Empowering sustainable farming practices with AI-enabled interactive visualization of hyperspectral imaging data

Abstract

In the context of sustainable applications, this research investigates using artificial intelligence (AI) in interactive visualization for hyperspectral pictures. Detailed spectrum data about the Earth's surface is provided through hyperspectral imaging, allowing for the monitoring and analyzing several phenomena about agriculture, land use, and environmental sustainability. However, processing, analyzing, and interpreting the massive data produced by hyperspectral sensors is challenging. AI methods and interactive visualization provide practical tools for deriving useful information from hyperspectral data and assisting in decision-making for environmentally friendly applications. This study examines the key elements of an interactive visualization framework powered by AI and emphasizes the advantages and implications for sustainable agricultural operations. This sector's difficulties and potential possibilities are also discussed, focusing on the need for data processing optimization, technology integration, user-friendly interfaces, and ethical issues. In general, interactive hyperspectral image visualization powered by AI shows potential for improving sustainability in agriculture and other related fields.

Keywords

• AI
• Interactive visualization
• Hyperspectral imaging
• Sustainable farming practices
• Agriculture
• Environmental monitoring