Embracing Opportunities of Livestock Big Data Integration with Privacy Constraints Livestock Big Data & Privacy Franz Papst (TU Graz / CSH Vienna) 5 smaXtec, Austria 1 / 13 Igor Franz Papst 12 Olga Saukh 12 Kay Römer 1 Florian Grandl 4 Jakovljevic 5 Franz Steininger 3 Martin Mayerhofer 3 Jürgen Duda 4 Christa Egger-Danner 3 1 TU Graz Institute of Technical Informatics, Austria 2 Complexity Science Hub Vienna, Austria 3 ZuchtData EDV-Dienstleistungen GmbH, Austria 4 LKV Bayern, Germany
Franz Papst (TU Graz / CSH Vienna) D4Dairy Livestock Big Data & Privacy 2 / 13 • Interdisciplinary research project for digitalisation in dairying • Provide digital support to dairy management • The four Ds stand for ▶ Digitalisation ▶ Data Integration ▶ Detection ▶ Decision Support • 44 project partners ▶ 31 industry partners ▶ 13 scientifjc partners • https://d4dairy.com/en/
D4Dairy Franz Papst (TU Graz / CSH Vienna) Livestock Big Data & Privacy 3 / 13
Introduction dairying Franz Papst (TU Graz / CSH Vienna) Livestock Big Data & Privacy 4 / 13 • IoT has a big impact on agriculture • Cheap sensors enable a paradigm shift in farming ▶ monitoring fjelds ▶ monitoring livestock ▶ … • Potential use-cases for IoT in ▶ activity ▶ body temperature ▶ feed intake ▶ milk yield
http://www.molevalleyfarmers.com/mvf/info/general/smaxtec-animal-care-system No Legal Basis Valuable cattle data remains in silos. Franz Papst (TU Graz / CSH Vienna) Livestock Big Data & Privacy 5 / 13 • Farm data is in general not afgected by privacy regulations ▶ it should be more viewed as farmers’ trade secrets • Same applies for sensor companies • Communities push standardisation ▶ e.g. , ICAR
Analysing data is key, but it has to be done with privacy constraints. Difgerent Perspectives Franz Papst (TU Graz / CSH Vienna) Livestock Big Data & Privacy 6 / 13 • Farmers ▶ have difgerent sensors on their farms ▶ which come with difgerent applications ▶ want a unifjed view of what’s happening on the farm • Sensor Companies ▶ want to improve the utility of their products ▶ hesitant to share their proprietary data • Veterinarians • Regulatory Agencies • Federal Agencies • Cattle Breed Associations
Our Contributions Franz Papst (TU Graz / CSH Vienna) Livestock Big Data & Privacy 7 / 13 • Survey of existing systems • Propose a privacy-preserving data integration architecture • Give examples of potential use cases
Existing Systems Overview decentralised centralised System Barto 2018 centralised ADA 2018 ODiL 365FarmData not yet decentralised HARA 2019 decentralised Existing systems exchange data, but do not use it further. Franz Papst (TU Graz / CSH Vienna) Livestock Big Data & Privacy 2013 8 / 13 centralised centralised NCDX Analytics OFIS Privacy Data Storage Architecture 2015 2015 Live since JoinData 2018 centralised ✗ ✓ ✗ ✓ ✗ ✗ ✓ ✓ ✗ ✓ ✓ ✗ ✓ ✓ ✗ ✗ ✓ ✗ ✗ ✓ ✗ ✓ ✓ ✗
Our Architecture Data integration on a global scale is required. Livestock Big Data & Privacy Franz Papst (TU Graz / CSH Vienna) 9 / 13 Global Scope Federal Data Exchange Agency Sensor Local Scope Company F A R M S
Example https://www.gea.com/de/products/ gea-free-stall-feeder-wic.jsp https://www.lely.com/gb/solutions/milking/taurus/ Franz Papst (TU Graz / CSH Vienna) Livestock Big Data & Privacy 10 / 13 • Investigate relation between feed intake and milk yield ▶ from difgerent farms ▶ with difgerent equipment ▶ without disclosing those values
Privacy-preserving Data Analytics https://aircloak.com/data-anonymization-use-cases/ All these methods allow data analysis, while not exposing private data. Franz Papst (TU Graz / CSH Vienna) Livestock Big Data & Privacy 11 / 13 • Secure multi-party computing • Federated learning • Data anonymisation and obfuscation • Synthetic data generation
Applications and Benefjts for the Farmers https://www.allflex.global/livestock-monitoring-and-intelligence Franz Papst (TU Graz / CSH Vienna) Livestock Big Data & Privacy 12 / 13 • Predicting missing and delayed data • Anomaly and event detection • Monitoring cattle health and welfare • Autocomplete and verifjcation of manual input
Conclusion privacy-preserving manner Franz Papst (TU Graz / CSH Vienna) Livestock Big Data & Privacy 13 / 13 • IoT has big potential for the dairying industry • Privacy concerns are currently hindering potential use-cases • We propose an architecture, which is able to analyse data in a • This system enables better utilisation of data
Recommend
More recommend
