# CAREER: Towards Semantic-Centric Wireless Foundations for Swarm AI

> **NSF 01002627DB NSF RESEARCH & RELATED ACTIVIT** · Clemson University (SC) · $551,585

## Abstract

Artificial intelligence (AI) is rapidly expanding from centralized computing infrastructures into the physical world, where networks of distributed devices must sense, reason, and act together in dynamic and uncertain environments. This transformation gives rise to swarm AI, an emerging form of intelligent infrastructure that supports applications such as disaster response, environmental monitoring, precision agriculture, and autonomous mobility. Unlike traditional systems that rely on stable wired connections, swarm intelligence operates over wireless links that are intermittent, noisy, and resource constrained. Communication, therefore, becomes a central bottleneck that limits reliability, efficiency, and coordination. This project establishes a new wireless foundation for swarm AI by prioritizing the meaning and task relevance of transmitted information rather than raw bit accuracy alone. By strengthening how distributed agents share mission-critical information under challenging wireless conditions, the research enhances the resilience, scalability, and interoperability of next-generation intelligent systems. The project integrates research and education through curriculum development in communication-aware AI, hands-on mentoring of undergraduate and graduate students, outreach to K-12 learners, and open dissemination of research outcomes. These activities broaden participation in advanced wireless and intelligent systems research and contribute to workforce development in emerging communication and intelligent system technologies.

The project addresses a fundamental gap between AI systems that assume ideal connectivity and wireless communication protocols that optimize bit-level fidelity without accounting for task intent. The scientific problem is how to design wireless architectures that are aware of semantic content, resilient to time-varying channel impairments, and adaptive to heterogeneous device capabilities in swarm settings. The research establishes

## Key facts

- **NSF award ID:** 2542152
- **Awardee organization:** Clemson University (SC)
- **SAM.gov UEI:** H2BMNX7DSKU8
- **PI:** Lan Zhang
- **Primary program:** 01002627DB NSF RESEARCH & RELATED ACTIVIT
- **All programs:** Artificial Intelligence (AI), CAREER-Faculty Erly Career Dev, Wireless comm & sig processing, EXP PROG TO STIM COMP RES
- **Estimated total:** $551,585
- **Funds obligated:** $551,585
- **Transaction type:** Standard Grant
- **Period:** 09/01/2026 → 08/31/2031

## Primary source

NSF Award Search: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2542152

## Citation

> US National Science Foundation, Award 2542152, CAREER: Towards Semantic-Centric Wireless Foundations for Swarm AI. Retrieved via AI Analytics 2026-07-01 from https://api.ai-analytics.org/grant/nsf/2542152. Licensed CC0.

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