University of Illinois Urbana-Champaign

Toward a platform for programmable digital olfactory processing

Wezelis, Abigail

This item's files can only be accessed by the Administrator group.

Permalink

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

Description

Title
Toward a platform for programmable digital olfactory processing
Author(s)
Wezelis, Abigail
Issue Date
2022-10-06
Director of Research (if dissertation) or Advisor (if thesis)
Kumar, Rakesh
Department of Study
Electrical & Computer Eng
Discipline
Electrical & Computer Engr
Degree Granting Institution
University of Illinois at Urbana-Champaign
Degree Name
M.S.
Degree Level
Thesis
Keyword(s)
  • digital olfaction
  • e-nose
  • odor processing
  • digital scent technology
  • programmable odor platform
Abstract
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.
Graduation Semester
2022-12
Type of Resource
Thesis
Copyright and License Information
Copyright 2022 Abigail Wezelis

Owning Collections

Graduate Dissertations and Theses at Illinois PRIMARY
Graduate Theses and Dissertations at Illinois