Sensor arrays
Built to capture multi-channel response patterns instead of treating air quality as a single total value.
Olfactory intelligence, built from sensor to signal.
NeuroSense combines electronic nose sensing, structured scent data, and AI pattern recognition to help products interpret odor, gas, and VOC signals.
A measured path from invisible signal to usable intelligence.
- 01
Capture changing chemical signals.
Multi-channel electronic nose arrays are designed to support odor, gas, and VOC sensing inside product environments.
- 02
Turn response curves into stable signal patterns.
Preprocessing helps convert raw sensor behavior into comparable patterns across humidity, temperature, airflow, and time.
- 03
Build scent fingerprints for AI recognition.
Labeled scent data can train models to separate useful odor contexts from background environmental variation.
- 04
Embed decisions into products and systems.
Lightweight intelligence can be applied to connected products, spaces, and machines that need smell-aware context.
Hardware response, data structure, and AI recognition in one stack.
Signal conditioning
Designed to support cleaner interpretation by reducing environmental noise before classification.
Scent data
Helps convert repeatable odor events into structured fingerprints that can be reused across product programs.
AI recognition
Uses pattern recognition to translate sensor behavior into practical product-level context.
Built for products that need smell-aware context.
Air care
Identify odor and gas contexts that can guide purification, ventilation, and comfort decisions.
Health signals
Track non-invasive breath or body-odor signals as wellness indicators while staying in a screening context.
Food freshness
Sense VOC patterns associated with freshness, spoilage, storage, and fermentation environments.
Robotics and safety
Give mobile systems another sensing layer for invisible hazards, leaks, and environmental changes.