Agriculture is vital to economic growth, contributing 4% to global GDP and over 25% in some developing countries. Most farming practices are outdated, necessitating modernization for improved efficiency. Advances in deep learning, multi- and hyperspectral imagery (MHSI), UAVs, and agri-bots have revolutionized precision agriculture (PA). Computer vision (CV) techniques, enhanced by MHSI, have automated tasks like crop classification, disease monitoring, and biomass estimation. UAVs assist in field scouting, disease detection, and precision spraying, while agri-bots with IoT sensors facilitate real-time data-driven actions such as fruit picking and weed control. This chapter reviews the latest developments in CV, MHSI, UAVs, and agri-bots, examining current methods, challenges, datasets, and future applications in precision agriculture.
Authors: Muhammad Jawad Bashir, Rafia Mumtaz
DOI: https://doi.org/10.4018/979-8-3693-6255-6.ch006
Publish Year: 2025
