AIMHiGH as an FF4EuroHPC success story
The AIMHiGH project is an experiment that was conducted under the FF4EuroHPC initiative to improve the efficiency and performance of high-performance computing in Europe. The main goal of the engagement was to understand their business challenges and to present an IoT-based poultry farm management solution, supported by a set of sensors for environmental monitoring. The use of HPC and deep learning AI were used to create prediction models that can be deployed on edge devices equipped with camera sensors for use in IoT/AI solutions in the poultry sector.
Several organizations collaborated on the AIMHiGH project. The end-users were the Radinović Company and Meso-Promet Franca, while the University of Donja Gorica, which is part of the NCC Montenegro, provided domain expertise. The ISV for the project was DunavNET, and DigitalSmart provided HPC and AI expertise.
The AIMHiGH project resulted in a new digital farming solution that combines cameras, edge computing, and an IoT platform. The system helped to reduce manual labor costs and chicken mortality rates by 10% and detect disease or abnormalities quicker than before. The technology developed in this project has become a part of the poultryNET platform offering, and there is an opportunity to sell such components to third-party vendors active in the market of smart agriculture solutions.
Overall, the AIMHiGH project demonstrated the potential of artificial intelligence, machine learning, and high-performance computing to develop innovative solutions for the agriculture industry. The project also showcased the benefits of collaboration among different organizations with expertise in various fields.
We invite you to view the video presentation highlighting the AIMHiGH project as one of the success stories of FF4EuroHPC.
Read More
New publication on Botrytis cinerea forecast model
A new paper on Botrytis cinerea forecast modelling has been published in the Journal of Networking and Network Applications (2022). The paper is titled, “Qualitative parameter analysis for Botrytis cinerea forecast modelling using IoT sensor networks’. Botrytis cinerea is a fungus that affects many plant species but attacks wine grapes frequently. The research leading to these results received funding from the European Union’s Horizon 2020 — The EU Framework Programme for Research and Innovation 2014–2020, under DEMETER.
The authors of the publication are Spasenija Gajinov, Tomo Popović, Dejan Drajić, Nenad Gligorić and Srđan Krčo.
Abstract: This paper provides results of an evaluation of a fungal disease Botrytis cinerea forecast model (Model for Botrytis cinerea appearing) in vineyards for qualitative analysis of parameters that affect the development of the disease by using data from a network of connected sensors (air temperature and relative humidity, rain precipitation, and leaf wetness). The fungal disease model used by agronomists was digitalized and integrated into agroNET, a decision support tool, helping farmers to decide when to apply chemical treatments and which chemicals to use, to ensure the best growing conditions and suppress the growth of Botrytis cinerea. The temperature and humidity contexts are used to detect the risk of the disease occurrence. In this study, the impact of the humidity conditions (relative humidity, rain precipitation, and leaf wetness) is evaluated by assessing how different humidity parameters correlate with the accuracy of the Botrytis cinerea fungi forecast. Each observed parameter has its own threshold that triggers the second step of the disease modelling-risk index based on the temperature. The research showed that for relative humidity, rain precipitation, and leaf wetness measurements, a low-cost relative humidity sensor can detect, on average, 14.61% of cases, a leaf wetness sensor an additional 3.99% of risk cases, and finally, a precipitation sensor can detect an additional 0.59% of risk cases (in the observed period the risk was detected in 19.19% (14.61%+3.99%0.59%) of the time), which gives a guide to farmers how to consider cost effective implementation of sensors to achieve good performance. The use of the proposed model reduced the use of pesticides up to 20%
The full paper is available DOI:10.33969/J-NaNA.2022.020305
Read MorepoultryNET case study video presentation
poultryNET is a cloud-based solution for the digital transformation of poultry farms. It provides real-time observations of the parameters of interest and digitized domain expertise enabling farmers to manage all steps in the broiler production while reducing negative environmental impact and respecting animal wellbeing.
