Pet Content System Using Feedback and Self-Service TRIZ Principles
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Solution Overview
Problem
Current technologies fail to provide personalized content to pets based on their individual tastes and conditions, often leaving them unattended and potentially suffering from loneliness, as existing solutions do not consider the pet's preferences when providing videos or images.
Innovation Solution
A system and method that collect information on a pet's actions, noises, and environment, process this data into messages, and use deep learning or reinforcement learning to analyze user responses, searching for and output customized content matching the pet's preferences, allowing for a more engaging and tailored experience.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If a pet owner leaves the house after turning on the TV for the pet, then the pet can be left alone safely, but the content provided is one-sided and does not match the pet's taste and desire
Solution Approach 1:
The system continuously monitors the pet's reactions (noise, movement, attention) to the displayed content and uses this feedback to dynamically adjust and select subsequent content. The analyzing device processes the pet's responses to determine preference, creating a closed-loop system that adapts content delivery based on real-time pet feedback, thereby achieving personalized content without requiring complex manual configuration.
Solution Approach 2:
The pet effectively selects its own preferred content through its natural reactions and behaviors. The system observes what type of content the pet pays attention to (e.g., birds, fish, running animals) and automatically provides similar content in the future, allowing the pet to self-determine its entertainment preferences without human intervention.
2Reliability
If technology is developed to provide personalized content to pets, then pet entertainment and comfort improve, but the system complexity and analysis requirements increase
Solution Approach 1:
The system divides the complex task of pet analysis into separate functional modules: a collecting device that gathers raw data (noise, images), an analyzing device that processes the data to determine pet state and preferences, and a content provision system that delivers appropriate content. This segmentation allows each component to be optimized independently and simplifies the overall system architecture.
Solution Approach 2:
The analyzing device serves as an intermediary between the pet's natural behaviors and the content delivery system. It translates the pet's reactions into meaningful insights about preference and state, bridging the gap between observing raw pet behavior and selecting appropriate content, thereby reducing the complexity of direct pet-content matching.
Data Source
AI summary
The present disclosure relates to a method for providing content using communication with animals and the program and the system therefor, which can analyze information of a pet, such as the pet's action, noise, and surrounding environment, process the information into a message, provide a user with the message, search for content matching the message after analyzing the user's response message, and output and provide the contents for the pet.