Qualcomm incorporated (20240303118). Managing Vehicle Computing Resources simplified abstract
Contents
- 1 Managing Vehicle Computing Resources
- 1.1 Organization Name
- 1.2 Inventor(s)
- 1.3 Managing Vehicle Computing Resources - A simplified explanation of the abstract
- 1.4 Simplified Explanation
- 1.5 Potential Applications
- 1.6 Problems Solved
- 1.7 Benefits
- 1.8 Commercial Applications
- 1.9 Questions about Vehicle Computing Resources
- 1.10 Original Abstract Submitted
Managing Vehicle Computing Resources
Organization Name
Inventor(s)
Kapil Gulati of Belle Mead NJ (US)
Hong Cheng of Basking Ridge NJ (US)
Shailesh Patil of San Diego CA (US)
Gene Wesley Marsh of San Diego CA (US)
Managing Vehicle Computing Resources - A simplified explanation of the abstract
This abstract first appeared for US patent application 20240303118 titled 'Managing Vehicle Computing Resources
Simplified Explanation
The patent application discusses methods and systems for identifying vehicle computing resources that can be used to support remote computing systems with edge computing services. It involves selecting available computing capacity in a vehicle computing system based on its operating state and offering this capacity to perform computing tasks from a network computing device.
- Identifying vehicle computing resources with capacity for edge computing services
- Selecting available computing capacity based on the operating state of the vehicle computing system
- Offering the available computing capacity to perform computing tasks from a network computing device
- Storing predetermined available computing capacity in a data table in memory
- Identifying the operating state by receiving information on system functions being performed
Potential Applications
This technology could be applied in various industries such as autonomous vehicles, smart transportation systems, and remote monitoring systems where edge computing services are required.
Problems Solved
This technology addresses the need for efficient utilization of vehicle computing resources to support remote computing systems with edge computing services.
Benefits
The benefits of this technology include optimized use of vehicle computing resources, improved performance of remote computing systems, and enhanced edge computing services.
Commercial Applications
- Optimizing computing resources in autonomous vehicles
- Enhancing edge computing services in smart transportation systems
- Improving remote monitoring systems with efficient computing capacity utilization
Questions about Vehicle Computing Resources
How does this technology impact the efficiency of edge computing services?
This technology improves the efficiency of edge computing services by offering available computing capacity from vehicle computing resources based on their operating state.
What are the potential implications of this technology in the development of autonomous vehicles?
This technology could significantly enhance the development of autonomous vehicles by optimizing computing resources for edge computing services.
Original Abstract Submitted
various embodiments include methods and systems for identifying vehicle computing resources with capacity that can be offered to support remote computing systems with edge computing services. various embodiments may include identifying an operating state of a vehicle computing system not responsible for vehicle navigation or maneuvering, selecting an available computing capacity of the computing system based on the identified operating state, and offering the available computing capacity of the computing system to perform a computing task received from a network computing device. in some embodiments, selecting an available computing capacity of the computing system may include identifying a predetermined available computing capacity of the computing system corresponding to the identified operating state in a data table stored in memory. in some embodiments, identifying the operating state of the computing system may include receiving information regarding which of a limited number of system functions that the computing system is performing.
