From Nature.com (emphasis added):
Here, we describe easily deployable hardware and software for the long-term analysis of a user’s excreta through data collection and models of human health. The ‘smart’ toilet, which is self-contained and operates autonomously by leveraging pressure and motion sensors, analyses the user’s urine using a standard-of-care colorimetric assay that traces red–green–blue values from images of urinalysis strips, calculates the flow rate and volume of urine using computer vision as a uroflowmeter, and classifies stool according to the Bristol stool form scale using deep learning, with performance that is comparable to the performance of trained medical personnel. Each user of the toilet is identified through their fingerprint and the distinctive features of their anoderm, and the data are securely stored and analysed in an encrypted cloud server. The toilet may find uses in the screening, diagnosis and longitudinal monitoring of specific patient populations.
tl;dr — Data gathering for toilets using biometrics of your anus. Got it? Okay cool.
The article itself is paywalled, as far too many academic articles are, but one Twitter user shared screenshots of this screening, diagnosis, and longitudinal monitoring technology:
Other pages explain:
We performed 410 fingerprinting [Ed note: butthole] trials from 10 participants … Among 11 participants, two video clips of the anus per participants were acquired from 7 participants, whereas one video clip of the anus per participant was acquired from 4 participants … As an input, individual frames of the anus from participant 1 were used for identification purposes.
And the general data collection method:
As a user sits on the toilet for a defecation event, the pressure sensor below the toilet seat initiates the defecation monitoring camera. The camera records the toilet bowl until the end of the defecation event. The collected images are then fed into deep CNN layers for stool classification.
Ain't that some shit, huh?
A mountable toilet system for personalized health monitoring via the analysis of excreta [Seung-min Park, Daeyoun D. Won, Brian J. Lee, Diego Escobedo, Andre Esteva, Amin Aalipour, T. Jessie Ge, Jung Ha Kim, Susie Suh, Elliot H. Choi, Alexander X. Lozano, Chengyang Yao, Sunil Bodapati, Friso B. Achterberg, Jeesu Kim, Hwan Park, Youngjae Choi, Woo Jin Kim, Jung Ho Yu, Alexander M. Bhatt, Jong Kyun Lee, Ryan Spitler, Shan X. Wang & Sanjiv S. Gambhir / Nature Biomedical Engineering]