3 accepted papers
In this work, we present a method for detecting anomalous chemical sensors using contrastive learning-based framework. In many practical systems, an array of multiple chemical sensors are used. Some of the sensors may malfunction due to sensor drift and chemical poisoning. In standard contrastive le…
Sensor drift is a major problem in chemical sensors that requires addressing for reliable and accurate detection of chemical analytes. In this paper, we develop a causal convolutional neural network (CNN) with a Discrete Cosine Transform (DCT) layer to estimate the drift signal. In the DCT module, w…
While Volatile Organic Compounds (VOC) and ammonia have a place in our daily lives, their leakage into the environment is harmful to human health. In order to prevent and detect gaseous leaks of harmful VOCs, a cyber-physical system (CPS) comprised of ordinary people or first responders is proposed.…