The main features provide complete 24/7 insight into poultry barns from monitoring environmental parameters, daily weight and consumed feed and water, to a biosafety guide, costs/revenue calculator and digital assistant in problem solving. Using the poultryNET the environmental conditions, as well as food and water consumption and prepared feed mixture, could be tailored to specific animal needs and production goals. Increased of energy, optimized food and water consumption and better meat quality are the main benefits.
The poultryNET solution is applicable for broiler farms, parental flocks and laying hens.
Case study
Four years ago, we started cooperation with Agroprodukt Šinković company by implementing our digital farming platform for poultry production on their farm. The collaboration continued within the DEMETER project by expanding solutions and setting a basis for a transparent supply chain.
The Agroprodukt Šinković is a Serbian company focused on raising laying hens, parental flocks and day-old chicks for over 20 years. Their annual production is more than 10 million day-old chickens.
The video briefly presents the poultryNET case study – with case study customer Agroproduct Šinković Farm.
Read MoreDEMETER Open Call 2
The Horizon 2020 project, DEMETER, has announced the launch of its 2nd Open Call, DEPLOY, with a total budget of €740,000 available. DEMETER aims to lead the digital transformation of Europe’s agri-food sector through the rapid adoption of advanced Internet of Things (IoT) technologies, data science and smart farming ensuring the industry’s long-term viability and sustainability.
DEPLOY, the second Open Call in DEMETER, aims to increase the outreach of the DEMETER value proposition by funding small consortia of 2-3 partners for the deployment of new, high-value pilots in the agri-food sector. These pilots will focus on employing DEMETER methodologies and technologies, addressing clear farmers’ needs, with a particular focus on EU geographic regions not represented within DEMETER pilots. This will expand the technological and/or business coverage of the project, towards digitalising and boosting the European agrobusiness sector. European countries not covered by DEMETER pilots are Austria, Bulgaria, Croatia, Cyprus, Denmark, Estonia, France, Hungary, Lithuania, Luxembourg, Malta, Netherlands, Slovakia and Sweden.
Twenty pilot projects are currently running in DEMETER to demonstrate and evaluate how innovations and extended capabilities benefit from the interoperability mechanisms. A wide spectrum of sub-sectors: arable crops, irrigated crops, fruit production and livestock (poultry, dairy, animal welfare) are covered. These pilots can be used as an example for potential applicants to develop similar or different pilots to be funded under DEPLOY.
The new pilots to be funded under the DEMETER Open Call #2 – DEPLOY must address specific farmers’ needs and fit into one or more DEMETER challenges and objectives.
Open Call #2 – DEPLOY will fund consortia composed of two or three:
- micro, small, and medium-sized enterprises (SMEs),
- secondary and higher education establishments, research institutes and other not-for profit research entities.
The Open Call closes on the 16th February 2022 at (17.00 CET).
More information on DEPLOY and how to apply is available at www.h2020-demeter.eu/open-call-deploy.
Applications can be made via the F6S platform at www.f6s.com/demeter-open-call-2-deploy/apply
Read MorePigstEYE solution
Within the first ATLAS Demo Day, our product manager Senka Gajinov, presented the PigstEYE, our solution for livestock farm management, exploring the topic of Behavioral Analysis and Management of Livestock.
The first ATLAS Demo Day brought together speakers from the agricultural sector. They explored the benefits of data-driven agriculture using the ATLAS Interoperability Network within a multitude of pilot studies. The event cast light on agricultural challenges and opportunities to overcome these through digital agriculture. It Is organized under the title: “Business Opportunities for Innovative Digital Data-Driven Agriculture”.
PigstEYE is the turnkey IoT/AI solution designed to improve animal welfare on pig farms and improve the overall farm performance. The solution provides pigs’ recognition, calculation of their size, and tracking of their movement. The work done in the PigstEye project will be used as the basis for the creation of a line of animal wellbeing features and features enabling optimization of another process in the value chain. PigstEYE is supported by H2020 ATLAS Project.
The Demo Day was held on November 24, as a virtual event. In case you missed it, you can watch the presentation and learn more about the PigstEYE solution and our involvement in the ATLAS H2020 project here.
Read More