Versatile and convenient safety management of a construction machine is achieved. Construction machines and workers are photographed by a camera of a surveying apparatus. The images of a construction machine and a worker are identified in the photographic image. The positions of the construction machine and the worker that are identified in the photographic image are measured by the surveying apparatus with the use of laser light. The separation distance between the construction machine and the worker in which the positions are measured is calculated. In the case in which the calculated separation distance is at a threshold or less, a warning is issued to the construction machines and the workers.

An industrial work order analysis system applies statistical and machine learning analytics to both open and closed work orders to identify problems and abnormalities that could impact manufacturing and maintenance operations. The analysis system applies algorithms to learn normal maintenance behaviors or characteristics for different types of maintenance tasks and to flag abnormal maintenance behaviors that deviate significantly from normal maintenance procedures. Based on this analysis, embodiments of the work order analysis system can identify unnecessarily costly maintenance procedures or practices, as well as predict asset failures and offer enterprise-specific recommendations intended to reduce machine downtime and optimize the maintenance process.

The exemplary embodiments disclose a method, a computer program product, and a computer system for managing environment change. The exemplary embodiments may include determining a plurality of change and risk models for a plurality of computing environments, generating a plurality of association rules based on the plurality of change and risk models, and generating a joint association rule by combining at least two of the plurality of association rules, wherein the joint association rule indicates, from the three dimensions, an association relationship between changes and risk events over at least a part of the time series.

A computer-implemented method is provided for training a supervised machine learning engine able to predict characteristics of aircraft trajectories from parameters of an aircraft, and environment parameters of the aircraft trajectory. A system able to train the supervised machine learning engine, a system for using the engine, and a computer-implemented method for using the engine are provided. The methods and systems provided are particularly useful for air traffic flow management applications.

A system and method for providing real-time distributed micro-grid optimization using price signals to the electrical grid system by allowing bi-directional electricity usage from a distributed network of energy storage stations to form a large, distributed resource for the grid. A machine learning optimization module ingests various forms of data-from grid telemetry to traffic data to trip-to-trip data and more-in order to make informed spatiotemporal decisions about optimal pricing signals as well as strategically placing and balancing energy stores across various regions to support optimum energy usage, risk mitigation, grid fortification, and revenue generation. Energy stores are then sent updated price signals and updated parameters as to the amount of energy to hold or release.

Contracts are a fundamental tool for coordinating economic activity and need to be managed throughout the lifecycle of contracts. The existing methods are incomplete, expensive, time-consuming, and error-prone. A method and system for management of lifecycle of contracts have been provided. The system leverages a combination of artificial intelligence (AI) techniques appropriate for different micro services in contract lifecycle management. The deep learning and natural language processing (NLP) techniques help in understanding of clauses of the contract, risk levels involved in the contract. The system is configured to automatically generate contracts for a customer based on the other criteria of the customer. The system also identifies alternate options to risky clauses and mandatory clauses to be included. The system is also configured to manage the workflows based on context of contract to seek exception approvals from appropriate stakeholders during contract creation and alert appropriate stakeholders on delivery governance issues.

The embodiment herein provides a system and a method for assessing a cyber-risk and loss in a cloud infrastructure includes (a) deriving at least one of asset, topology, network or authentication vulnerabilities of a cloud infrastructure, (b) generating a technology risk machine learning model and a technology risk index, (c) generating a compliance risk machine learning model and a compliance risk, (d) generating a ransomware machine learning model and a business risk by processing (i) the compliance risk machine learning model and the compliance risk, (ii) a business input comprising asset information, cash flow, a value of the asset, (e) determining an asset's ransomware risk and loss based on the business risk and (f) automatically enabling one or more actions to mitigate the asset's ransomware risk and loss by fix misconfigurations or upgrading software using an API of cloud infrastructure.

The embodiment herein provides a system and a method for assessing a cyber-risk and loss in a cloud infrastructure includes (a) deriving at least one of asset, topology, network or authentication vulnerabilities of a cloud infrastructure, (b) generating a technology risk machine learning model and a technology risk index, (c) generating a compliance risk machine learning model and a compliance risk, (d) generating a ransomware machine learning model and a business risk by processing (i) the compliance risk machine learning model and the compliance risk, (ii) a business input comprising asset information, cash flow, a value of the asset, (e) determining an asset's ransomware risk and loss based on the business risk and (f) automatically enabling one or more actions to mitigate the asset's ransomware risk and loss by fix misconfigurations or upgrading software using an API of cloud infrastructure.

A system for predictive holistic facility management is provided including a sensor in electronic communication with a processor, a non-transitory computer-readable storage medium in electronic communication with the processor having instructions stored thereon that, in response to execution by the processor, cause the processor to perform operations comprising, receiving, at the processor, first data related to a building from the sensor, receiving, at the processor, second data related to a state of the building, calculating, by the processor, a PC Ratio of the building based upon the first data and the second data, and/or allocating, by the processor, a predetermined capital expenditure and operating expenditure budget to the building based upon the PC Ratio.

A system for predictive holistic facility management is provided including a sensor in electronic communication with a processor, a non-transitory computer-readable storage medium in electronic communication with the processor having instructions stored thereon that, in response to execution by the processor, cause the processor to perform operations comprising, receiving, at the processor, first data related to a building from the sensor, receiving, at the processor, second data related to a state of the building, calculating, by the processor, a PC Ratio of the building based upon the first data and the second data, and/or allocating, by the processor, a predetermined capital expenditure and operating expenditure budget to the building based upon the PC Ratio.