Towards automated molecular detection through simulated generation of CMOS-based rotational spectroscopy.

The use of CMOS sensors for rotational spectroscopy is a promising, but challenging avenue for low-cost gas sensing and molecular identification. A main challenge in this approach is that practical CMOS spectroscopy samples contain various different noise sources that reduce the effectiveness of matching techniques for molecular identification with rotational spectroscopy. To help solve this challenge, we develop a software application tool that can demonstrate the feasibility and reliability of detection with CMOS sensor samples. Specifically, the tool characterizes the types of noise in CMOS sample collection and synthesizes spectroscopy files based upon existing databases of rotational spectroscopy samples gathered from other sensors. We use the software to create a large database of plausible CMOS-generated sample files of gases. This dataset is used to help evaluate spectral matching algorithms used in gas sensing and molecular identification applications. We evaluate these traditional methods on the synthesized dataset and discuss how peak finding and spectral matching algorithms can be altered to accommodate the noise sources present in CMOS sample collection.