Mars. has filed a patent for a system that analyzes images of animal fecal matter using machine learning to provide health assessments and recommendations. The method involves receiving the image, processing it, generating a recommendation, and displaying it to the user. The system may also output confidence scores and follows a SaaS model. GlobalData’s report on Mars gives a 360-degree view of the company including its patenting strategy. Buy the report here.
According to GlobalData’s company profile on Mars, Filled confectionary manufacturing was a key innovation area identified from patents. Mars's grant share as of January 2024 was 55%. Grant share is based on the ratio of number of grants to total number of patents.
Fecal matter analysis for animal health assessment
The patent application (Publication Number: US20240037734A1) describes a computer-implemented method that involves receiving an input image of fecal matter from an animal, processing the image using machine learning models to generate a classification or health assessment of the animal, and providing recommendations based on this analysis. The method includes detecting blood in the fecal matter, assessing various characteristics of the fecal matter, and incorporating additional inputs such as the animal's activity level, diet, and microbiome analysis to generate a comprehensive health assessment. Recommendations can range from pet products to veterinary visits based on the analysis conducted.
Furthermore, the patent application also covers the implementation of this method through computer-readable non-transitory storage media and a system comprising processors and storage media. The system is designed to receive input images, process them using machine learning models, generate health assessments and recommendations for the animal, and display relevant information to the user. The classification of fecal matter includes health metrics related to the animal, and the method accounts for various factors such as species, breed, age, gender, weight, height, biological age, and microbiome age status of the animal to provide a comprehensive health assessment. The system aims to offer personalized recommendations for pet care based on a thorough analysis of the animal's fecal matter and additional inputs, ultimately enhancing the well-being of the animal.
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