Introduction of a system that informs about diarrhea by listening to the sounds of the toilet.
An interesting use of artificial intelligence has now also emerged in the toilet, in which a sensitive microphone analyzes the sounds coming from the toilet and can predict diarrhea with 98% accuracy. A cholera outbreak can also be predicted from toilet data in a public or busy place.
Maya Gatlin of the Georgia Institute of Technology and her colleagues recorded 350 different toilet sounds from YouTube and a database called SoundSnap, including common situations like defecation, diarrhea, urination, and flatulence. Voices were included.
The scientists then put 70 percent of the collected sounds into artificial intelligence software and trained the algorithm to differentiate between the four types of defecation, then in the next step when they were confident the artificial intelligence was capable of it. The remaining 10 percent of the data was tested on this, followed by the remaining 20 percent of the recorded sounds that were finally tested on the software.
The system was found to be 98% accurate in telling whether it has diarrhea by listening to the sound of the toilet, but it is necessary to reduce the noise of people talking and other types of noise or its accuracy will decrease. It remains up to 96 percent.
Apart from this, by placing a microphone on a public toilet, diarrhea, diarrhea and cholera epidemics can also be determined in any area. This system includes a sensitive microphone, a microprocessor called diarrhea detector, which can predict health with the help of software. does, thus the sound signal is heard and processed very finely.
However, it is certain that the design of the toilet can make a difference to the sounds, and toilets like those in the US or Europe are not found around the world, however Professor Maya's team decided to record and test more real sounds.
