SpecPipe: A scalable AI/ML-facilitating data pipeline for spectrum

By: Hao-Ming Hsu, Omair Alam, Will Almy, Alice Lee

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In today's interconnected world, radio spectrum signals surround us, yet there exist noticeable limitations in the data systems created to access, monitor, perform AI experiments, and contribute to this analog data.

To democratize the access and usage of spectrum data, we have built SpecPipe, a distributed AI/ML data pipeline. This platform’s core values of accessibility, extensibility and scalability ensure that individual users can start to work with radio data with inexpensive hardware, minimal configuration, and a smooth onboarding process.

We have accomplished this goal of improving access to spectrum data by building SpecPipe as an open-source project free for people to access and use, with easy to follow documentation, and a plethora of startup examples that allow users to understand our framework interactively.

For more details on the architecture of SpecPipe click here.

For more context about SpecPipe, please read our technical report. Additionally, Here is a one-page projet brief that summarizes our work.