HENCO2: Cloud based IT platform designed to improve poultry productivity and reduce greenhouse gas emissions Team of project Līga Paura Duration 2020 - 2022 Research focus 4. Development and adaptation of technologies for obtaining high-value agricultural and forest products, as well as in veterinary medicine Source of funding National grant Description of project The objective of this research is to analyse the existing smart poultry management systems that allow taking a decision for the most appropriate feeding process and the lowest level of CO2 and NH3 emission for every particular egg and broiler producer to enhance productivity, reduce disease, mortality and to take a care of the environ-ment.The following proposed tasks are defined:1) to analyse the typical data sources in poultry farms and factors affecting poultry productivity, 2) to analyse the research directions and technologies related to smart poultry man-agement systems, 3) to identify the necessary challenges of the smart platform implementation de-signed for improvement poultry productivity and reduction of GHG emissions. Results Bumanis, N., Kviesis, A., Paura, L., Arhipova, I., & Adjutovs, M. (2023). Hen Egg Production Forecasting: Capabilities of Machine Learning Models in Scenarios with Limited Data Sets. Applied Sciences, 13(13), 7607. Arhipova, I., Vitols, G., Paura, L., Jankovska, L. Smart Platform Designed to Improve Poultry Productivity and Reduce Greenhouse Gas Emissions (2022) Lecture Notes in Networks and Systems, 235, pp. 35-46. Būmanis, Arhipova, Paura, Vītols, Jankovska, Būmanis, Nikolajs, . . . Jankovska, Līga. (2022). Data conceptual model for smart poultry farm management system. 1877-0509. Procedia Computer Science. Vol. 200 : 3rd International Conference on Industry 4.0 and Smart Manufacturing; (2022), p. 517-526. Paura, L., Arhipova, I., Jankovska, L., Bumanis, N., Vitols, G., & Adjutovs, M. (2022). Evaluation and association of laying hen performance, environmental conditions and gas concentrations in barn housing system. Italian Journal of Animal Science, 21(1), 694-701.
