Research Idea: Detecting Refilled Tap Water in Premium Mineral Water using Ultrasonic AI
I have been conducting a literature review on non-invasive authentication methods and noticed that several researchers have successfully used Ultrasonic Testing for liquid analysis. However, most of these studies focused on fluids with higher viscosity (like oils or honey), which naturally presents an easier challenge due to distinct density variations.
My current objective is to address a more complex problem: Detecting treated tap water in refilled premium mineral water bottles.
Since the physical differences here are minimal, I am very keen to apply Deep Learning and Computer Vision techniques (e.g., analyzing spectrogram images of the ultrasonic echoes) to distinguish the authentic brands.
Has anyone here worked on a similar subject or seen case studies regarding low-viscosity fluid differentiation? I am open to collaboration or any insights on this topic.
I have been conducting a literature review on non-invasive authentication methods and noticed that several researchers have successfully used Ultrasonic Testing for liquid analysis. However, most of these studies focused on fluids with higher viscosity (like oils or honey), which naturally presents an easier challenge due to distinct density variations.
My current objective is to address a more complex problem: Detecting treated tap water in refilled premium mineral water bottles.
Since the physical differences here are minimal, I am very keen to apply Deep Learning and Computer Vision techniques (e.g., analyzing spectrogram images of the ultrasonic echoes) to distinguish the authentic brands.
Has anyone here worked on a similar subject or seen case studies regarding low-viscosity fluid differentiation? I am open to collaboration or any insights on this topic.
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