TeamCAMS is an open-source simulation environment for studying human-AI interaction, teamwork, and decision-making in complex operational settings. Designed for scientific research, it provides a flexible platform for exploring automation, collaboration, performance, and the future of intelligent work systems.
TeamCAMS represents a significant step forward for both researchers and developers in the field of human-AI interaction and team-based simulation research.
Built on a modern client-server architecture, TeamCAMS enables multiple participants to collaborate simultaneously from their own devices during experimental sessions. The simulation is centrally managed by a Manager application, running on the researcher's computer, which acts as the authoritative source for simulation state, scenario execution, and experimental control.
Participants access the simulation through a web-based Operator Interface, removing the need for dedicated software installation and supporting a wide range of devices, including desktops, laptops, and tablets. Because the interface operates entirely within a standard web browser, TeamCAMS can be deployed both in laboratory environments and in remote settings, allowing participants to complete training sessions and research studies from virtually any location.
Communication between the Manager and the Operator Interfaces relies on an MQTT-based messaging infrastructure. MQTT serves exclusively as a lightweight communication layer, enabling efficient data exchange between distributed components while ensuring that the simulation itself remains hosted on the researcher's system rather than in the cloud. This approach allows researchers to retain full control over experimental data, system configuration, and study execution.
To ensure privacy and security, all communication between the Manager and connected Operator Interfaces is encrypted. As a result, participant interactions and experimental data remain accessible only to authorized researchers. The architecture also supports operation across different networks, making it possible for geographically distributed participants to engage in the same simulation session in real time.
The platform provides powerful tools for experiment management and study design. Researchers can supervise and control multiple experimental sessions simultaneously while collecting detailed logs for subsequent analysis. To simplify scenario creation, TeamCAMS includes a visual script editor that presents experimental procedures through an intuitive graphical timeline, making the development of both simple and highly complex scenarios more accessible.
In addition, TeamCAMS offers a dedicated log processing tool capable of automatically extracting, aggregating, and batch-processing data from multiple experimental logs. This functionality substantially reduces the effort required for data preparation and enables more efficient analysis of experimental results.
Together, these enhancements make TeamCAMS a flexible, scalable, and user-friendly research platform for investigating human performance, teamwork, automation, and human-AI collaboration in complex operational environments.