18055876. ARTIFICIAL INTELLIGENCE-BASED SUSTAINABILITY CONTROL simplified abstract (INTERNATIONAL BUSINESS MACHINES CORPORATION)
Contents
- 1 ARTIFICIAL INTELLIGENCE-BASED SUSTAINABILITY CONTROL
- 1.1 Organization Name
- 1.2 Inventor(s)
- 1.3 ARTIFICIAL INTELLIGENCE-BASED SUSTAINABILITY CONTROL - 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
ARTIFICIAL INTELLIGENCE-BASED SUSTAINABILITY CONTROL
Organization Name
INTERNATIONAL BUSINESS MACHINES CORPORATION
Inventor(s)
Gary Zasman of Boulder CO (US)
Mansura Habiba of Jhonstown (IE)
ARTIFICIAL INTELLIGENCE-BASED SUSTAINABILITY CONTROL - A simplified explanation of the abstract
This abstract first appeared for US patent application 18055876 titled 'ARTIFICIAL INTELLIGENCE-BASED SUSTAINABILITY CONTROL
Simplified Explanation
The abstract describes a patent application related to autonomous sustainability control for achieving a functional objective. Here is a simplified explanation of the abstract:
- Data from various sources is normalized to train an artificial intelligence model.
- The AI model learns dynamic key performance indicators linking functional objective performance to sustainability.
- Anomalies are identified using the learned indicators, and corrective actions are generated to mitigate associated risks.
- These actions enable autonomous sustainability control in achieving the functional objective.
Potential Applications
The technology described in the patent application could be applied in various industries such as manufacturing, energy production, transportation, and agriculture to optimize sustainability practices while achieving operational goals.
Problems Solved
This technology addresses the challenge of balancing performance objectives with sustainability goals by providing a systematic approach to identify and mitigate risks through autonomous control mechanisms.
Benefits
The benefits of this technology include improved sustainability practices, enhanced operational efficiency, reduced environmental impact, and proactive risk management through autonomous decision-making.
Potential Commercial Applications
The potential commercial applications of this technology include smart manufacturing systems, sustainable energy management solutions, precision agriculture platforms, and intelligent transportation systems, all aimed at optimizing performance while ensuring sustainability.
Possible Prior Art
One possible prior art could be existing systems that use artificial intelligence for performance optimization or sustainability management in specific industries. However, the specific combination of dynamic key performance indicators and autonomous control for sustainability in achieving a functional objective may be unique to this patent application.
What are the technical specifications of the artificial intelligence model used in the patent application?
The technical specifications of the artificial intelligence model, such as the architecture, training data, hyperparameters, and validation methods, are not detailed in the abstract. Further information would be needed to understand the specific implementation of the AI model in this context.
How does the patent application ensure data privacy and security when collecting and processing information from heterogeneous sources?
The abstract does not mention specific measures for data privacy and security in handling heterogeneous data sources. It would be important to explore how the patent application addresses these concerns to protect sensitive information and comply with data regulations.
Original Abstract Submitted
Autonomous sustainability control is provided related to performing a functional objective. Normalized data is obtained from heterogeneous data obtained from a plurality of data sources, where the heterogeneous data is related, at least in part, to the functional objective. The normalized data is used to train an artificial intelligence model to learn dynamic key performance indicators relating, at least in part, performance of the functional objective to sustainability. The artificial intelligence model is used to learn a set of dynamic key performance indicators to relate current performance of the functional objective to sustainability. The learned set of dynamic key performance indicators is used to identify an anomaly, and one or more corrective actions are generated to remediate a risk associated with the anomaly. The one or more actions facilitate the autonomous sustainability control related to performing the functional objective.
