estatefert.blogg.se - Anomaly 2 ui design

Supports any cloud provider (AWS, Azure, Google, etc.), used by organizations.Ī-Gnostics may be deployed at a company’s data centers. Secured cloud environment, based on a subscription model.

Software-as-a-Service / Model-as-a-ServiceĪpproach allows the client to connect and use the platform’s services from our.

Infrastructure, in terms of where the services may be deployed and launched.Ī-Gnostics supports multiple deployment and consumption models: Principles and advantages of the a-Gnostic platform is its independent Presenting dashboards and metrics to end users.

API - an enabler for a-Gnostics servicesĬonsumption by external systems, analytical platforms, and out-of-the-box UI.

Storage - a scalable cloud or on-premisesĪutomated data retrieval, validation, and cleansing in preparation to.

Top-level a-Gnostics architectureĪbove shows the high-level architecture of the a-Gnostics platform (the mostĬhallenging tasks are shown in orange on the diagram).Ĭomposed of the following functional components:

The a-Gnostics platform addresses all these challenges via the abundance of out-of-the-box features and customization capabilities that allow tailoring the services to client’s needs. More complexity is added with high security, compliance, data, and model governance requirements. A flexible infrastructure that can scale proportionally to host the data and execute hundreds and thousands of models is also essential. One of the main challenges of industrial AI/ML solutions is a need to process a variety of data from different sources. For example, a recently added a-Gnostics service is the solution to electrical motor failures using failure prediction to help manufacturers reduce costs of repairs and maintenance. The list of services is getting extended based on new use cases and implementations of industrial AI and machine learning. Predictive analytics for industrial equipment, such as boilers at thermal power Failure prediction, anomaly detection, and.Generation, with the accuracy of up to 90%. (electricity and natural gas) consumption by large factories, with about 95%

The forecasting of electricity consumption byĬounties and regions, with 96–99% accuracy.Variety of services known as A-SETS that are offered to the customers by theįall into the following high-level categories: Failure Prediction service at a-Gnostics DataDome The main objective is to apply machine learning and artificial intelligence to predict failures before they occur. The service is tailored to multivariable processes and timeseries data, retrieved from industrial equipment to automatically and accurately indicate normal, pre-failure, and failure statuses. Anomaly Detection and Equipment Failure Prediction General BackgroundĪ-Gnostics, SoftElegance company, implements an Industrial AI service focused on anomaly detection and equipment failure prediction. We are excited to release a-Gnostics 2.0, the service for rapid development of predictive analytics models, and would like to share details about the platform architecture and the new features available in this release.