Multi-sensor cow monitoring

Producing high-quality food with a low ecological footprint and high animal well-being is one of the greatest challenges of modern livestock production systems. In order to fulfil these requirements, farmers invest more into their properties, resulting in high-value farms and an increasing necessity to guard, track and monitor all assets with the help of innovations. Those technologies need to seamlessly and proactively integrate to turn the industry into a smart and sustainable one. While the number of connected devices continues to rise simultaneously with the growing demands on the agri-food sector, particularly precision livestock farming requires reliable, affordable, low-power, wide-range network technologies and smart sensors (LoRa and NB-IoT). As those IoT applications play an important role in this use case, leveraging their key characteristics is crucial. The system is thus made up of a small rumen bolus, monitoring various physiological data (temperature, rumen and body activity, pH level), and a cloud-based server application to provide accurate information for daily operations. At the same time, involving multiple types of farms and connected supply chain stakeholders across different regions helps to further develop and deploy the latest innovations required to perform efficient and sustainable livestock farming and animal breeding.

Specific goals

  • Increase quality analogous to yield, prodictivity, production and reproduction rates;
  • Analyse needs of dairy and beef farmers;
  • Decrease the occurrence of animal health problems (heat, stress, rumen acidosis; milk fever, etc.), the number of veterinary interventions and antibiotics or hormone treatments;
  • Improve farmers’ work-life balance;
  • Accurate indoor and outdoor positioning through NB-IoT or LoRa geolocation;
  • Provide standard APIs for third party system integration;
  • Improve animal welfare by understanding cattle behaviour, rumen contraction detection and animal activity.

Expected results

  • Cattle monitoring time -10%
  • Productivity and yield increase
  • Increased animal health and welfare
  • Accurate heat detection and calving alert
  • System operation life >10 years
  • No-SQL and SQl based database for multimillion data storage and management
  • Data processing algorithms, Machine Learning and Big Data analysis for prediction, interpretation and pattern recognition

Source: iof2020.eu

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