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Updated: Sep 28, 2025

Integration of 5G Experimentation Infrastructures into a Multi-Site NFV Ecosystem
Published on: February 3, 2021
Counseling (ro)bot as a use case for 5G/6G.
Yoshio Taniguchi1, Yukino Ikegami2, Hiroshi Fujikawa3
1Hitachi Industry & Control Solutions Ltd, Tokyo, Japan.
This study introduces an AI-powered Visual Counseling Agent (VICA) for remote mental healthcare. Leveraging 5G/6G networks and edge computing significantly improves VICA
Area of Science:
- Mental Healthcare Technology
- Artificial Intelligence in Psychology
- Telecommunications
Background:
- Remote mental healthcare delivery faces challenges with current network limitations.
- Conventional 4G networks hinder the performance of AI-driven counseling agents like VICA, causing issues like word dropping and connection failures.
- Existing AI counseling systems require enhanced network infrastructure for reliable and high-quality remote support.
Purpose of the Study:
- To enhance the Visual Counseling Agent (VICA) for improved remote mental healthcare.
- To mitigate performance issues of VICA on 4G networks by utilizing 5G/6G network slicing and mobile/multiple edge computing (MEC).
- To improve speech recognition reliability and enable facial expression analysis for superior counseling quality.
Main Methods:
- Proposed and implemented an enhanced and advanced version of the VICA system.
- Utilized 5G/6G network slicing inclusive of MEC to process data closer to the user.
- Developed a multi-level catalog quality assurance mechanism for VICA.
- Conducted experiments comparing VICA performance on 4G networks versus 5G/6G with MEC.
Main Results:
- Speech recognition errors were more than twofold higher in Internet Cloud compared to edge computing.
- The advanced VICA version, with facial expression recognition, significantly enhances counseling quality.
- 5G/6G network slicing with MEC demonstrated higher efficiency in quality assurance for the VICA counseling (ro)bot.
- Edge computing reduced speech recognition errors compared to traditional cloud-based processing.
Conclusions:
- 5G/6G network slicing combined with MEC effectively addresses the limitations of 4G for AI-driven remote mental healthcare.
- The enhanced VICA system offers a more reliable and higher-quality remote counseling experience.
- Integrating advanced features like facial expression recognition with robust network infrastructure is crucial for future tele-mental health solutions.
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