17493832. USING A PREDICTIVE MACHINE LEARNING TO DETERMINE STORAGE SPACES TO STORE ITEMS IN A STORAGE INFRASTRUCTURE simplified abstract (International Business Machines Corporation)
USING A PREDICTIVE MACHINE LEARNING TO DETERMINE STORAGE SPACES TO STORE ITEMS IN A STORAGE INFRASTRUCTURE
Organization Name
International Business Machines Corporation
Inventor(s)
Venkata Vara Prasad Karri of Visakhapatnam (IN)
Ramprasad Bhat of Bangalore (IN)
Saraswathi Sailaja Perumalla of Visakhapatnam (IN)
USING A PREDICTIVE MACHINE LEARNING TO DETERMINE STORAGE SPACES TO STORE ITEMS IN A STORAGE INFRASTRUCTURE - A simplified explanation of the abstract
This abstract first appeared for US patent application 17493832 titled 'USING A PREDICTIVE MACHINE LEARNING TO DETERMINE STORAGE SPACES TO STORE ITEMS IN A STORAGE INFRASTRUCTURE
Simplified Explanation
The patent application describes a computer program, system, and method for using predictive machine learning to determine storage spaces for items in a storage infrastructure. Here are the key points:
- The system uses information on the storage infrastructure, including physical configurations, usages, items placed, and a predictive model.
- The predictive model takes inputs such as attributes of a target item, physical configuration of storage spaces, attributes of the storage spaces, and usages of the storage spaces.
- The predictive model processes the inputs to output an available storage space that optimizes storage of the target item.
- An augmented reality representation of the storage information for the target item and the available storage space is generated on a computer display.
Potential applications of this technology:
- Warehouse management systems: The technology can be used to optimize storage of items in warehouses, improving efficiency and reducing errors.
- Retail inventory management: It can help retailers determine the best storage spaces for their products, ensuring easy access and efficient organization.
- Logistics and supply chain: The system can assist in determining the optimal storage spaces for items during transportation and distribution.
Problems solved by this technology:
- Inefficient storage: The technology helps solve the problem of inefficient storage by using predictive machine learning to determine the best storage spaces for items.
- Lack of organization: By optimizing storage spaces, the system helps solve the problem of disorganized storage, making it easier to locate and retrieve items.
- Wasted space: The technology helps eliminate wasted space by ensuring that storage spaces are utilized effectively.
Benefits of this technology:
- Improved efficiency: By optimizing storage spaces, the system improves efficiency in storage infrastructure, reducing time and effort required for locating and retrieving items.
- Enhanced organization: The technology helps in organizing storage spaces, making it easier to maintain an organized inventory.
- Cost savings: By utilizing storage spaces effectively and reducing wasted space, the system can lead to cost savings in storage infrastructure.
Original Abstract Submitted
Provided are a computer program product, system, and method for using a predictive machine learning to determine storage spaces to store items in a storage infrastructure. Information on the storage infrastructure indicates storage spaces in the storage infrastructure, including physical configurations of the storage spaces, usages of the storage spaces, items placed in the storage spaces, and a predictive model. The predictive model receives as inputs, attributes of a target item to add to the storage spaces, the physical configuration of the storage spaces, attributes of the storage spaces, and the usages of the storage spaces. The predictive model processes the inputs to output an available storage space to optimize storage of the target item. An augmented reality representation of information on storage of the target item with respect to the available storage space is generated on a computer display.
