Abstract: A method, computer system, and a computer program product for product safety is provided. The present invention may include mapping one or more products within a smart container by identifying each of the one or more products and determining a location for each of the one or more products. The present invention may include determining a safety level for each of the one or more products. The present invention may include determining a recommended location to store a new product within the smart container based on a safety confidence score, wherein the safety confidence score is determined based on at least the safety score of the one or more products within the smart container, the safety score of the new product, and a machine learning model. The present invention may include displaying the recommended location to a user.

Abstract: A processor may receive an information dataset. The information dataset may include geographical area information and electronic waste information. A processor may generate a digital twin of the physical geographical area. The digital twin may be based, at least in part, on the information dataset. A processor may simulate one or more factors on the physical geographical area. A processor may predict, responsive to simulating the one or more factors, one or more electronic waste impacts on the physical geographical area.

Abstract: An approach is disclosed that is performed by a pair of smart glasses worn by a user that includes an information handling system that includes a processor and a memory. The approach receives input cues at input components of the smart glasses. Input components include a digital camera that is included in the smart glasses and accessible by the processor, a microphone that is included in the smart glasses and accessible by the processor. The received cues are analyzed resulting in one or more output cues focused on assisting the user. These output cues are transmitted through one or more output components of the smart glasses. One of the output components is a display on the inside of a lens included in the smart glasses.

Abstract: The present disclosure includes digitizing user symptoms. A processor may receive user provided data from one or more data collection devices. A processor may access a historical database. The historical database may include historical user provided data. A processor may generate a user data packet based, at least in part on, the user provided data and the historical database. A processor may display the user data packet to one or more authorized user and one or more other correlating information.

Abstract: A method, computer system, and a computer program product for product safety is provided. The present invention may include mapping one or more products within a smart container by identifying each of the one or more products and determining a location for each of the one or more products. The present invention may include determining a safety level for each of the one or more products. The present invention may include determining a recommended location to store a new product within the smart container based on a safety confidence score, wherein the safety confidence score is determined based on at least the safety score of the one or more products within the smart container, the safety score of the new product, and a machine learning model. The present invention may include displaying the recommended location to a user.

Abstract: A method, apparatus, system, and computer program product for processing electronic resumes. Classifications are identified for sections in the electronic resume. Resume classification codes are associated with the sections based on the classifications identified, wherein the resume classification codes enable matching the electronic resume to a job opening. Visibility codes are generated for the sections. The visibility codes enable selective viewing of the sections.

Abstract: A method, apparatus, system, and computer program product for processing electronic resumes. Classifications are identified for sections in the electronic resume. Resume classification codes are associated with the sections based on the classifications identified, wherein the resume classification codes enable matching the electronic resume to a job opening. Visibility codes are generated for the sections. The visibility codes enable selective viewing of the sections.