Abstract: A device may receive and process client data, with a first machine learning model, to determine current state data identifying a current state of a client. The device may process the current state data and prior client data, with a second machine learning model, to determine a problem statement for the client and future state data of the client. The device may utilize the second machine learning model to identify initiatives for the client, and costs of the initiatives, based on the problem statement, the current state data, and the future state data, and to assign benefits and priorities to the initiatives. The device may process the initiatives, the benefits and priorities of the initiatives, and the costs of the initiatives, with the second machine learning model, to generate an initiative plan for solving a problem of the problem statement, and may perform actions based on the initiative plan.

Abstract: A system and method of identifying potential areas for mineral extraction is disclosed. The proposed systems and methods describe an autonomous mineral discovery platform that leverages robotics, X-Ray Florescence (XRF) technology, image analytics, smart devices, and IoT enabled devices to perform comprehensive field surveying and exploratory sampling. For example, by implementation of remote navigation and control, as well as field data capture and real-time data transmission capabilities, this platform can be configured to automatically identify rock types and their surface features and perform elemental composition analysis of surface while on-site and remote from the operator site.

Abstract: A system and method of identifying potential areas for mineral extraction is disclosed. The proposed systems and methods describe an autonomous mineral discovery platform that leverages robotics, X-Ray Florescence (XRF) technology, image analytics, smart devices, and IoT enabled devices to perform comprehensive field surveying and exploratory sampling. For example, by implementation of remote navigation and control, as well as field data capture and real-time data transmission capabilities, this platform can be configured to automatically identify rock types and their surface features and perform elemental composition analysis of surface while on-site and remote from the operator site.

Abstract: According to an example, with respect to blast reconciliation for mines, pre blast measurement data and post blast measurement data associated with a blasting operation for a mining site may be ascertained from a pre and post blast measurer. A blast reconciliation model may be generated using existing pre blast measurement data and existing post blast measurement data, and used to analyze the ascertained pre blast measurement data and the ascertained post blast measurement data. Based on the analysis of the ascertained pre blast measurement data and the ascertained post blast measurement data, a blast material yield for the mining site may be determined as a result of the blasting operation. An alert indicative of the blast material yield may be generated.

Abstract: According to an example, with respect to blast reconciliation for mines, pre blast measurement data and post blast measurement data associated with a blasting operation for a mining site may be ascertained from a pre and post blast measurer. A blast reconciliation model may be generated using existing pre blast measurement data and existing post blast measurement data, and used to analyze the ascertained pre blast measurement data and the ascertained post blast measurement data. Based on the analysis of the ascertained pre blast measurement data and the ascertained post blast measurement data, a blast material yield for the mining site may be determined as a result of the blasting operation. An alert indicative of the blast material yield may be generated.

Abstract: A business tool is disclosed to assess the operational capability of an organization. A framework is provided for a user to provide information from various sources, including a particular industry, a particular function, competition and research. An assessment of actual and desired scores defining the competitive essence is made, within each capability of a function, to come up with a collective number per function based on intra-function weight. This is followed by allocation of inter-function weight. Calculations of desired and actual scores are performed for the organization. The variance is reverse scaled to calculate the number for operational excellence. Where the actual number lacks the desired number, business insights and improvement opportunities are identified along with key tools. Where the desired number trails the actual number, optimization opportunities are identified.