A real-time architecture of SOC selective gas sensor array using KNN based on the dynamic slope and the steady state response

This paper demonstrates that using the dynamic response together with the steady state response greatly improves the classification performance of gas sensors. We propose a SOC VLSI architecture based on the KNN algorithm and operating on both the steady state and dynamic slope response of the data from the gas sensor array. The architecture is based on a current model analog pipelining strategy which allows to share hardware resources between different sensors within the sensor array. This results in significant area savings making the prospect of building low cost and real-time electronic nose microsystem reasonably cheap.