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The patented data compaction software uses machine learning to seek patterns in IoT message payloads, compacting the data before transmitting it between devices. As a result, virtually no latency is added, no matter the device, protocol, or network. Once data is transmitted to its destination, it is rebuilt 100% losslessly.
Compaction uses machine learning to send small ‘codewords’ that represent larger patterns rather than sending the original source. This adds a critical layer of security without needing a separate encryption or decryption process.
The technology benefits IoT applications by significantly reducing airtime costs, while making satellite connectivity more viable and secure, all in a single, ultra-lightweight computing process.
An illustration demonstrating the architecture of Compaction within a satellite IoT network. Individual customer circumstances may vary from what's shown.
AtomBeam is a California-based software company specialising in data compaction solutions to save bandwidth. Its machine learning technology and use of code transforms the data compaction process for customers, circumventing the need for hardware or new pipelines. The Compaction solution reduces airtime costs, making satellite connectivity both more viable and secure.