Unknown Organization (20240311425). Systems and methods for multi-domain inference simplified abstract
Contents
Systems and methods for multi-domain inference
Organization Name
Inventor(s)
Moshe Salhov of Herzeliya (IL)
Systems and methods for multi-domain inference - A simplified explanation of the abstract
This abstract first appeared for US patent application 20240311425 titled 'Systems and methods for multi-domain inference
The abstract describes a system and method for multi-domain AI predictions using imagery data from on-road vehicles to analyze interactions between various object categories over an extended period.
- Leveraging imagery data captured by a large network of on-road vehicles
- Analyzing interactions between diverse object categories such as individuals, organizations, structures, vehicles, and wearable devices
- Accumulating vast amounts of data and employing advanced machine learning to train a predictive model
- Understanding complex relationships and drawing inferences across multiple domains including social dynamics, transportation, infrastructure, and consumer behavior
- Predicting physical events and complex human behaviors like emotions, intentions, and social connections
Potential Applications: - Traffic management and optimization - Urban planning and development - Market research and consumer behavior analysis
Problems Solved: - Enhancing predictive capabilities across multiple domains - Understanding complex human behaviors and interactions - Improving decision-making processes based on AI predictions
Benefits: - Increased accuracy in predicting events and behaviors - Enhanced understanding of social dynamics and consumer behavior - Improved efficiency in various domains such as transportation and urban planning
Commercial Applications: Title: Multi-Domain AI Predictions System for Enhanced Decision-Making This technology can be utilized in industries such as transportation, urban planning, market research, and consumer behavior analysis to improve predictive capabilities and decision-making processes.
Questions about Multi-Domain AI Predictions System: 1. How does this system improve upon traditional predictive models? This system enhances predictive capabilities by leveraging vast amounts of imagery data and advanced machine learning techniques to understand complex relationships and draw inferences across multiple domains.
2. What are the key benefits of using this system in urban planning and development? Using this system in urban planning can lead to more efficient infrastructure development, optimized traffic management, and improved understanding of social dynamics within cities.
Original Abstract Submitted
system and method for multi-domain ai predictions leveraging imagery data captured by a large network of on-road vehicles. the system analyzes interactions between diverse object categories, including individuals, organizations, structures, vehicles, and wearable devices, over an extended period. by accumulating vast amounts of data and employing advanced machine learning, a predictive model is trained to understand complex relationships and draw inferences across multiple domains, such as social dynamics, transportation, infrastructure, and consumer behavior. the system and method aim to predict not only physical events but also complex human behaviors, including emotions, intentions, and social connections.
