Consciousness Affect Generation Using Non-Biological Inputs
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Solution Overview
Problem
Current online social networks are inadequate in capturing and representing the complex emotional and intentional responses of users, relying on limited user inputs like 'Like' buttons, which fail to accurately convey underlying consciousness and influence, leading to inaccurate consumer insights and ineffective communication.
Innovation Solution
A network-based system that transforms user-generated consciousness inputs and non-biological inputs into a visual and/or audible representation of consciousness affects, allowing for real-time calculation and display on client devices, incorporating emotional state, reasoned, location, physical awareness, and spiritual insight inputs, along with non-biological inputs like synchronicity, to provide a more comprehensive understanding of user influences and group dynamics.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If a simple 'Like' button or single-button response system is used, then ease of operation is improved, but measurement precision and information quality deteriorate
Solution Approach 1:
The patent segments the single 'Like' button response into multiple distinct response options representing different emotional states (e.g., Love, Joy, Peace, Serenity, Desire, Fear, Anger). This segmentation allows users to express nuanced emotions while maintaining ease of operation through simple selection, thereby improving measurement precision without sacrificing user convenience.
Solution Approach 2:
The patent adds a new dimension to the response system by introducing intensity levels (e.g., 1-5 scale or low/medium/high) for each emotional state. This transforms a one-dimensional like/dislike response into a multi-dimensional emotional expression system, enabling more precise measurement of both the type and strength of user emotions.
2Measurement precision
If multiple consciousness inputs and non-biological inputs are integrated, then measurement precision and consumer insights are improved, but device complexity increases
Solution Approach 1:
The patent segments the complex processing task into distinct modules: one module receives and processes consciousness inputs (user-selected emotional states and intensities), another module receives non-biological inputs (contextual data from sensors or external sources), and a third module integrates these inputs to calculate consciousness affects. This modular segmentation reduces device complexity by making the system more manageable and scalable.
Solution Approach 2:
The patent introduces an intermediary calculation layer that processes raw consciousness inputs and non-biological inputs separately before integrating them. This intermediary step simplifies the overall processing by handling different input types through dedicated transformation logic, reducing the complexity of direct integration while improving measurement precision.
3Loss of information
If real-time calculation and visual representation of consciousness affects are implemented, then information quality and consumer insights are improved, but use of energy and processing resources increase
Solution Approach 1:
The patent implements partial real-time processing by calculating consciousness affects continuously but only performing full visual representation updates when significant changes occur or at predetermined intervals. This approach maintains high information quality by keeping data current while reducing energy consumption by avoiding unnecessary continuous rendering and processing cycles.
Solution Approach 2:
The patent uses simplified visual representations (e.g., color-coded indicators, basic icons) that require minimal processing resources to generate and display. These lightweight visual elements provide sufficient information quality for consumer insights while consuming significantly less energy than complex graphical displays or animations would require.
Data Source
AI summary
A method of generating a consciousness affect is described. The method includes: (i) receiving a consciousness input originating from one or more users associated with a client device; (ii) receiving a non-biological input not originating from one or more of the users and the non-biological input originating from a device or a module; (iii) calculating, using a server and/or the client device and based on the consciousness input and the non-biological input, a consciousness affect for one or more of the users; (iv) storing, in memory of the server and/or the client device, the consciousness affect; and wherein said consciousness input includes at least one input chosen from a group comprising emotional state input, reasoned input, location information input, physical awareness input and spiritual insight input, and said non-biological input is at least one input chosen from a group comprising emotional state input, reasoned input, location information input, physical awareness input and synchronicity input.