Micron technology, inc. (20240185067). DRIVING REPORT GENERATION USING A DEEP LEARNING DEVICE simplified abstract
Contents
- 1 DRIVING REPORT GENERATION USING A DEEP LEARNING DEVICE
- 1.1 Organization Name
- 1.2 Inventor(s)
- 1.3 DRIVING REPORT GENERATION USING A DEEP LEARNING DEVICE - 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 Prior Art
- 1.11 Frequently Updated Research
- 1.12 Questions about Deep Learning Device for Vehicle Report Generation
- 1.13 Original Abstract Submitted
DRIVING REPORT GENERATION USING A DEEP LEARNING DEVICE
Organization Name
Inventor(s)
Saideep Tiku of Folsom CA (US)
DRIVING REPORT GENERATION USING A DEEP LEARNING DEVICE - A simplified explanation of the abstract
This abstract first appeared for US patent application 20240185067 titled 'DRIVING REPORT GENERATION USING A DEEP LEARNING DEVICE
Simplified Explanation
Methods, systems, and devices for generating reports using a deep learning device in a vehicle are described. The vehicle uses sensor data and a deep learning device to provide reports to the driver based on the environment and events identified.
- The vehicle collects data from sensors and stores inputs in memory.
- Processing units generate a model of the environment using the stored sensory inputs.
- The vehicle identifies events using the model and sensory inputs.
- A deep learning device is used to generate event reports based on machine learning models and inputs.
Key Features and Innovation
- Utilizes sensor data and deep learning for report generation in vehicles.
- Models the environment using stored sensory inputs.
- Identifies events and generates reports using machine learning models.
- Enhances driver awareness and safety through timely reports.
Potential Applications
This technology can be applied in various industries such as automotive, transportation, and logistics for real-time reporting and decision-making.
Problems Solved
- Improves driver awareness by providing timely reports.
- Enhances safety by identifying events in the vehicle's environment.
- Enables proactive maintenance based on generated reports.
Benefits
- Increased driver safety and awareness.
- Real-time reporting for better decision-making.
- Proactive maintenance to prevent potential issues.
Commercial Applications
- "Deep Learning Device for Vehicle Report Generation" can be used in automotive fleets for real-time monitoring and maintenance scheduling, enhancing operational efficiency and safety.
Prior Art
No prior art information available at this time.
Frequently Updated Research
No frequently updated research available at this time.
Questions about Deep Learning Device for Vehicle Report Generation
Question 1
How does the deep learning device in vehicles improve driver awareness and safety?
The deep learning device in vehicles enhances driver awareness and safety by analyzing sensor data to identify events in the vehicle's environment and generate timely reports for the driver.
Question 2
What are the potential applications of using deep learning devices for report generation in vehicles?
The potential applications of using deep learning devices for report generation in vehicles include real-time reporting, proactive maintenance, and enhanced decision-making in industries such as automotive, transportation, and logistics.
Original Abstract Submitted
methods, systems, and devices for driving report generation using a deep learning device are described. in some cases, a vehicle may use sensor data and a deep learning device to provide a report to a driver of the vehicle. the vehicle may collect data from vehicle sensors and store a set of inputs received from the sensors in a volatile memory device. one or more processing units coupled with the memory system of the vehicle system may generate a model associated with the environment of the vehicle using the stored sensory inputs. the vehicle may identify events using the model, the sensory inputs or both. in some examples, the vehicle may employ a deep learning device to generate an event report using a machine learning model and the set of inputs.
