UTT Students Advance to the Final Round of AIoT Developer InnoWorks 2026

On 26 September 2026, at the Semi-final Round of the AIoT Developer InnoWorks 2026 Competition, Energy Twin, a team from the University of Transport Technology (UTT), successfully advanced to the Final Round. The result recognises the team’s efforts in research and product development, as well as its ability to apply AIoT, Edge Computing and Digital Twin technologies to smart energy management.

AIoT Developer InnoWorks is a technology competition for undergraduate and postgraduate students, focusing on the development of solutions using AIoT and digital technologies. In 2026, the competition was held at Phenikaa University, with key areas including Smart Manufacturing, Smart Cities, Energy and Environment.

Representing the University of Transport Technology at the competition was Energy Twin with the project “AIoT-Based Smart Energy Digital Twin Platform - An AIoT Platform for Energy Consumption Monitoring, Forecasting and Optimisation”. The team consists of six students from interdisciplinary technical fields including Automation, Electrical and Electronic Engineering, IoT, Information Technology and Economics, under the supervision of Dr. Vu Duc Tuan.

Energy Twin was developed to address a practical challenge that is receiving increasing attention in buildings, educational institutions and large-scale campuses: energy data is often scattered across multiple devices, while managers lack an intuitive tool to monitor electricity consumption in real time, detect abnormal usage patterns and forecast energy demand.

To address this issue, UTT students developed a Digital Twin solution, creating a digital model that reflects the energy consumption status of individual areas and load groups. Data on voltage, current, power and electrical energy is collected, processed and transferred to the platform, enabling operators to monitor system status, analyse historical data, detect abnormalities and support energy-saving recommendations.

The Energy Twin project developed by the University of Transport Technology team at the competition

One of the notable features of Energy Twin is its integration of AIoT, Edge Computing, data analytics and Digital Twin. Data processing, information aggregation and abnormal event detection can be performed directly at edge devices before the data is synchronised with the central system. The solution also aims to utilise historical data to forecast short-term electricity demand, compare it with consumption baselines and support appropriate operational recommendations.

The Energy Twin architecture is organised in a chain comprising sensors and electrical measuring devices - controller/Edge Gateway - WISE-IoT platform - time-series database - Dashboard → Digital Twin model and recommendation system. This approach enables physical-world data to be directly linked with a digital model, providing a foundation for scaling up from an experimental model to energy management for classrooms, laboratories, buildings and school campuses.

Through an intuitive interface, users can monitor electrical parameters in real time, observe the status of individual areas or loads, receive alerts when abnormal consumption occurs, and use data to assess energy consumption trends. This also provides a foundation for the system to further develop forecasting and operational optimisation functions, as well as assess carbon emissions corresponding to electricity consumption.

UTT students introducing and presenting the Energy Twin project at the Semi-final Round

At the Semi-final Round, the Energy Twin team presented the technological approach, system architecture and potential applications of its solution to the Judging Panel. Advancing to the Final Round demonstrates UTT students’ ability to approach and integrate multiple emerging technologies into a practical solution, ranging from embedded systems, IoT and Edge Computing to AI and Digital Twin.

Energy Twin team - University of Transport Technology at the Semi-final Round of AIoT Developer InnoWorks 2026

The Energy Twin team’s result also demonstrates the effectiveness of the University of Transport Technology’s approach to integrating education with scientific research, innovation and practical product development. Through technology competitions such as InnoWorks, students not only apply their specialised knowledge but also develop system design thinking, teamwork, product development, presentation and problem-solving skills for practical implementation.

Advancing to the Final Round marks an important milestone and opens the next stage for Energy Twin to further improve its product, enhance system stability, optimise analysis and forecasting algorithms, refine the Digital Twin interface, and demonstrate more clearly the effectiveness of the solution in energy management and energy saving.

The Final Round of AIoT Developer InnoWorks 2026 is scheduled to take place on 27 November 2026 at Phenikaa University. Building on the platform already developed and the experience gained from the Semi-final Round, the Energy Twin team will continue refining its solution towards a smart energy management system with the potential for practical application and scalability.

Congratulations to the Energy Twin team and the students of the University of Transport Technology. We wish the team continued confidence and creativity, and every success in the Final Round of AIoT Developer InnoWorks 2026!

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