An IIoT-Based Digital Twin Architecture for Remote Supervisory Water-Level Control: Design and Latency Evaluation
Digital twins are attracting growing interest in the industry. They enable the optimization of monitoring, control, and decision-making. However, many existing implementations rely on costly proprietary platforms. This limits their adoption by small and medium-sized enterprises. This paper presents a low-cost digital twin architecture. It is based on open-source platforms (Node-RED, MQTT) and affordable hardware (Raspberry Pi). This architecture was applied to the remote supervisory setpoint control of the water level in an industrial reservoir. Real-time synchronization between the physical system and its digital twin was evaluated through transport-latency measurements on clock-synchronized machines (NTP, inter-clock offset below 0.1 ms), with sequence-numbered messages paired end-to-end between the gateway and the twin. Across several measurement campaigns totaling over 33,000 messages, including a fully paired 5226-message validation session (zero loss, duplication, or reordering), the median transport latency was 44 ms, with 99.20% of messages delivered within 100 ms and occasional peaks of a few hundred milliseconds (maximum 923 ms), consistent with transport-layer retransmission stalls. Despite these peaks, performance remains acceptable for non-critical real-time applications, such as water-level supervisory control, since the resulting estimated level-deviation bound stays within the controller’s 0.2% hysteresis band for 99.0% of messages. These results indicate that a digital twin of a small industrial reservoir can be implemented in a viable and cost-effective manner at the gateway and communication layers. This approach makes the technology more accessible to small and medium-sized industries.
Authors
- Mohamed Tabaa (ORCID: https://orcid.org/0000-0003-3938-3566)
- Abdelhafid Ait Elmahjoub (ORCID: https://orcid.org/0000-0002-4961-3532)
- Zineb Hidila (ORCID: https://orcid.org/0000-0003-1104-4896)
- Ayoub Fentis (ORCID: https://orcid.org/0000-0001-8364-4749)
- Adnane Bouchra
- Abdennaser Amana
- Fatima-Ezzahra Labchiri
Institutions
- École Marocaine des Sciences de l'Ingénieur (MA)
- University of Hassan II Casablanca (MA)
Publication Details
- Journal
- IoT
- Published
- 2026-10-26
- DOI
- https://doi.org/10.3390/iot7040090
- Primary Topic
- Digital Transformation in Industry
- Type
- article
- Field-Weighted Citation Impact
- 0.00