Deshpande et al. Res. Trends Int. J. Technol. Innov., October - December 2026, 1 (4) : 18-26
1Department of Electronics and Communication Engineering, Vellore Institute of Technology, Vellore, India; 2Department of Electrical Engineering, Jadavpur University, Kolkata, India
Article History
Accepted : 28 Jul 2026
Published : 05 Oct 2026
Publication Issue
Volume 1, Issue 4
October - December 2026
Page Number18–26
Residential smart metering deployments in areas with limited WiFi or GSM coverage benefit from narrowband IoT connectivity due to its extended range and low power requirements. This paper presents a smart meter design using NB-IoT for reporting appliance-level load disaggregation computed on-device via a lightweight event-based non-intrusive load monitoring algorithm. Deployed across 25 households over eight weeks, the system achieved 88.4 percent appliance identification accuracy for six common load types while consuming under 40mW average power, enabling battery-only operation between 14 and 18 months.
Keywords - smart metering, NB-IoT, non-intrusive load monitoring, residential energy, low-power design
Non-intrusive load monitoring allows appliance-level energy insights from a single point of measurement at the meter, avoiding the cost of per-appliance sub-metering, and NB-IoT extends this capability to rural and semi-urban residential areas with poor WiFi or cellular data coverage.
A smart meter prototype sampled aggregate current and voltage at 4kHz and applied a lightweight edge-based event detection algorithm to identify appliance on/off transitions and classify appliance type from transient current signatures, reporting 15-minute aggregated appliance-level summaries over an NB-IoT connection rather than raw high-frequency waveforms, deployed across 25 households for an eight-week field trial.
The on-device event-based classifier achieved 88.4 percent identification accuracy averaged across six common appliance types (refrigerator, water heater, washing machine, air conditioner, television, and lighting circuits), with average system power draw of 38mW, projecting 14 to 18 months of operation from a single 10,000mAh battery pack depending on household appliance-switching frequency.
Combining edge-based non-intrusive load monitoring with NB-IoT reporting enables appliance-level residential energy insight in coverage-limited areas without the cost of per-appliance sensors. Future work will extend the appliance signature library to cover a broader range of household equipment.
[1] Hart G. W., Nonintrusive appliance load monitoring, Proceedings of the IEEE, 1992. [2] Ratasuk R. et al., NB-IoT system for M2M communication, IEEE WCNC, 2016.
© 2026 The Author(s). Published by IJEIA Editorial Office. This is an open access article under the Creative Commons Attribution 4.0 International License (CC BY 4.0).
Pranav Deshpande, Ankita Bose (2026). Design of a Smart Energy Metering System Using NB-IoT for Residential Load Monitoring. IJEIA, 1(4), 18-26.
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