Integration of artificial intelligence and the Internet of things for advanced monitoring and optimization of energy facilities in smart cities


DOI: 10.34759/trd-2023-131-23

Аuthors

Kasatikov N. N.*, Brekhov O. M.**, Nikolaeva E. O.

Moscow Aviation Institute (National Research University), 4, Volokolamskoe shosse, Moscow, А-80, GSP-3, 125993, Russia

*e-mail: Nick925@yandex.ru
**e-mail: obrekhov@mail.ru

Abstract

Energetics is one of the most important and state-of-the-art topics of the contemporaneity. Energy facilities monitoring and optimization play decisive role in ensuring effective energy consumption and sustaining stable infrastructure in the fast-developing cities.

Energy facilities optimization with the artificial intelligence (AI) and Internet of things (IoT) technologies plays an important role in ensuring effective energy consumption and sustaining stable infrastructure in the fast-developing cities. New innovative technologies allow data collecting in the real-time mode, performing enhanced analytics and accomplish intellectual decision making, which leads to the energy efficiency enhancing, operational costs reduction and stability increasing.

One of the energy facilities monitoring advantages using AI and Iot consists in the possibility for energy consumption optimization based on the demand, weather conditions and other factors. The AI algorithms are able to analyze collected data and predict energy requirements, which allows reducing electricity bill and negative impact on the environment. The algorithms may simplify the air traffic controllers tasks while civil aircraft landing or departure.

The IoT units, i.e. sensors and intellectual counters, are being installed at the energy facilities and civil aviation industry objects for real time data collection on various parameters, such as temperature, pressure, voltage and output power. These units transmit data to the central monitoring system, allowing operators surveying the energy facilities operation and indicating any deviations from the normal operation conditions.

The AI algorithms, machine learning and deep learning models can analyze the data collected by the IoT units to detect anomalies and anomalous regularities. The researchers may study the normal operating behavior the energy facilities by training the AI models using the test data. When the collected data deviate significantly from the expected values, the AI system may issue warnings to notify operators about potential problems or malfunctions requiring their attention.

AI and neural networks may be employed for predicting demands for servicing and preventing unexpected damage at the energy facilities and civil airports. By the data analysis from the IoT sensors and units, the AI models can reveal regularities pointing out potential failures or productivity reduction. It allows operators planning technical servicing in advance of repairing equipment prior to the failures and minimizing the downtime.

The AI algorithms can as well optimize operation of the energy facilities and enterprises of civil aviation trend by the real time data analyzing and revealing the possibilities for the efficiency enhancing. The AI, for example, may analyze the energy consumption schemes, the data on the equipment productivity and external factors, such as weather conditions, for energy systems optimal control and energy consumption reduction.

Thus, the Ai and IoT technologies application for energy facilities and civil aviation objects monitoring and optimizing demonstrate many advantages, including energy efficiency enhancing, power consumption costs reduction, stability improving and reducing negative impact on the environment. These innovative approaches help municipal companies, power suppliers and objects managers make justified decisions, develop strategies and ensure long-term stability of energy facilities in the rapid-developing cities.

Keywords:

Internet of things, smart city, artificial intelligence, smart devices, smart sensors, neural networks

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