📄 Sciences Methods and Technologies
International Journal (SciMeTech)

Volume 2 · Issue 1 · 2026
ISSN: 3085-5284
AI-Driven Smart Energy Management in IoT-Enabled Buildings
ALOUACH Abdennour, BENKIRANE Said, GUEZZAZ Azidine, LAMAAKAL Ismail
Pages 116–123 · Multidisciplinary Faculty of Nador, Mohammed Premier University, Oujda 60000, Morocco · Higher School of Technology Essaouira, Cadi Ayyad University, Marrakech 40000, Morocco
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Abstract
The presented study considers energy management in buildings which is a crucial issue that requires effective solutions. Specifically, it should be aimed at monitoring energy consumption, detecting potential problems and solving them automatically. In many cases, existing energy management systems are not able to make predictions regarding the possible development of circumstances and to perform actions automatically in response to abrupt changes in electricity consumption. In order to solve these shortcomings, this paper offers a holistic energy management architecture for an IoT-enabled building. It includes a multi-agent simulation using Node-RED which models realistic power consumption in functional rooms in the building, while InfluxDB is used for optimized storage of time series data. As for the reliability check, the process of dynamic anomaly injection, allowing for simulation of faults such as high-power spikes and blackouts, is used. Artificial intelligence forecasting model based on Prophet is used to predict energy consumption within six hours in the building while the threshold values for such analysis will be adjusted depending on season using Prophet's API. Once the deviation from predicted consumption is detected, real-time feedback control using MQTT will provide automatic isolation of circuits. According to findings, the system works fast enough, in about six seconds. The solution proposed in this paper can be implemented not only in smart buildings but also in the entire smart grid. In the future, reinforcement learning can be used to facilitate the work of a smart grid and to prevent faults in it.
Keywords: IoT-enabled building, Smart Building, Energy Management, Time-Series Data, MQTT, Node-RED, InfluxDB, Prophet, Real-Time Feedback Control, Artificial Intelligence

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SciMeTech · Volume 2, Issue 1 · 2026 · ISSN 3085-5284