Implementing an Operational Digital Twin for Optimizing Water Motor Operations in Resource-Constrained Environments

Small centrifugal pumps critical for rural and peri-urban water supply often lack advanced monitoring. This study develops a low-cost operational Digital Twin (DT) for a 3.7 kW induction motor pump at IIIT-Hyderabad (IIIT-H), optimised for resource-constrained settings with limited bandwidth and power. Using an ESP32 gateway, temperature, current, and vibration data are streamed to ThingSpeak, stored in MongoDB, and synchronised with a Simulink model via Eclipse Ditto. The system continuously compares simulated and actual pump data and raises alerts when abnormal behaviour is detected using a Root Mean Square Error (RMSE)-based anomaly detector. A dashboard was developed to enable remote motor operation and automated shutdown during unsafe conditions. The twin operates in a partially closed-loop mode: sensor streams continuously update the virtual model and generate alerts, while relay-based actuation allows automated start/stop motor operation. From August to November 2024, 160,000 minutely-sampled records demonstrated an≈8-second end-to-end latency, which is characterised as near real-time and adequate for supervisory pump monitoring. This meets the SCADA real-time standards, with 5% modelling error. The system enabled anomaly detection, detecting faults hours early without labelled data, and achieved rapid operator adoption with minimal training. This open-source solution bridges a research gap for 3-5 HP pumps, offering a scalable blueprint for small utilities and supporting future enhancements like fully closed-loop control.