Λεπτομέρειες βιβλιογραφικής εγγραφής
| Τίτλος: |
Agriculture 4.0 and the role of education. |
| Συγγραφείς: |
Pogorelskaia, Ilsiiar, Várallyai, László |
| Πηγή: |
Journal of Agricultural Informatics / Agrárinformatika Folyóirat; 2020, Vol. 11 Issue 1, p45-51, 7p |
| Θεματικοί όροι: |
Blockchains, Information & communication technologies, Agriculture, Robot programming |
| Περίληψη: |
The fast development of information and communication technologies gave impetus to the emergence of a new turn in the revolutionary development of the Agriculture industry. The main goal of Agriculture 4.0 is to produce more and better with fewer tools (sensors), for which more tools and technologies already exist today. Use of robots and drones is being introduced in agriculture and various targeted software is being developed to process data. Deploying IoT devices in agricultural areas that can send us plant-related data remotely opens up a whole new opportunity for us in several areas. Agriculture, or the food industry in general, cannot be an exception when it comes to Agriculture 4.0. There are also some ideas and initiatives around the use of Blockchain technology. So, farmers extremely need to get ready to embrace the upcoming digital change and they have to increase or acquire new ICT skills and capabilities. Nowadays digital education makes it easier to acquire new knowledge and skills in ICT. Information and communication technologies tools open new potentials for on-the-job, individual workplace learning, using new methods and models of education such as personal learning clouds or set up personal learning environments. All of these helps to solve one of the main challenges - reducing existing skill gaps. [ABSTRACT FROM AUTHOR] |
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Copyright of Journal of Agricultural Informatics / Agrárinformatika Folyóirat is the property of Hungarian Association of Agricultural Informatics and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.) |
| Βάση Δεδομένων: |
Complementary Index |