A team of mathematicians from RUDN University has proposed a system that utilizes the Internet of Things (IoT) and digital twin technology to enhance energy efficiency. This system, which optimally distributes tasks and manages energy allocation between devices, has the potential to significantly reduce household energy costs. The findings of the study were published in Sensors.
The development of sustainable households of the future requires an optimal energy distribution system. A novel concept in this regard is nanonetworking, a decentralized energy distribution system that operates at the level of individual residential buildings. The key objective of nanonetworking is to optimize energy exchange, enabling households to make the most efficient use of energy resources.
To achieve this, the team of mathematicians from RUDN University, in collaboration with researchers from Saudi Arabia and South Korea, proposed leveraging digital twins and IoT technologies. The Internet of Things has already had a transformative impact on various sectors, including medicine and navigation. However, the full potential of IoT in the energy industry has yet to be explored. RUDN University researchers believe that moving from traditional smart grid systems to IoT platforms based on digital twins is crucial for improving the performance of distributed energy systems.
One of the potential benefits of energy storage systems in nanonetworks is the ability to spend energy more efficiently, increase resilience, and adopt sustainable practices by storing excess energy. Ammar Muthanna, Ph.D., Director of the Scientific Center for Modeling Wireless 5G Networks at RUDN University, highlighted the potential of these systems.
The proposed system by the mathematicians at RUDN University is built upon two key concepts: digital twins and IoT. The system employs multiple sensors to monitor the status of devices within households. This real-time information is then transmitted to the IoT system, where an artificial neural network coordinates tasks. As a result, an optimal energy consumption mode is selected, with the neural network making accurate forecasts and formulating the most effective energy strategy.
The RUDN University mathematicians described the proposed system theoretically and presented the algorithm in the form of code. To assess the system’s performance in a real-world environment, the researchers developed a simulation consisting of 21 nanonetworks. Compared to similar systems, the proposed system exhibited a 1.5–2.5 times decrease in the number of uncompleted tasks.
Ammar Muthanna, Ph.D., Director of the Scientific Center for Modeling Wireless 5G Networks at RUDN University, emphasized that the proposed architecture is a practical and viable option for implementing smart grids in real-time. It effectively manages energy distribution, promoting sustainability and efficiency.
In conclusion, the innovative IoT-based system proposed by the mathematicians from RUDN University offers promising potential for reducing household energy costs. By leveraging digital twins and the IoT, households can optimize their energy consumption, leading to greater sustainability and efficiency.
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1. Source: Coherent Market Insights, Public sources, Desk research
2. We have leveraged AI tools to mine information and compile it
