The physical world is full of invisible signals. A plant under stress changes the chemistry of the air around it. A machine overheating releases different compounds. A room after a contaminating event carries a fading chemical trace.
Robots are entering these environments, but most of them are chemically blind. Aeralyte builds the research foundation for machines that can smell — controlled air sampling, compact sensor arrays, on-device AI, and rigorous experimental protocols.
Near-term: repeatable smell fingerprints. Long-term: a machine-readable language of smell that lets robots and IoT devices detect, interpret, trace, and eventually synthesize chemical signatures.
Each is an open research direction — a place where reading the chemistry of air earlier, or on-device, could change what a machine can do.
We have designed the air-sampling protocol, the electronic-nose sensor array, the ESP32-S3 firmware, and the truth-gated analysis pipeline that turns sensor responses into smell fingerprints. The bench is live: the board is flashed and three sensor families are returning real readings. We are completing the rig and moving into controlled chamber experiments.