17948621. ENERGY OPTIMIZATION PLATFORM USING ARTIFICIAL INTELLIGENCE AND EDGE COMPUTING simplified abstract (Bank of America Corporation)
ENERGY OPTIMIZATION PLATFORM USING ARTIFICIAL INTELLIGENCE AND EDGE COMPUTING
Organization Name
Inventor(s)
Maharaj Mukherjee of Poughkeepsie NY (US)
George Albero of Charlotte NC (US)
Jinna Kim of Charlotte NC (US)
ENERGY OPTIMIZATION PLATFORM USING ARTIFICIAL INTELLIGENCE AND EDGE COMPUTING - A simplified explanation of the abstract
This abstract first appeared for US patent application 17948621 titled 'ENERGY OPTIMIZATION PLATFORM USING ARTIFICIAL INTELLIGENCE AND EDGE COMPUTING
Simplified Explanation
The abstract of the patent application describes a system for energy optimization in edge computing. Here is a simplified explanation of the abstract:
- A computing platform receives an event processing request.
- The platform identifies parameters of the request.
- The platform inputs the parameters into a global energy optimization model to determine the edge computing system for processing.
- The event processing request is routed to the identified edge computing system along with commands to process using a local energy optimization model specific to that system.
Potential Applications: This technology can be applied in various industries such as IoT, smart cities, and industrial automation for efficient energy usage in edge computing systems.
Problems Solved: This technology addresses the challenge of optimizing energy consumption in edge computing systems, leading to cost savings and improved performance.
Benefits: The system helps in reducing energy consumption, optimizing processing of event requests, and enhancing overall efficiency in edge computing environments.
Potential Commercial Applications: One potential commercial application of this technology could be in the development of energy-efficient edge computing solutions for smart homes and buildings.
Possible Prior Art: One possible prior art could be research papers or patents related to energy optimization in cloud computing or IoT devices.
Unanswered Questions: 1. How does the system ensure the security and privacy of data processed in edge computing systems? 2. What are the scalability limitations of this energy optimization model when applied to a large number of edge computing systems?
Original Abstract Submitted
Aspects of the disclosure relate to energy optimization. A computing platform may receive an event processing request. The computing platform may identify parameters of the event processing request. The computing platform may input the parameters into a global energy optimization model, to identify an edge computing system at which to process the event processing request. The computing platform may route the event processing request to the edge computing system along with commands to process the event processing request using an energy mix identified by a local energy optimization model, corresponding to the edge computing system, which may cause the edge computing system to: input the parameters of the event processing request into the local energy optimization model to identify the energy mix, and process, using the energy mix, the event processing request.
