International business machines corporation (20240190469). EXTERNAL DATA COLLECTION BASED ON PREDICTED DATA INSUFFICIENCY simplified abstract
Contents
- 1 EXTERNAL DATA COLLECTION BASED ON PREDICTED DATA INSUFFICIENCY
- 1.1 Organization Name
- 1.2 Inventor(s)
- 1.3 EXTERNAL DATA COLLECTION BASED ON PREDICTED DATA INSUFFICIENCY - A simplified explanation of the abstract
- 1.4 Simplified Explanation
- 1.5 Key Features and Innovation
- 1.6 Potential Applications
- 1.7 Problems Solved
- 1.8 Benefits
- 1.9 Commercial Applications
- 1.10 Questions about the Technology
- 1.11 Original Abstract Submitted
EXTERNAL DATA COLLECTION BASED ON PREDICTED DATA INSUFFICIENCY
Organization Name
international business machines corporation
Inventor(s)
Tiberiu Suto of Franklin NY (US)
Martin G. Keen of Cary NC (US)
Jeremy R. Fox of Georgetown TX (US)
Sarbajit K. Rakshit of Kolkata (IN)
EXTERNAL DATA COLLECTION BASED ON PREDICTED DATA INSUFFICIENCY - A simplified explanation of the abstract
This abstract first appeared for US patent application 20240190469 titled 'EXTERNAL DATA COLLECTION BASED ON PREDICTED DATA INSUFFICIENCY
Simplified Explanation
The patent application describes a method for predicting data insufficiency in autonomous vehicles and mitigating it by collecting external data from additional sources.
- The processor directs actions for the autonomous vehicle based on external data.
- Contextual data about the vehicle's environment is collected to predict data insufficiency.
- Additional external data is collected from a second data source to address the predicted insufficiency.
Key Features and Innovation
- Predicting data insufficiency in autonomous vehicles.
- Mitigating data insufficiency by collecting external data.
- Using contextual data to predict insufficiency.
- Directing actions based on collected external data.
Potential Applications
This technology can be applied in autonomous vehicles, robotics, and other AI-driven systems that require real-time data for decision-making.
Problems Solved
- Addressing data insufficiency in autonomous vehicle operations.
- Enhancing the reliability and safety of autonomous systems.
- Improving decision-making processes in dynamic environments.
Benefits
- Increased accuracy and efficiency in autonomous vehicle actions.
- Enhanced safety and reliability in autonomous operations.
- Real-time data collection for improved decision-making.
Commercial Applications
- Autonomous vehicle industry for enhanced safety and efficiency.
- Robotics sector for real-time data collection and decision-making.
- AI-driven systems for improved performance and reliability.
Questions about the Technology
How does this technology improve the safety of autonomous vehicles?
This technology enhances safety by predicting data insufficiency and collecting additional external data to ensure accurate decision-making.
What are the potential applications of this innovation beyond autonomous vehicles?
This innovation can be applied in various industries such as robotics, AI-driven systems, and any technology requiring real-time data for operations.
Original Abstract Submitted
provided is a computer-implemented method, system, and computer program product for predicting data insufficiency related to performing autonomous vehicle actions and dynamically mitigating the data insufficiency by collecting external data from additional data sources. a processor may direct, for an autonomous vehicle, an action in response to external data. the processor may collect contextual data about an environment in which the autonomous vehicle is operating. the processor may predict, based in part on the collected contextual data, an insufficiency of external data for performing the action. in response to the predicting, the processor may direct collection of additional external data from a second data source.
