Application of Bio and Nature-Inspired Algorithms in Agricultural Engineering

Abstract The article reviewed the four major Bioinspired intelligent algorithms for agricultural applications, namely ecological, swarm-intelligence-based, ecology-based, and multi-objective algorithms. key emphasis was placed on variants of swarm intelligence algorithms, artificial bee colony (ABC), genetic algorithm, flower pollination algorithm (FPA), particle swarm, ant colony, firefly fish Krill herd because they had been widely employed in sector. There a broad consensus among scholars that certain BIAs' were more effective than others. For example, Ant Colony Optimization Algorithm best suited farm machinery path optimization pest detection, other applications. On contrary, useful determining plant evapotranspiration rates, which predicted water requirements irrigation process. Despite promising adoption hyper-heuristic agriculture remained low. No universal could perform multiple functions farms; different designed to specific functions. Secondary concerns relate data integrity cyber security, considering history cyber-attacks smart farms. concerns, benefits associated with BIAs outweighed risks. average, farmers can save 647–1866 L fuel is equivalent US$734-851, use GPS-guided systems. accuracy mitigated risk errors applying pesticides, fertilizers, irrigation, crop monitoring better yields.