Development of an IoT-Enabled Digital Twin for Smart Load Monitoring in Rural Nigerian Communities

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@article{1714448,
      author = {Ejie, Ndamzi Destiny, Dr. Matthew Ehikhamenle},
      title = {Development of an IoT-Enabled Digital Twin for Smart Load Monitoring in Rural Nigerian Communities},
      journal = {Iconic Research And Engineering Journals},
      year = {2026},
      volume = {9},
      number = {8},
      pages = {1198-1202},
      issn = {2456-8880},
      url = {https://www.irejournals.com/formatedpaper/1714448.pdf},
      abstract = {Rural distribution networks in Nigeria frequently operate with limited visibility, intermittent communication, and weak maintenance capacity, conditions that amplify overloads, voltage deviations, and prolonged outages. This study presents the development of an Internet of Things enabled digital twin framework for real time smart load monitoring that fuses field measurements with a dashboard driven virtual representation of feeder behaviour. The proposed architecture combines voltage and current sensing, embedded computation for power and power factor estimation, and a digital twin dashboard for remote visualization, alerting, and data logging. A structured preprocessing pipeline converts raw measurements into quality checked features, including RMS quantities, real and apparent power, energy, frequency, and efficiency indicators. System verification was performed using a 48 hour monitoring campaign and a simulation driven IoT dashboard replay that validated end to end sensing, communication, and visualization. The field test recorded a stable supply voltage of 229.99 V within the 220 to 240 V nominal band, a perfectly stable 50.00 Hz frequency, and a power factor of 0.96, confirming correct power quality computation and reporting. The digital twin dashboard replay further demonstrated reliable streaming of timestamped load states and status classification across successive time windows. Overall, the work shows that a lightweight digital twin, anchored by IoT measurement fidelity, can provide actionable situational awareness for rural operators, support energy management decisions, and establish a practical foundation for future predictive analytics and automated demand side control in Nigerian mini grids.},
      keywords = {Digital Twin, IoT, Smart Load Monitoring, Rural Electrification, Power Quality, Dashboard Visualization},
      month = {February},
      doi = {https://doi.org/10.64388/IREV9I8-1714448}
  }