5G Tiny-ML AI-based IoT eNose system for Hazardous Odour Detection and Classification

Abstract

More than 2 million people have died in the world in 2019 exposed to hazard substances. In this context, it is of paramount importance to deliver effective systems to help minimizing such number of dead. The usage of advanced technologies, such as artificial intelligence (AI) and the Internet of Things (IoT), plays a critical role in the detection of hazardous substances within Industry 4.0. The combination of these technologies enhance the efficiency and accuracy of monitoring harmful materials, improving safety standards and operational processes in industrial environments. AI can be used to analyse vast amounts of data for identifying patterns and predicting potential hazards, while IoT connects various devices and sensors to ensure real-time tracking and prompt responses to risks. This technological synergy is essential for modern industries aiming to create safer and more automated systems. In this work, we propose a 5G AI-IoT e-Nose system for the real-time detection and classification of 5 hazardous odours. The proposed AI model is very lightweight and it is affordable for our IoT micro controller unit. The system has been validated in laboratory conditions, but has the advantage and potential impact to be effective in any scenario.