This paper presents the design and implementation of an automated power consumption monitoring system tailored for multi-tenant-based billing in residential buildings. Traditional manual metering methods often lead to inaccurate billing, disputes, and reduced incentives for energy conservation. To address these challenges a prototype was built using a transformer-less 5V supply, 50A CT, HLW8032 metering IC, Arduino Nano, IR receiver, and TM1637 7-segment display; firmware (C++, 500Hz sampling) computes RMS/energy, logs to Electrically Erasable Programmable Read-Only Memory (EEPROM) and handles secure resets. Calibration and tests showed current error ? ±0.7%, voltage error ? ±0.4% (power error <1%), 5V regulation within ±0.3% with <100 mVpp ripple, and a 48-hour field trial recorded kWh deviations between ? 0.54% and + 0.48% (? ±0.6%). EEPROM persisted through power interrupts, IR resets decoded ?98% of the time, firmware ran 72hours without issues, and display refresh averaged ~37 ms. The prototype meets the project objectives which is accurate, repeatable tenant-level monitoring and automated billing with low measurement error and robust operation, demonstrating suitability for residential deployment. Recommended next steps are scaling the architecture for larger complexes, adding networked connectivity and secure cloud APIs, improving the user interface (mobile and web dashboard), and incorporating advanced analytics for consumption forecasting and automated energy-saving recommendations
W. Raheem, O. Ipinnimo, C. Folorunso et al.· LAUTECH Journal of Engineeri...· 0 citations
In this paper, the joint radio resource management issues in a cognitive radio network driven by radio frequency energy harvesting (CRN- RF-EH) functionalities are investigated. For the CRN-RF-EH, the cognitive radio (CR) node first harvests its required energy directly from the transmitter of spectrum licensed user for its data communication and consequently transmits its data on the licensed frequency of the legacy user using the underlay accessing technique. Thus, RF-EH is an exciting innovation for energizing low-powered next- generation wireless networks (NGWNs). Consequently, due to CRN-RFEH’d low power limitations, the resource allocation for CRN-RF-EH has to be optimized considering the trade-off among spectral efficiency, energy efficiency, and RF energy supply. Equal allocation of transmission time and/or transmission power may not be efficient for CRN-RF-EH with limited transmission time and power resources. A joint optimal time and power allocation (OTPA) strategy for CRN-RF-EH is proposed to maximise the total spectral efficiency of the CRN- RF-EH. The coupled variables in the formulated joint resource allocation problems create a non-convex optimization problem formulation. For analytical tractability, the non-convex optimization formulation is initially converted to its equivalent standard convex optimization formulation using proper variables and next, it is then solved using the convex optimization technique. The CONOPT solver, a powerful optimization-solving tool for solving convex optimization problems, is utilized to resolve the equivalent standard convex optimization problem formulation. When compared with the baseline biased random time optimum power allocation (BRTOPA) scheme, numerical simulation results show that the OTPA strategy dramatically improves the total spectral efficiency performance. In a severe radio propagation environment with a path loss exponent (PLE) equal to 3.5 such as in urban areas and less severe radio propagation environment with a path loss exponent (PLE) equal to 2.0, such as in rural areas, the OTPA outperformed the BROTPA with a mean performance improvement of approximately 23. 96% and 42.94% , respectively.
E. Obayiuwana, O. Ipinnimo, P. Ayodele et al.· Nigerian Journal of Technolo...· 1 citation
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