Neural Synchronization Data Transmission With Motion Signal Protocol

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Solution Overview

Problem

Current network data processing methods are inefficient, leading to high costs, resource waste, and limitations in next-generation cloud services due to antiquated data transmission patterns based on human verbal communication.

Innovation Solution

A system, method, and computer program product utilizing a neural synchronization architecture to reduce, optimize, secure, and accelerate data records/frames transmission and processing by converting data into data entropy and using the Motion Signal Protocol (MSP).

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Quantity of substance

If data is transmitted using traditional network protocols with metadata and frames, then data can be communicated across the network, but bandwidth requirements increase and transmission efficiency decreases

Engineering Contradiction:

Improvebandwidth requirementsVSAvoidtransmission efficiency

Core Design Contradiction:

Quantity of substanceVSProductivity

Solution Approach 1:

The patent extracts and removes unnecessary metadata and frame structures from data transmission, keeping only the essential information. This is achieved through neural synchronization that identifies and eliminates redundant data elements, directly reducing bandwidth requirements while maintaining transmission efficiency

Inventive Principle:

Principle #2Taking out (Extraction)

Solution Approach 2:

The patent changes the fundamental parameters of data representation by converting traditional structured data (with metadata and frames) into neural synchronization patterns. This parameter transformation enables more efficient data encoding that requires less bandwidth while improving transmission speed and efficiency

Inventive Principle:

Principle #35Parameter changes

2Speed

If data is sent one frame at a time following human verbal communication patterns, then data transmission can occur, but processing speed decreases and resource consumption increases

Engineering Contradiction:

Improveprocessing speedVSAvoidresource consumption

Core Design Contradiction:

SpeedVSUse of energy by moving object

Solution Approach 1:

The patent implements continuous data transmission through neural synchronization patterns, eliminating the stop-start nature of traditional frame-by-frame communication. This continuous action enables parallel processing of multiple data elements simultaneously, increasing processing speed while reducing overall resource consumption through more efficient utilization

Inventive Principle:

Principle #20Continuity of useful action

Solution Approach 2:

The patent performs preliminary neural synchronization and data pattern recognition before transmission, allowing the system to pre-process and optimize data sequences. This preliminary action enables faster processing during actual transmission and reduces resource consumption by avoiding redundant processing operations

Inventive Principle:

Principle #10Preliminary action

3Ease of operation

If traditional network protocols with extensive metadata are used, then data can be standardized for human reading, but data transmission costs increase

Engineering Contradiction:

Improvedata standardizationVSAvoiddata transmission costs

Core Design Contradiction:

Ease of operationVSQuantity of substance

Solution Approach 1:

The patent inverts the traditional approach by prioritizing machine-to-machine communication efficiency over human readability. Instead of standardizing data for human consumption with extensive metadata, it uses neural synchronization patterns optimized for computational processing, thereby reducing transmission costs while maintaining operational effectiveness

Inventive Principle:

Principle #13The other way round (Inversion)

Data Source

PatentUS12242923B2System, method, and computer program product for reduction, optimization, security, and acceleration of computer data transmission using neural synchronization

Publication Date: 2025.03.04 EDGAR DAVID ALLAN

AI summary

Systems and methods are described herein which may be implemented using computer programs comprising instructions that replicate the neural synchronization algorithm of the human brain. These implementations result in reduction, optimization, security and acceleration of data records/frames and processing in a computer system or network. An embodiment of the invention comprises motion decimation, motions reactor, motion replicator and motion aggregator modules for replicating higher intelligence functions, and a management module for configuring resources and monitoring system operation. Systems and methods as described herein may operate on wired or wireless computer networks. Data are translated from original format into thalamic motion and further encoded with motion signal protocol, then reproduced and aggregated using thalamic motion for integration with higher forms of intelligence. By duplicating the human brain's neural synchronization process, overall process and communication efficiency may be dramatically increased.