The OSCAR project, led by SEGNO GmbH in Bremen, set out to create a standardized data interface—OSCAR‑Connect—for environmental control systems on cruise ships and other industrial plants such as biogas, wastewater, and emission‑cleaning facilities. The core technical achievement was the development of an IoT connector that gathers sensor data, buffers it locally, and securely transmits it to cloud platforms, primarily Siemens Mindsphere, while maintaining full functionality even when internet connectivity is temporarily lost. The connector stores configuration and log data in a lightweight SQLite database, which is independent of the operating system, and uses JSON files for offline buffering. When connectivity is restored, the buffered data are uploaded automatically, ensuring no loss of information.
The system architecture incorporates an edge‑computing module that aggregates raw measurements, applies pre‑configured compression, and holds the results until they can be sent to the cloud. The Mindsphere connector, built on the MindConnect‑Lib Agent, authenticates with stored credentials and can transmit data at configurable intervals. Although OPCUA communication was not required for the initial scope, the connector’s design allows future integration with OPCUA servers, providing flexibility for different industrial environments. To validate Modbus‑TCP communication, the team employed a Node‑RED simulation because a physical Modbus controller was not available. Node‑RED, a browser‑based graphical development tool, was used to emulate the Modbus‑TCP traffic and to test the connector’s handling of real‑time data streams.
The software stack is based on Node.js, with several lightweight libraries for handling network protocols, data compression, and database access. The project also used a small set of auxiliary Node.js packages that provide simplified implementations of basic functions. The entire solution runs on a Raspberry Pi platform, which is configured via raspi‑config and set to start the connector automatically on boot. The modular design of the connector allows it to be adapted to various communication hardware, and the configuration files can be modified to change measurement parameters, compression settings, or cloud endpoints without recompiling the code.
Beyond the technical implementation, the OSCAR project aimed to demonstrate that a digital twin of the environmental system could operate outside the cloud environment and still provide real‑time monitoring, predictive analytics, and remote alarm capabilities. The digital twin receives the same data stream as the cloud, processes it locally, and can issue recommendations or control commands back to the ship’s systems. This dual‑deployment strategy ensures resilience and offers a pathway for fleet‑wide management of environmental performance across multiple vessels.
The collaboration involved SEGNO GmbH as the primary developer and coordinator, with additional partners contributing expertise in cloud integration, simulation, and system testing. The project timeline extended into the third and fourth quarters of 2022, with a cost‑neutral extension that allowed the team to refine the connector and validate its portability across different hardware setups. Funding was provided by German research agencies, supporting the development of industry‑ready solutions for environmental monitoring and fleet management. The OSCAR project therefore delivers a robust, secure, and adaptable IoT connector that bridges on‑board environmental systems with cloud analytics, paving the way for broader adoption of Industry 4.0 practices in maritime and industrial sectors.