Page 461 - AI for Good Innovate for Impact

AI for Good Innovate for Impact

2�2 Benefits of the Use Case

This system improves access to spoken communication in educational settings, offering
real-time transcription and equitable speaker turns. It ensures all students can participate
meaningfully, even when traditional audio tools are unavailable or limited. 4.4-Productivity

By enforcing a fair, AI-managed speaking queue, the solution prevents conversational
dominance and ensures all voices—including those from underrepresented genders—have
equal opportunity to be heard.
The system reduces costs related to specialized audio hardware and technical staffing. It provides
a scalable communication tool for resource-limited workplaces, supporting productivity and
innovation, especially in developing regions.

Replacing traditional hardware with AI-powered, software-based infrastructure supports digital
transformation. Using existing smartphones and local Wi-Fi makes the solution deployable
even in areas with limited infrastructure.

The AI ensures fair speaker selection regardless of background. Features like transcription aid
those with hearing impairments or softer voices, helping everyone participate equally.

This system improves communication in public forums, town halls, and councils by promoting
organized participation and public engagement. It also aids in transparent decision-making.

Automated recording, transcription, and fair speaking procedures promote transparency and
accountability in official settings. This supports stronger governance and civic trust.

2�3 Future Work

As the AI-Driven Wireless Audio Conference System evolves, future work will focus on enhancing
AI capabilities through features like dynamic speaker prioritization, sentiment-based urgency
detection, and speaker diarization for better multi-speaker management. The system will
expand to support cloud-based deployments for remote and hybrid meetings, and multilingual
transcription and translation to promote inclusivity. Technical upgrades will include support
for low-spec devices, integration with Bluetooth PA systems, and edge computing to reduce
latency. Real-world audio data will be collected to retrain and fine-tune models for improved
accuracy across diverse environments and accents. Strategic collaborations with universities,
local governments, and accessibility experts are planned to expand reach and ensure inclusive
design. Lastly, development will emphasize strong data privacy, ethical AI governance, and
compliance with international standards like General Data Protection Regulation (GDPR).

3 Use Case Requirements

• REQ-01: It is critical that the mobile application must be compatible with Android and iOS
platforms to ensures that users, regardless of the device they use, can join and participate
in meetings, conference, maximizing inclusivity and adoption.
• REQ-02: It is critical for all mobile devices (clients) and the AI-driven server to be connect
to the same local Wi-Fi network. This setup avoids internet latency, ensures fast, low-
latency communication, and simplifies deployment in venues like schools, conferences,
or town halls.
• REQ-03: It is crucial that the AI-driven server must analyse incoming speaker requests,
evaluate parameters like user role, speaking time, and order of request, and automatically

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