<abstract xmlns="http://www.w3.org/1999/xhtml">

<p>The only technology that is currently mature enough to help us quickly recover losses in agriculture is digital technology. Digital transformation is increasingly referred to as the fourth industrial revolution, aimed at merging the real world with the virtual one, bringing advantages even in traditional sectors such as agriculture. Artificial intelligence (AI) algorithms are used to analyze large amounts of data collected from various sources in the field, as well as from farmers or beneficiaries of European funds for agricultural sector development. Specifically, they can analyze information gathered from soil sensors, weather stations, satellite images, or European funding applications, among others. This analysis provides farmers with valuable information to make informed decisions regarding seed selection, optimal timing, planting techniques, and resource allocation decisions. At the same time, AI-powered systems can learn from historical data and identify patterns, enabling more accurate predictions and recommendations. Machine learning algorithms can anticipate managerial decisions, detect potential problems, and suggest appropriate interventions to improve financial performance for the successful implementation of projects funded by European funds.</p>
</abstract>

The only technology that is currently mature enough to help us quickly recover losses in agriculture is digital technology. Digital transformation is increasingly referred to as the fourth industrial revolution, aimed at merging the real world with the virtual one, bringing advantages even in traditional sectors such as agriculture. Artificial intelligence (AI) algorithms are used to analyze large amounts of data collected from various sources in the field, as well as from farmers or beneficiaries of European funds for agricultural sector development. Specifically, they can analyze information gathered from soil sensors, weather stations, satellite images, or European funding applications, among others. This analysis provides farmers with valuable information to make informed decisions regarding seed selection, optimal timing, planting techniques, and resource allocation decisions. At the same time, AI-powered systems can learn from historical data and identify patterns, enabling more accurate predictions and recommendations. Machine learning algorithms can anticipate managerial decisions, detect potential problems, and suggest appropriate interventions to improve financial performance for the successful implementation of projects funded by European funds.

Optimization of Financial Flows with the Help of Artificial Intelligence in Public Institutions

The Bucharest University of Economic Studies

Proceedings of the International Conference on Business Excellence

This work is licensed under the Creative Commons Attribution 4.0 International License.

The only technology that is currently mature enough to help us quickly recover losses in agriculture is digital technology. Digital transformation is...

Optimization of Financial Flows with the Help of Artificial Intelligence in Public Institutions

Online veröffentlicht: 03. Juli 2024

Seitenbereich: 1857 - 1967

DOI: https://doi.org/10.2478/picbe-2024-0156

Schlüsselwörter
AI, agriculture, application, financials, machine learning

© 2024 Daniel Ifrim et al., published by Sciendo

This work is licensed under the Creative Commons Attribution 4.0 International License.

Optimization of Financial Flows with the Help of Artificial Intelligence in Public Institutions

Online veröffentlicht: 03. Juli 2024

Seitenbereich: 1857 - 1967

DOI: https://doi.org/10.2478/picbe-2024-0156

SchlüsselwörterAI, agriculture, application, financials, machine learning

© 2024 Daniel Ifrim et al., published by Sciendo

This work is licensed under the Creative Commons Attribution 4.0 International License.

Schlüsselwörter
AI, agriculture, application, financials, machine learning