ARTIFICIAL INTELLIGENCE-BASED TECHNOLOGY FOR ACCELERATED TREE CULTIVATION FOR THE FURNITURE INDUSTRY

This article explores the potential of artificial intelligence (AI) technologies for optimizing the cultivation period of wood raw materials required by the furniture industry. An integrated technological model is proposed that focuses on selecting tree species, analyzing soil and climatic conditions, automating irrigation, remotely monitoring plant growth, and predicting wood quality. The study employs methods of scientific literature review and systematic synthesis of existing technologies. The results indicate that integrating AI, remote sensing, sensors, and data-driven management can improve resource-use efficiency, enable the early detection of problems in tree development, and facilitate the forecasting of wood volumes required for furniture manufacturing. The proposed approach can be adapted to local conditions and applied in regions of Uzbekistan where water resources are limited.