Plants respond and adapt to changes in their surroundings through various mechanisms,including chemical signals like volatile organic compounds and mechanical signals,producing acoustic signals. Advances in acoustic sensing technologies have increasinglyrevealed the potential for using sound-based methods to monitor and assess plant health.This work synthesizes the current state of the art in plant acoustics research, highlightinghow ultrasonic and audible signals emitted by plants can serve as valuable indicators ofphysiological status. It further explores data-processing methods, including machinelearning and signal analysis, that transform raw acoustic data into actionable insights. Thereview concludes by identifying key technical and conceptual challenges, including theneed for standardized monitoring protocols, robust sensor networks, and improvedinterpretations of acoustic signatures under varied environmental conditions.