Implementation of Artificial Intelligence in Intelligent Agricultural Systems for Agrotechnological Transformation for Daily Life

Ramdhoani; I Made Suryana

Authors

Ramdhoani Agrotechnology Study Program, Mahasaraswati University Denpasar, Indonesia, Indonesia Author
I Made Suryana Agrotechnology Study Program, Mahasaraswati University, Denpasar, Indonesia, Indonesia Author

Keywords:

Artificial Intelligence, Precision Agriculture, Smart Farming, IoT Sensors, Crop Disease Detection

Abstract

The development of artificial intelligence (AI) technology has brought a significant transformation in the agrotechnology sector, transforming conventional agricultural practices into efficient and sustainable smart farming systems. This research aims to examine the implementation of AI in agrotechnology for farmers' daily life applications. The systematic literature review method was used by analyzing 170 scientific publications indexed by Scopus for the 2022-2025 period. The results of the study show that AI has been implemented in various aspects of agrotechnology including: (1) computer vision-based plant disease detection system with an accuracy of up to 98%, (2) an integrated IoT platform for real-time monitoring of land and plant conditions, (3) a machine learning-based recommendation system for irrigation and fertilization management, (4) UAV technology with deep learning for land mapping and scouting, and (5) digital twin for simulation and optimization of production systems. The implementation of federated learning enables collaboration between farmers in the development of models without compromising data privacy. In conclusion, AI provides practical and affordable solutions to improve productivity, resource efficiency, and sustainability of agriculture in daily life. The implications of this study provide guidance for farmers, practitioners, and academics in adopting AI technology for the transformation of agrotechnology towards smart and sustainable agriculture

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