SMELLNET: A Large-scale Dataset for Real-world Smell Recognition

Researchers have developed SmellNet, a large-scale database of approximately 180,000 samples capturing diverse natural smells, to advance AI's ability to identify substances through scent. Despite promising classification accuracy, the study highlights ongoing technical challenges in creating robust, real-time, on-edge smell recognition models capable of functioning reliably in real-world environments.