We succesfully completed SMART4ALL KTE
What is SMART4ALL?
SMART4ALL is a group of 25 highly competent partners from 16 countries in South, Eastern, and Central Europe, funded by the EU program Horizon 2020, under the Smart Anything Everywhere initiative, for a period of four years, starting on the 1st of January, 2020.
The purpose of SMART4ALL is to accelerate digital transformation and increase digital skills in Europe by combining under a common vision different cultures, policies, and geographical areas in the domains of digitized environment, digitized agriculture, digitized transport, and digitized anything.
How does SMART4ALL operate?
SMART4ALL Provides total funding of 2,2 Mio Euros via 9 open calls and it will support 88 cross-border pathfinder application experiments from European consortia.
Each experiment will get funding up to €80,000 and it will be supported with novel coaching services from world-lead experts in ethics, technology, funding, and business development.
What is KTE (Knowledge Transfer Experiment)?
A novel type of experiment allowing smaller projects, or less mature ideas to be presented, and tested and thus potentially find the fertile ground to grow and reveal their product potential. KTEs act as internships/traineeships, apprenticeships, and short-term training programs for unemployed people for vacant digital jobs.
The duration of each KTE is 3 months and it provides up to 8,000€ to cover cost of the experiment.
MyGrowe – Growing Olives With Efficient Use Of Environmental Data
Olives are famous for thriving in a Mediterranean climate. They need a long, hot summer and a cool winter. Traditionally, olive groves are located in areas where water is scarce and needs to be delivered by trucks. Also efficient fertilizing is extremely important for healthy and firm fruit to produce oil of high organoleptic qualities and nutritive content. This environment requires a solution that will enable the use of resources in the most efficient way. Animus, an AppsForce solution that is able to locally calculate detailed environmental conditions and create personalized advice to farmers for optimal crop maintenance, has been successfully piloted in the Netherlands. Animus hardware and software technology can be used to help farmers in the Split-Dalmatia region maximize their olive yield. Animus technology helps in analyzing data and providing instant, personalized advice to achieve those results as well as reduce production costs and increase sustainability.
myGrowe is a solution that offers olive farm management and provides farmers with assistance in olive growing.
myGrowe offers management of multiple farms and fields from one place.
myGrowe offers current and predictive meteorological data.
myGrowe offers satellite feed-generated NDVI for each field.
NDVI (Normalized Difference Vegetation Index) is a widely used remote sensing index that measures the greenness of vegetation. NDVI is commonly used to monitor the health of crops and vegetation, detect changes in vegetation cover, and map land use and land cover. NDVI values can be used to identify areas of healthy vegetation, stressed vegetation, and bare soil or water. NDVI values can also be used to detect changes in vegetation over time, such as changes in growth or changes in land use.
myGrowe provides feed from various agricultural and other types of sensors.
Combining all data sources myGrowe provides farmers with a birdseye view of the situation on all the farms and groves.
Using all the data from these 3 sources myGrow AI can help olive farmers: Generate recommended actions to optimize irrigation, fertilization, and other farming practices, reducing costs and increasing yields. AI-powered predictive models can be used to forecast crop yields, weather patterns, and other trends, which can help farmers make more informed decisions. AI-controlled drones, robots, and other machines can be used to automate certain tasks such as pruning, harvesting, fertilization, and irrigation, which can improve efficiency and reduce labor costs.
myGrowe SMART4ALL presentation
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