Human Activity Analysis Using AI, Logic, and Context Fusion
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Solution Overview
Problem
Current technologies face challenges in analyzing and predicting time-based human activities with sufficient accuracy and efficiency, particularly in complex scenarios like automotive driving and group gatherings, where traditional methods struggle to process and interpret the vast amount of data generated by human interactions.
Innovation Solution
The implementation of a time-based human activities universal processor that combines artificial intelligence analysis with logic and contextual analysis, utilizing advanced mathematical algorithms and n-dimensional space-curves formulas to extract actionable insights from matrices element indices, enabling the classification and prediction of human behavior and motion.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional methods are used to process and interpret data from human activities, then the system complexity remains low, but the analysis accuracy and prediction capability are insufficient
Solution Approach 1:
The patent combines multiple analysis methods (artificial intelligence analysis, logic analysis, contextual analysis) into a unified processing system. The universal processor integrates these different analytical approaches to work together, improving measurement precision while managing system complexity through coordinated integration rather than separate independent systems.
Solution Approach 2:
The universal processor is designed to perform multiple functions: artificial intelligence analysis, logic analysis, contextual analysis, and prediction. This multi-functional approach allows a single system to handle diverse analytical tasks, improving accuracy across different human activity scenarios without requiring multiple specialized systems.
2Reliability
If advanced mathematical algorithms and AI analysis are implemented, then the prediction capability improves, but the processing time and computational resources increase
Solution Approach 1:
The patent segments the analysis process into distinct modules: artificial intelligence analysis module, logic analysis module, and contextual analysis module. Each module handles specific aspects of the data processing, allowing parallel execution and optimization of individual components, which reduces overall processing time while maintaining high prediction capability.
Solution Approach 2:
The system performs preliminary processing and feature extraction before the main analysis. By pre-processing the data and preparing it in advance, the system reduces the computational burden during real-time prediction, thereby decreasing processing time while preserving prediction accuracy.
3Loss of information
If comprehensive data processing is performed to reduce ambiguity, then the decision-making quality improves, but the device complexity increases
Solution Approach 1:
The patent introduces contextual analysis as an intermediary layer between raw data and final predictions. This contextual module mediates by providing background information and situational context that disambiguates data without requiring complex processing of every raw data point, thus reducing ambiguity while managing complexity through layered processing.
Data Source
AI summary
The method solves several problems to assist the investigation of human activities, by creating a human activities set of objects, by using an advanced mathematic computation algorithm and a time-based n-dimensional space-curves formula Fi algorithm, by using matrices calculus and tensors calculus, by incorporating artificial intelligence analysis in combination with logic and contextual analysis to create a time-based human activities universal processor. The method extracts time-based escalating risk and priority concepts, anomalous understanding and time-based ranking information, generating action to take, identifying present and predicting future object position, motion and behavior. When, this method is loaded as an application on an automotive and a machine, the method will be at home replacing a human.