18011923. Analyzing Travel Metrics simplified abstract (GOOGLE LLC)
Contents
Analyzing Travel Metrics
Organization Name
Inventor(s)
Yan Borisovich Mayster of Aurora CO (US)
Bruce Bahnsen of Boulder CO (US)
Analyzing Travel Metrics - A simplified explanation of the abstract
This abstract first appeared for US patent application 18011923 titled 'Analyzing Travel Metrics
The technology described in the patent application is a method for predicting travel metrics for a user based on their starting location and travel history. This includes metrics such as time of travel, distance traveled, expenses, and carbon footprint.
- Predict travel metrics based on starting location and user's travel history
- Metrics may include time of travel, distance traveled, expenses, carbon footprint, etc.
- Travel history is based on location information detected by a device with location sensors
- Identify relevant destinations and routine trips to determine predicted travel metrics
- Improve travel planning and decision-making for users
Potential Applications: - Personalized travel planning apps - Environmental impact assessment tools - Business travel expense management systems
Problems Solved: - Lack of personalized travel predictions - Inefficient travel planning processes - Limited visibility into travel expenses and carbon footprint
Benefits: - Enhanced user experience - Cost savings on travel expenses - Reduced carbon footprint - Improved sustainability practices
Commercial Applications: Title: Personalized Travel Prediction Technology for Enhanced User Experience This technology can be utilized in travel planning apps, expense management systems, and sustainability platforms to offer personalized predictions and insights for users, improving their overall travel experience.
Questions about the technology: 1. How does this technology improve travel planning for users? 2. What are the key benefits of predicting travel metrics based on user history?
Frequently Updated Research: Stay updated on the latest advancements in travel prediction technology and its impact on user experience, sustainability, and cost savings.
Original Abstract Submitted
The technology generally relates to a method for predicting travel metrics for a user for a predetermined time period based on a starting location and the user's travel history. The predicted travel metrics may include, for example, a time of travel, a distance traveled, travel expenses, carbon footprint, etc. The travel history may be based on location information detected by a device having location sensors. The location information may be used to identify relevant destinations frequented by the user and routine trips completed by the user. The identified destinations and trips may be used to determine predicted travel metrics.
