To mitigate agricultural crop losses caused by wildlife and unauthorized intrusions, an interactive orchard intrusion detection system combining edge-level automation and human-in-the-loop control was developed. The system integrates an Arduino Mega 2560 microcontroller, a servo-mounted 180° scanning ultrasonic sensor, multi-modal deterrents, and an Internet Protocol camera for real-time smartphone verification. Experimental results for performance evaluation showed a spatial detection accuracy of 94.0%, an average local response latency of 420 ms, and a false-positive rejection rate of 89.5% against environmental clutter such as wind-driven foliage. Despite these advantages, the system presented limitations: ultrasonic susceptibility to severe weather and dense vegetation, reliance on manual human verification under intermittent rural connectivity, and vulnerability to pest habituation and high power demands. To address these limitations, it is necessary to incorporate edge AI for autonomous threat classification, solar-assisted energy harvesting for power-supply autonomy, and long-range-based decentralized communication protocols to ensure long-range operation. The improved system serves as a scalable, low-cost solution for precision agriculture.