A developer frustrated by poor gzip compression of steady temperature sensor data built ALEC, a domain-specific codec for IoT streams. The tool exploits the predictable, low-entropy nature of sensor readings, using delta encoding and a dynamic pattern dictionary to shrink data far more effectively than generic algorithms.

Shannon's theorem states you can't compress below entropy, but entropy depends on your data model. Generic compressors treat sensor values as arbitrary bytes, while ALEC understands temporal stability and bounded ranges. This domain-specific approach is what enables dramatic gains for long-running IoT streams with predictable patterns.

Benchmark tests show ALEC beating gzip by up to 22x with preload data, versus gzip's 8x. It wins immediately on small sample counts where generic compressors fail. The key is eliminating warmup costs by syncing an initial context between encoder and decoder, making it ideal for production IoT deployments.