ALERT MESSAGE BASED ON ANIMAL DETECTION IN AGRICULTURE FIELD USING DEEP LEARNING

AbstractIn modern agricultural systems, the prevention ofanimal intrusion is paramount to averting substantialdamage and economic loss. This research introducesan artificial intelligence–driven animal detectionmechanism employing a bespoke YOLO (You OnlyLook Once) model to facilitate the real-timeidentification of diverse animal species. The system iscapable of analyzing video streams or static imagery,discerning the presence of specific fauna, andinitiating an automated auditory deterrent contingentupon the species identified. Through the integration ofadvanced deep learning techniques and automatedresponse protocols, the framework markedly enhancesagricultural security, diminishes the reliance onconstant human oversight, and constitutes anefficacious approach to mitigating wildlife-relatedthreats. The model has been trained on acomprehensive dataset encompassing a range ofanimal species commonly encountered in agriculturalvicinities, thereby ensuring a high degree of precisionand operational reliability.