Toward a platform for programmable digital olfactory processing

Digital olfactory processing comprises a set of solutions that use odor detection and synthesis for solving problems. With recent advances in electronic nose (e-nose) and odor synthesis technologies, it may be time to consider the development of a programmable platform for digital olfactory processing. In this work, we identify a number of odor processing tasks that should be supported on such a platform in wearable and AR/VR devices: odor localization, e-nose classification, odor authentication, odor similarity, active odor cancellation, odor pleasantness estimation, and odor demixing. We then collate a list of commonly used algorithms for these tasks: particle filtering (PF), Infotaxis, principal component analysis (PCA), linear discriminant analysis (LDA), support vector machine (SVM), artificial neural network (ANN), k-means clustering analysis (CA), angle distance of vector sums (ADVS), convex optimization (CVX), random forest (RF), and orthogonal matching pursuit (OMP). Benchmarking is then performed in order to learn about the characteristics of these algorithms. Common algorithmic characteristics across the selected odor processing tasks, such as the frequency of non-linear floating point operations and the vectorizability of linear floating point operations, will be able to drive support for effective specialization in future programmable platforms for digital olfactory processing.

Name thesis:degree_name

M.S.

Level thesis:degree_level

Thesis

Discipline thesis:degree_discipline

Electrical & Computer Engr

Grantor

University of Illinois at Urbana-Champaign

Year dc:date

2022

Author dc:creator

• Wezelis, Abigail

Contributors dc:contributor

• Kumar, Rakesh

• Digital Olfaction
• E-nose
• Odor Processing
• Digital Scent Technology
• Programmable Odor Platform

Statement dc:rights

• Copyright 2022 Abigail Wezelis

Language dc:language

en, eng

Handle dc:identifier

https://hdl.handle.net/2142/117535

OAI record oai:identifier

https://www.ideals.illinois.edu/oai-pmh?verb=GetRecord&metadataPrefix=etdms&identifier=oai%3Awww.ideals.illinois.edu%3A2142%2F117535