VISUALIZING INTELLIGENT ENERGY NETWORKS: CONCEPTUAL DESIGN OF A SINGLE-WIRE IOT-ENABLED POWER DISTRIBUTION SYSTEM
DOI:
https://doi.org/10.29121/shodhkosh.v7.i2s.2026.7328Keywords:
Single-Wire Power Distribution, Internet of Things (IoT) Energy Networks, Smart Grid Architecture, Intelligent Energy Monitoring, Edge -Cloud Energy Management, Sustainable Smart Power InfrastructureAbstract [English]
The increasing complexity and inefficiency of traditional multi-wire power distribution systems are a need to impose new architecturally paradigmatic approaches. In the current research paper, the conceptual design of a single-wire, IoT-based intelligent energy network has been outlined in detail combining power delivery with real-time monitoring and adaptive control features. The proposed architecture will be based on the Internet of Things (IoT), edge computing, and cloud-based analytics to develop a single framework of efficient energy distribution, visualization, and management. The viability of simplified conductor systems designed with intelligent sensor networks is illustrated through mathematical modeling, theoretical analysis and through a simulation-based evaluation. The study tackles the basic issues of power transmission efficiency, system stability, and scalability as well as provides a base on the future deployment of smart grids. Some of its key contributions include a new system architecture, mathematical modeling of single-wire transmission, strategies of integrating the IoT, and a complete visualization framework. Findings point to good prospects of use in smart cities, microgrids and rural electrification situations, with major consequences of sustainable development of energy infrastructure.
References
Bopche, Y., Parque, V., Peshkar, S., Gupta, S., Patle, V., and Khobragade, P. (2026). Hybrid ARIMA-LSTM Forecasting of Residential and Regional Energy Consumption. In Proceedings of the 2026 20th International Conference on Ubiquitous Information Management and Communication (IMCOM) (1–6). IEEE. https://doi.org/10.1109/IMCOM69009.2026.11360878 DOI: https://doi.org/10.1109/IMCOM69009.2026.11360878
Condon, F., Martínez, J. M., Eltamaly, A. M., Kim, Y.-C., and Ahmed, M. A. (2023). Design and Implementation of a Cloud-IoT-Based Home Energy Management System. Sensors, 23(1), 176. https://doi.org/10.3390/s23010176 DOI: https://doi.org/10.3390/s23010176
Garcés, H. O., Godoy, J., Riffo, G., Sepúlveda, N. F., Espinosa, E., and Ahmed, M. A. (2025). Development of an IoT-Enabled Smart Electricity Meter for Real-Time Energy Monitoring and Efficiency. Electronics, 14(6), 1173. https://doi.org/10.3390/electronics14061173 DOI: https://doi.org/10.3390/electronics14061173
Kirmani, S., Mazid, A., Khan, I. A., and Abid, M. (2023). A Survey on IoT-Enabled Smart Grids: Technologies, Architectures, Applications, and Challenges. Sustainability, 15(1), 717. https://doi.org/10.3390/su15010717 DOI: https://doi.org/10.3390/su15010717
Kong, L., Tan, J., Huang, J., Chen, G., Wang, S., Jin, X., Zeng, P., Khan, M., and Das, S. K. (2022). Edge-Computing-Driven Internet of Things: A survey. ACM Computing Surveys, 55(6), 1–41. https://doi.org/10.1145/3555308 DOI: https://doi.org/10.1145/3555308
Mirani, A. A., Awasthi, A., O’Mahony, N., and Walsh, J. (2024). Industrial IoT-Based Energy Monitoring System: Using Data Processing at Edge. IoT, 5(4), 608–633. https://doi.org/10.3390/iot5040027 DOI: https://doi.org/10.3390/iot5040027
Munoz, O., Ruelas, A., Rosales, P., Acuña, A., Suastegui, A., and Lara, F. (2022). Design and Development of an IoT Smart Meter with Load Control for Home Energy Management Systems. Sensors, 22(19), 7536. https://doi.org/10.3390/s22197536 DOI: https://doi.org/10.3390/s22197536
Nain, G., Pattanaik, K., and Sharma, G. (2022). Towards Edge Computing in Intelligent Manufacturing: Past, Present and Future. Journal of Manufacturing Systems, 62, 588–611. https://doi.org/10.1016/j.jmsy.2022.01.010 DOI: https://doi.org/10.1016/j.jmsy.2022.01.010
Noman, A. A., Baidya, P., Hossain, M. A., Dev, P., Saha, K., and Hossain, M. L. (2025). Design and Implementation IoT-Driven Distribution Transformer Health Monitoring System for the Smart Power Grid. Engineering Proceedings, 87(1), 27. https://doi.org/10.3390/engproc2025087027 DOI: https://doi.org/10.3390/engproc2025087027
Qiu, T., Chi, J., Zhou, X., Ning, Z., Atiquzzaman, M., and Wu, D. O. (2020). Edge Computing in Industrial Internet of Things: Architecture, Advances and Challenges. IEEE Communications Surveys and Tutorials, 22(4), 2462–2488. https://doi.org/10.1109/COMST.2020.3009103 DOI: https://doi.org/10.1109/COMST.2020.3009103
Rajbhar, A. J., Pattanshetty, A. A., Parmar, D. K. S. K., Rajbhar, R. M., Parkar, A., and Sharma, S. (2025). Smart Energy Tracker. International Journal of Advanced Engineering and Communication Electronics, 14(1), 89–96. https://doi.org/10.65521/ijaece.v14i1.342 DOI: https://doi.org/10.65521/ijaece.v14i1.342
Serror, M., Hack, S., Henze, M., Schuba, M., and Wehrle, K. (2021). Challenges and Opportunities in Securing the Industrial Internet of Things. IEEE Transactions on Industrial Informatics, 17(5), 2985–2996. https://doi.org/10.1109/TII.2020.3023507 DOI: https://doi.org/10.1109/TII.2020.3023507
Shaban, M., and Alsharekh, M. F. (2022). Design of a Smart Distribution Panelboard using IoT Connectivity and Machine Learning Techniques. Energies, 15(10), 3658. https://doi.org/10.3390/en15103658 DOI: https://doi.org/10.3390/en15103658
Tekler, Z. D., Low, R., Yuen, C., and Blessing, L. (2022). Plug-Mate: An IoT-Based Occupancy-Driven Plug Load Management System in Smart Buildings. Building and Environment, 223, 109472. https://doi.org/10.1016/j.buildenv.2022.109472 DOI: https://doi.org/10.1016/j.buildenv.2022.109472
Tekler, Z. D., Low, R., and Blessing, L. (2022). User Perceptions on the Adoption of Smart Energy Management Systems in the Workplace: Design and Policy Implications. Energy Research and Social Science, 88, 102505. https://doi.org/10.1016/j.erss.2022.102505 DOI: https://doi.org/10.1016/j.erss.2022.102505
Published
How to Cite
Issue
Section
License
Copyright (c) 2026 Dr. Lowlesh Nandkishor Yadav, Dr. Midhun Chakkaravarthy, Dr. Dharmesh Dhabliya
This work is licensed under a Creative Commons Attribution 4.0 International License.
With the licence CC-BY, authors retain the copyright, allowing anyone to download, reuse, re-print, modify, distribute, and/or copy their contribution. The work must be properly attributed to its author.
It is not necessary to ask for further permission from the author or journal board.
This journal provides immediate open access to its content on the principle that making research freely available to the public supports a greater global exchange of knowledge.
