# Linux
cd bin
./startup-local-distrib.sh          # or ./startup.sh on a machine reachable by its network name

# Windows
cd bin
startup-local-distrib.bat

# equivalent command run by the scripts
../jre/<os>/bin/java -Dfile.encoding=UTF-8 -Xmx4048m --add-opens=... -jar ../lib/gind-r-io-standalone-<version>.jar start

The console then shows the r-iosuite> prompt. Type info to list the started web services with their host and port, shutdown to stop the suite and exit to leave the console. The first start takes a few minutes: embedded MongoDB and Neo4j initialise, metamodels and domains are published, and the predefined use cases listed in load-predefined-usecases are loaded.

1. In r-ioga, create a Crisis project named Fire at Albi Cathedral (the name cannot change afterwards) and clear its reference projects.
2. In r-ioda, Context And Partners, let the AI Creator Assistant create the city Albi and the building Albi Cathedral fixed onto Albi, and check in r-ioplay that both sit at the right place on the map. Then create the role Firefighter with its functions and one firefighter, renamed Owen Hartley (Olivia Hartley if the generated person is a woman), with Generate corresponding user to give him an r-io4U account (login ohartley). Add the function Confirm Fire, with a Radio output Fire Confirmed: Extinguish fires Needs it, and the edge carries the condition @Fire Confirmed[Confirm Fire] == "Yes".
3. In Objectives, with only Freeze checked, add a Fire_Alert, generate its Treats objective and make Extinguish fires satisfy it.
4. Back in Context And Partners, create a dedicated smoke sensor on the cathedral that references the frozen alert.
5. r-iota shows no alert. Play the dataset of the sensor step by step in r-iosemit: at the fourth step the alert becomes sure. Click Find solution(s) in r-iota: in the execution graph, the Sequence_Flow toward Extinguish fires carries the copied condition (CE badge, shown on hover).
6. In r-io4U, logged in as Owen Hartley, the tasks appear on their own after the deduction: tick Confirm Fire, answer Yes in its output form, then tick Extinguish fires: the process ends and r-iota shows no more alert. As the expert, validate the resolution with Delete positive deviations in r-iota: the active objective and alert are deleted, the flames leave the cathedral and the supervision ends. Replay the sensor: the fire starts again as a new alert; answer No this time and the process ends through the otherwise flow. Export the project as a zip archive to import it elsewhere.

Open the guided walkthrough →

1. In r-ioga, open the Load use cases dialog: it lists the packaged use cases and can download further ones from Nexus (downloadRemoteUsecase).
2. Choose IMT Albi Crisis. The models are published to the graph through the governance (batch publication, interceptors and history), and its game scenarios and shared resources come with it.
3. Open r-ioda in the same context to browse the campus: buildings, networks, partners, sensors, risks and objectives, exactly as described on the use case page.

1. From r-iota (deduce dialog) or r-ioded, launch a deduction with the Drools Simple Satisfaction strategy on the objectives manager of the project. The campaign runs asynchronously; progress arrives through the SOLUTION topic.
2. Review the solutions: each one is a planned collaborative process with assigned actors, resources and expected dates. Select the one to execute.
3. Deploy and run it: r-ioga (or r-iosepe’s run-and-supervise chain) deploys the process on the workflow engine, starts it and supervises it. Computer tasks call the mock endpoints created by the scenario; human tasks appear in the to-do list of the assigned persons and in r-io4U.
4. Follow execution in r-iota and r-iomega: monitoring events show each exchange and the progression of the instance.