IJFANS International Journal of Food and Nutritional Sciences

ISSN PRINT 2319 1775 Online 2320-7876

Enhancing Crop Yield Prediction Accuracy through UAV-Based Multispectral Imagery

Main Article Content

V Bhavani, A Roshini

Abstract

Unmanned Aerial Vehicles (UAVs), commonly referred to as drones, have emerged as disruptive technologies with broad applications across various domains. These remotely piloted aircraft, equipped with advanced sensors and imaging capabilities, offer unprecedented opportunities for data collection and analysis. This abstract provides an overview of the diverse applications of UAVs, ranging from precision agriculture and environmental monitoring to disaster response, infrastructure inspection, and scientific research. The versatility of UAVs is underscored in their ability to access hard-to-reach locations, providing valuable insights for decision-making processes in agriculture, conservation, and disaster management. The abstract also explores the evolving technologies associated with UAVs, including advancements in artificial intelligence, machine learning, and sensor integration, enhancing their autonomy and operational efficiency. As these technologies mature, UAVs are poised to play a pivotal role in shaping the future of various industries, prompting the need for responsible regulation and ethical considerations to ensure their safe and beneficial integration into society.

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