Tuning into the Web: A Low-Cost Access Solution for Developing Countries

Abstract

Over a quarter of the global population remains without access to the Internet in 2026, primarily due to cost and limited infrastructure in developing regions. This gap is becoming more consequential as access to information increasingly depends on AI systems that presume reliable, high-bandwidth connectivity. In response, we present WebFM, a low-cost, scalable Web and AI access solution that builds on widely deployed infrastructure in developing regions: FM radio for downlink broadcasting and SMS for personalized uplink. Prior work on web-over-FM is limited to simulations, short-range experiments, and lossless links, leaving the effects of geographically induced signal variability largely unexplored. WebFM addresses this gap through several system-level innovations to effectively transmit Web content and enable LLM interactions over sound over FM radio, in a reliable and compressed form. For example, we introduce a loss-resilient file format for encoding webpages and modify Android to leverage built-in FM tuners, allowing deployment across a wide range of devices without requiring root access. We enable ChatGPT interactions by allowing users to submit prompts over SMS and receive model responses via FM broadcast. Finally, we preemptively transmit popular pages and a subset of their internal pages while the server is idle, improving user experience during peak hours. We deployed WebFM at an FM radio station in Cameroon for six weeks with 30 participants. Our evaluation shows a sustained downlink throughput of 10 kbps, less than 20% loss for most transmissions with signal strength above -90 dBm, and strong user engagement across both web browsing and ChatGPT interactions.