LeapIOT provides more than 100 industrial & Big Data modules to support field data acquisition, industrial system connectivity, Big Data storage, Big Data computing engine, public & private cloud resource scheduling, script execution engine, AI service and visualization of data analysis. Besides, these modules can be further extended with the SDK packages to support new applications at the Edge and in the Platform.
LeapIOT provides a high-speed real-time computing engine. Through drag&drop the plug-ins onto the canvas, the user can flexibly design a data stream for data access, protocol conversion, format conversion etc. The distributed architecture ensures the efficiency of data processing at a speed of 100K recs/sec, handling the complex field industrial data acquisition and immediate data analysis.
Compared with the traditional database which can only support a full-quantity data acquisition and storage at a workshop-level, LeapIOT TSDB can afford a PB-level (Petabyte) data storage at an enterprise-level. TSDB realizes the aggregation and storage of industrial field data without archiving. It supports the online query for full-quantity data. In addition to these, it can take advantages of an AI model for the re-mining of industrial data asset.
Through the collaboration with other Lenovo products such as LeapHD, LeapOcean and LeapAI, LeapIOT can achieve an instant online analysis and application for the massive industrial data. For example, an AI model trained on LeapAI, can be invoked dynamically and instantly by an application at the Edge and the Platform. Thus, LeapIOT implements the intelligent transformation and the continuous optimization for traditional industrial equipment.
LeapIOT provides the online design, development and management of IoT applications. Through the visual management function of platform, the user can easily and quickly customize the IoT application for different scenarios to complete the processing such as equipment access, data acquisition, data forwarding, data modeling, etc. Through the simple configuration, the platform can implement the centralized management of assets and the access of industrial system to practice the industrial intelligence.
Edge Computing provides the access of industrial assets/systems, the protocol conversion and the acquisition of industrial data. It provides the on-site data computing, the data storage and data analysis. Through the lightweight edge framework running on the embedded industrial devices/gateways/servers, Edge Computing implements the connectivity of industrial asset and the industrial intelligence. It deploys the flexible computing rules, analytics algorithms and intelligent applications in terms of the computing resources.
Based on the distributed message architecture, Message Queue provides a message subscription & publication mechanism through MQTT.
Stream supports the visual processing for massive data, the access of multi-source and the output of multi-target. Besides, with the extensible plug-ins, Stream achieves various kinds of data connection, computing, scheduling and storage to meet the complex demand of industrial data processing. In the meantime, it ensures the accuracy of the real-time data by the statistics monitoring.
TSDB provides the high-efficient time series read/write, high compression-ratio and low-cost time series data storage, the visualization of query results a=nd even the meta-data query. TSDB is characterized by its high-efficiency, low-cost and high-stability.
Digital Twin is digital representations of physical assets and systems with object templates, properties and instances. It implements the real-time status query and the reverse control which can operate the physical device. It supports the RESTful API for 3rd party integration.
With various kinds of widgets like Graph, Table, Text, Row, and Dashboard List, Data Insight supports the data visualization within a dashboard. The users can drag and drop the widgets to customize the dashboard. What’s more, it supports different kinds of data source with real-time access & display, and it provides flexible report settings for a better view of data analysis.
maximize the utilization of equipment and tap the maximum production potential.
find and solve the bottleneck problem in process, improve the rate of good products and save cost.
make human resources and equipment cooperate scientifically to maximize their potential.
collect real-time data of production line, consult production status and understand production information.
provide objective and scientific decision-making basis for enterprise strategic planning.
Data Access and Edge Computing of Field Device
Storage and Analysis of Massive Industrial Time Series Data
PHM & Status Analysis
Quality Management & Yield Optimization
Production analysis & State Identification
Quality Inspection & Traceability