to be suboptimal. That results in high emissions and losses. Now concern for welfare is rising, pig farmers struggle to maintain competitiveness. The project PigSys considers a whole system improvement.
BY BARBARA STURM, SHARVARI RAUT, PHIL KIRCHHOFER, SIMONE MÜLLER AND ABOZAR NASIRAHMADI*
P 100 5:50:00
90 80 70 60 50 40 30 20 10 0
igSys, an ERA-NET project, addresses issues of out- dated building standards, control systems and barn management by adopting a multidisciplinary, cross- scale, system-level approach to pig production. This
way, the project ensures that all aspects relevant to sustaina- ble, socially acceptable and economically viable pig produc- tion systems are adequately addressed. With partners from different European regions – and the inclusion of Germany,
Figure 1 - Scoring animal postures and activity levels using machine vision and deep learning techniques.
France and Denmark as three of the five biggest European pig producers – the project not only has geographical and climat- ic balance but also ensures its relevance across the EU. To this end, a comprehensive model of mass and energy flows and a decision support system, as well as novel building cli- mate-control systems, are being developed to underpin a sus- tainable improvement in overall performance. This will allow: 1. Improvement in the productivity, resilience and competi- tiveness of European animal production; 2. Improvement and better management of resources to re- duce waste and enhance the environmental sustainability of European animal production; and 3. Improvement of on-farm practices to enhance consumer acceptability and address societal challenges associated with animal welfare, product quality and safety, biodiversity and provision of ecosystem services.
Feeding time Visiting or activity time Standing 7:16:24
8:42:48 10:09:12 11:35:36 Time
Source: Sensors, August 2019 (
https://doi.org/10.3390/s19173738). 30 13:02:00 14:28:24 15:54:48
Monitoring behaviour and health Recent technological developments have expanded the possi- bilities of monitoring and assessing animal behaviour, health and welfare on large- and small-scale farms through machine vision, either three-dimensional (3D) or two-dimensional (2D), along with machine learning (e.g. deep learning) techniques. These techniques have a wide range of applications, flexibility, cost and efficiency. In the PigSys project, data from 2D video cameras were used to develop a machine learning–based, deep learning in particular, monitoring system. Image data from different commercial and research farms in different European countries (i.e. Germany, Sweden, Denmark and France) were used to train and validate the deep learning techniques. The developed models can con- tinuously monitor group and individual lying and standing postures as well as the activity of group-housed pigs in barns (see Figure 1). The developed models were transferred to a microcontroller (single board computer – Raspberry Pi – equipped with a cam- era) which allows the use of the developed system in different farming conditions. The models can score the behaviours in on- line (real-time) and offline (recorded video and image data) conditions. The scored data can be continuously saved in excel files. The results from the test phase of the developed deep learning models in different farming conditions (both weaning and fattening) show that the proposed model has flexibility
▶PIG PROGRESS | Volume 36, No. 9, 2020
Percentage of the postures
PHOTO: MARK PASVEER
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