Pet Identification System Using Image Analysis for Targeted Marketing
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Solution Overview
Problem
Current systems lack effective methods for collecting and utilizing pet-related data to provide targeted marketing, risk assessments, and personalized advertising, failing to leverage the potential insights from pet owners' preferences and pet characteristics.
Innovation Solution
A system that creates a digital pet profile through data collection and sharing, utilizing AI and machine learning for image and video recognition, and intelligent cropping, which links pet profiles to user IDs for targeted advertising and risk assessments.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If traditional advertising platforms are used, then revenue generation is possible, but the ability to provide targeted marketing and personalized advertising based on pet characteristics is insufficient
Solution Approach 1:
The system segments the advertising market by creating distinct pet profiles with specific characteristics (breed, age, weight, photos, videos, food preference, toy preference, adoption date, adoption source, birthdate, and location). This segmentation enables targeted marketing by dividing the general audience into specific pet owner groups based on their pet's attributes, allowing for personalized advertising campaigns.
Solution Approach 2:
The system performs preliminary data collection and pet profile creation before advertising campaigns are launched. By pre-collecting pet-related information and creating comprehensive digital profiles, the system prepares the necessary data infrastructure in advance, enabling efficient targeted marketing and personalized advertising when campaigns are initiated.
2Measurement precision
If comprehensive pet data is collected and stored, then personalized advertising and risk assessment accuracy improve, but system complexity and data management requirements increase
Solution Approach 1:
The pet profile system serves multiple functions simultaneously: it stores pet characteristics data, enables personalized advertising, performs risk assessment, and supports marketing analytics. By creating a universal digital profile that can be used across different applications (advertising, risk assessment, marketing), the system reduces overall complexity compared to having separate systems for each function.
Solution Approach 2:
The patent introduces an API (Application Programming Interface) as an intermediary layer between the pet data collection system and various applications (advertising platforms, risk assessment tools, marketing systems). This API simplifies data access and management by providing standardized interfaces, reducing the complexity burden on both the data collection system and the applications that consume the data.
3Measurement precision
If image and video recognition systems are implemented for pet identification, then breed, age, and characteristic detection accuracy improve, but processing time and computational resources increase
Solution Approach 1:
The system performs preliminary image and video processing by automatically detecting and extracting key pet characteristics (breed, age, weight, photos, videos, food preference, toy preference) and storing them in the pet profile database in advance. This preliminary action reduces the need for real-time analysis during advertising or risk assessment operations, thereby reducing processing time when these data are needed.
Solution Approach 2:
The system creates digital copies of pet characteristics from image and video data by using AI and machine learning to automatically generate structured data representations (breed identification, age estimation, weight prediction) from visual inputs. These digital copies are stored in the pet profile and can be quickly retrieved without re-processing the original images or videos, significantly reducing processing time for subsequent operations.
Data Source
AI summary
A pet is identified by capturing or receiving an image containing the pet, isolating the pet in the image, and identifying the pet. Isolating the pet may include image enhancement, such as outlining the pet (e.g., a fur outline) or removing a background of the image. The identification may include comparison of various pet characteristics to a database of characteristics associated with known pets. The characteristics may be type of animal characteristics, breed characteristics, and specific pet characteristics and/or the pet's name. Pets and their characteristics may be may be added to the database using similar criteria forming a profile for each pet that may be used for other purposes. More than one pet may be linked to an owner such as through a mobile device ID and more than one owner or individual may be linked to a pet.