Researchers from Hong Kong and Shenzhen universities have developed a specialized deep learning model (BladderCoordNet) combined with an ultrasonic sensor array to measure bladder volume and assist patients with lower urinary tract dysfunction. The lightweight model (165K parameters) achieves 8.5% average error rate and runs on smartphones in just 39ms, making it potentially applicable for real-world medical monitoring and Thai health-tech startups exploring IoT healthcare solutions.