Video conferencing algorithms for enhanced access to mental healthcare services in cloud-powered telepsychiatry

Rajagopalan Senkamalavalli, Subramaniyan Nesamony Sheela Evangelin Prasad, Mahalingam Shobana, Chellaiyan Bharathi Sri, Rajendar Sandiri, Jayavarapu Karthik, Subbiah Murugan

Abstract


Exploring the video conferencing algorithms for cloud-powered telepsychiatry to improve mental healthcare access. The goal is to evaluate and optimise these algorithms' latency, bandwidth utilisation, packet loss, and jitter across worldwide locations. To provide a smooth and high-quality virtual consultation between patients and mental health providers. Using performance data to identify areas for development, the effort aims to lower technological hurdles and increase telepsychiatry session dependability. Findings will help create strong, efficient algorithms that can handle different network situations, increasing patient outcomes and extending mental healthcare services. In the 1st instance latent analysis in a sample of 5 cities, the average latency (ms) is 45, the peak latency is 120, the off-peak latency is 30, and the packet loss is 0.5. In another instance, bandwidth utilisation in a sample of 5 sessions ranged from 30 to 120 minutes, with data supplied in MB - 150-600 and received in MB - 160-620, with average bandwidth (Mbps) - 5-15 and maximum bandwidth: 10-20.

Keywords


Cloud computing; Mental healthcare; Network optimization; Telepsychiatry; Video conferencing

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DOI: http://doi.org/10.11591/ijece.v15i1.pp1142-1151

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International Journal of Electrical and Computer Engineering (IJECE)
p-ISSN 2088-8708, e-ISSN 2722-2578

This journal is published by the Institute of Advanced Engineering and Science (IAES) in collaboration with Intelektual Pustaka Media Utama (IPMU).