Technological Evolution and System Integration of Intelligent Agricultural Spraying Equipment: A Review

Spray application in spatially heterogeneous three-dimensional crop canopies is constrained by inadequate within-canopy deposition, off-target losses, and poor matching between operating parameters and target structure. This review synthesizes the technological evolution of intelligent agricultural spraying equipment from the perspectives of airflow-assisted transport, demand-based dose allocation, target sensing, actuation control, system integration, and performance evaluation. Air-assisted spraying has expanded transport regulation from hydraulic output alone to coordinated airflow–droplet–canopy interactions. Variable-rate and prescription approaches subsequently linked dose allocation to measurable spatial differences in canopy structure and target distribution. Ultrasonic sensing, light detection and ranging (LiDAR), red–green–blue depth (RGB-D) imaging, machine vision, and multimodal perception have increased the spatial and semantic resolution of target representation. Pulse width modulation (PWM), fuzzy control, and data-driven methods have improved nozzle-level actuation and compensation for nonlinear hydraulic dynamics. However, closed-loop actuator or navigation should not be conflated with closed-loop control of application quality: deposition, drift, and biological efficacy are still evaluated mainly after operation and are rarely used as real-time feedback variables. Current limitations arise less from the absence of individual sensing or control technologies than from weak coupling among canopy representation, spray transport, multivariable actuation, and performance feedback. Future development should prioritize transferable multiscale models and explicit coordination of liquid flow, airflow, droplet size, speed, and equipment state. Scenario-specific architectures must connect sensing, decision-making, actuation, and evaluation without sacrificing field robustness.