Forget Manual Logs: Building a Real-Time Medication Compliance Auditor with YOLOv10 and TensorRT

Managing multiple medications is a high-stakes challenge, especially for the elderly or patients with complex chronic conditions. Traditional pill organizers help, but they can't provide real-time verification . What if we could use Computer Vision and Edge AI to ensure the right person takes the right pill at the right time? In this tutorial, we are building a "Visual Audit System" using YOLOv10 for high-speed object detection, TensorRT for hardware acceleration, and MQTT for instant alerting. By leveraging state-of-the-art real-time computer vision and object detection models, we can transform a standard webcam into a life-saving healthcare assistant. The Architecture: From Pixels to Alerts Our system follows a streamlined pipeline: capturing frames, detecting medicine labels, validating them against a JSON-based medication schedule, and broadcasting the status. graph TD A[Fixed Camera Stream] --> B[OpenCV Image Pre-processing] B --> C[YOLOv10 Inference - TensorRT] C --> D{Medicine D