Performance analysis of video data transmission for telemedicine applications with 5G enabled Internet of Things.

•The authors proposed a novel KNN classifier-based H.265 protocol with a single buffer model in this paper. Multiple sensors are placed at the transmitter and receiver base stations to exchange data efficiently and accurately.•The data transmission performance is measured using collision error, propagation error, sensing error, and visual security with encryption.•The proposed novel MS-KNN classifier-based single buffer technique with H.265 protocol performs better than the existing LE-based approach. The Hidden Markov Model-based queuing technique with CD, VS, and SP estimates the sensor performance.•There is a significant improvement for the proposed MS-KNN-based single buffer method in the parameters of sensing error, propagation error, Busy receiver error, and collision error are 2%, 3%, 3%, and 5%, respectively, at 200 meters distance when compared to LE-single buffer technique.•Similarly, significant improvement in received packet ratio at 10 dBm, 20 dBm and 30 dBm is 4%, 2% and 2%, respectively. Hence, the proposed single buffer method performs better than the existing double buffer method in the case of sensory errors and received packet ratio at various levels.