Autonomous Computing

he Autonomous Computing component enables the decentralisation and automation of decisions by autonomously controlling processes values and resources, be it zApps, i4 components or computational resources, as well as communicating and cooperating with other components.

To execute actions autonomously, users can define limits for data points, as well as qualifiers (eg energy consumption is ‘larger than’ & ‘100 kWh’) to trigger user defined actions. The actions to be used are obtained from the Orchestration component, where the user can model BPMN Processes.


  • Facilitates automation of critical processes which should kick in once specified KPI conditions meet

  • Provides an easy-to-use Graphical User Interface for defining autonomous process, KPIs etc

  • Provides a dashboard for creating and visualizing reports and graphs related to functioning of Autonomous processes and subscribed KPIs

  • Facilitates the AI-Analytics component to generate insights from historical trends of Autonomous process and KPI conditions

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Create Autonomous Process

Allows the creation of Autonomous Processes consisting of rules based on KPI values, and API calls that are executed whenever the condition specified is matched. This gives the user the possibility to automate the execution of Processes when the production indicators are not conforming with quality standards, minimizing the reaction time for critical situations.

View Autonomous Process Historic Data

Allows the user to see the Autonomous Processes data and its execution through time. This information is used by the AI-Analytics component to offer the user insights on how to improve the conditions applied. The KPI’s values associated to an Autonomous Process can also be visualised in a timeline to improve the visibility of the impacts of the autonomous processes’ execution in the KPI’s values.

Autonomous Process Monitor Engine

Monitors the KPI values changes to trigger the execution of a process. The component monitors the value change of every KPI associated to the Active Autonomous Processes, whenever the KPI values changes, an algorithm is applied to the conditions related to it, when the conditions are matched for one or more Autonomous Processes, the list of API calls defined are executed.

Improvement Insights UI

Displays insights on how to improve the autonomous processes accuracy, these insights are gathered from the AI-Analytics component based on the historic data of the autonomous process’s execution and its impacts on the associated KPI’s values.

Additional resources

Learn more about i4FS by visting the project website for general information, the wiki for information about the core components, the Technical Manual for API documentation, and downloading the repository’s source code.

Training Academy

Get a better understanding of the global architecture and information flow.

Source code

Our source code is opensource and available on our Gitlab repository.

Software Documentation

Read our easy to follow documentation to learn how to use the i4 Components.

Software Tutorials

Follow our step by step tutorials to create your first zApp.