Low-cost and Non-intrusive Food Sensing: A Survey

PhD Qualifying Examination


Title: "Low-cost and Non-intrusive Food Sensing: A Survey"

by

Mr. Yinan ZHU


Abstract:

Food sensing is an essential demand for customers, food stores and regulatory 
authorities. People are enthusiastic to find out the properties of their daily 
food such as flavor and nutrition contents, and concerned about food safety 
including spoilage and counterfeiting. However, precise food sensing via 
chemical experiments is either destructive to food such as liquid 
chromatography, or requires high equipment costs such as hyperspectrometers. 
With the recently emerged low-cost and non-intrusive sensing technologies, 
daily food sensing tends to be feasible. Nevertheless, the low-cost and non- 
destructive properties of these technologies limit their capabilities compared 
to precise chemical equipment, in terms of sensing granularity, robustness and 
generalization. To achieve fine sensing performance under low capabilities, 
signal processing algorithms and deep learning models as well as training 
schemes need to be well-designed for the given modalities and applications.

In this survey, we summarize the latest applications on daily food sensing 
empowered by low-cost and non-intrusive sensing techniques. We first introduce 
the related sensing modalities and their working mechanisms, especially for the 
promising spectroscopy techniques. Then, we present recent food sensing 
applications, including food property detection, food safety inspection and 
food monitoring for special groups, and elaborate on the model and algorithm 
details in their system design as well as their strengths and limitations. 
Furthermore, we introduce our two works on food safety based on low-cost 
multispectral imaging as our research attempts. In the end, we discuss future 
research directions and conclude this survey.


Date:                   Wednesday, 8 May 2024

Time:                   1:00pm - 3:00pm

Venue:                  Room 5501
                        Lifts 25/26

Committee Members:      Prof. Qian Zhang (Supervisor)
                        Prof. Song Guo (Chairperson)
                        Prof. Mo Li
                        Dr. Wei Wang