18060326. APPARATUSES, METHODS, AND COMPUTER PROGRAM PRODUCTS FOR CONTEXT-CONSCIOUS SENSOR SIGNATURE PROFILING WITH IMPRESSION ACQUISITION AND SCAVENGING simplified abstract (Honeywell International Inc.)
Contents
- 1 APPARATUSES, METHODS, AND COMPUTER PROGRAM PRODUCTS FOR CONTEXT-CONSCIOUS SENSOR SIGNATURE PROFILING WITH IMPRESSION ACQUISITION AND SCAVENGING
- 1.1 Organization Name
- 1.2 Inventor(s)
- 1.3 APPARATUSES, METHODS, AND COMPUTER PROGRAM PRODUCTS FOR CONTEXT-CONSCIOUS SENSOR SIGNATURE PROFILING WITH IMPRESSION ACQUISITION AND SCAVENGING - A simplified explanation of the abstract
- 1.4 Simplified Explanation
- 1.5 Potential Applications
- 1.6 Problems Solved
- 1.7 Benefits
- 1.8 Potential Commercial Applications
- 1.9 Possible Prior Art
- 1.10 Original Abstract Submitted
APPARATUSES, METHODS, AND COMPUTER PROGRAM PRODUCTS FOR CONTEXT-CONSCIOUS SENSOR SIGNATURE PROFILING WITH IMPRESSION ACQUISITION AND SCAVENGING
Organization Name
Inventor(s)
Bhabesh Chandra Acharya of Bangalore (IN)
Manu Taranath of Bangalore (IN)
APPARATUSES, METHODS, AND COMPUTER PROGRAM PRODUCTS FOR CONTEXT-CONSCIOUS SENSOR SIGNATURE PROFILING WITH IMPRESSION ACQUISITION AND SCAVENGING - A simplified explanation of the abstract
This abstract first appeared for US patent application 18060326 titled 'APPARATUSES, METHODS, AND COMPUTER PROGRAM PRODUCTS FOR CONTEXT-CONSCIOUS SENSOR SIGNATURE PROFILING WITH IMPRESSION ACQUISITION AND SCAVENGING
Simplified Explanation
The patent application describes a method for generating sensor characteristic profiles for different sensor types based on aggregated time series sensor data and context data. These profiles are stored in a database and used to generate sensor information and device characteristic profiles.
- Sensor characteristic profiles are generated based on aggregated time series sensor data and context data.
- Profiles are stored in a database for each sensor type.
- Information about specific sensors is determined using sample sensor data and stored profiles.
- Device characteristic profiles and virtual sensor characteristic profiles can be generated based on the stored sensor profiles.
Potential Applications
This technology could be applied in various industries such as:
- IoT (Internet of Things) systems
- Smart home devices
- Industrial automation
Problems Solved
This technology helps in:
- Efficient sensor data analysis
- Improved sensor performance monitoring
- Enhancing system reliability and accuracy
Benefits
The benefits of this technology include:
- Better understanding of sensor behavior
- Enhanced system optimization
- Real-time monitoring and control capabilities
Potential Commercial Applications
Potential commercial applications of this technology could include:
- Sensor manufacturers
- IoT solution providers
- Industrial automation companies
Possible Prior Art
One possible prior art could be the use of machine learning algorithms for sensor data analysis in operational systems.
Unanswered Questions
How does this technology improve sensor data accuracy and reliability?
This technology improves sensor data accuracy and reliability by creating specific profiles for each sensor type, allowing for better understanding and monitoring of sensor behavior.
What are the limitations of this technology in terms of scalability?
The scalability of this technology may be limited by the amount of data that can be processed and stored in the sensor type profile database. Additional research may be needed to address scalability issues for large-scale sensor networks.
Original Abstract Submitted
Sensor characteristic profiles for different sensor types for sensors of an operational system are generated based at least in part on aggregated time series sensor data from the sensors and context data for the sensors. The sensor characteristic profiles for each sensor type are stored in a sensor type profile database. Sensor information is generated based at least in part on the stored sensor characteristic profiles. Each of the sensor characteristic profiles comprises sensor type information identifying the sensor type and a sensor data signature for the sensor type. Sample sensor data from a particular sensor is used to determine information about the particular sensor based on the stored sensor characteristic profiles. Device characteristic profiles for different device types and/or virtual sensor characteristic profiles for different virtual sensors defined with respect to particular combinations of the sensors can be generated based on the stored sensor characteristic profiles.
