Published at : 29 Dec 2023
Volume : IJtech
Vol 14, No 8 (2023)
DOI : https://doi.org/10.14716/ijtech.v14i8.6906
Teuku Yuri M Zagloel | Department of Industrial Engineering, Faculty of Engineering, Universitas Indonesia, Kampus UI Depok, Depok, 16424, Indonesia |
Ruki Harwahyu | Department of Electrical Engineering, Faculty of Engineering, Universitas Indonesia, Kampus Baru UI, Depok, 16424, Indonesia |
Imam Jauhari Maknun | Department of Civil Engineering, Faculty of Engineering, Universitas Indonesia, Kampus Baru UI, Depok 16424, Indonesia |
Eny Kusrini | 1. Department of Chemical Engineering, Faculty of Engineering, Universitas Indonesia, Kampus Baru UI, Depok, 16424, Indonesia 2. Research Group of Green Product and Fine Chemical Engineering, Laborat |
Yudan Whulanza | Department of Mechanical Engineering, Faculty of Engineering, Universitas Indonesia, Kampus Baru UI, Depok, 16424, Indonesia |
Developing models and tools to explore
the synergies between energy transition and the digital economy has been an
interesting topic, aiming to provide significant contributions to the domains
of technological innovation, economic development, sustainability, and global
establishment. All efforts from these models and tools can support the advanced
and establishing countries by collaborating among all members, researchers,
governments, and others.
The following argument highlights how important predictive analytics is for forecasting changes in energy consumption. Data analytics and machine learning models can foresee changes in demand and help energy providers make plans by examining historical data and current patterns. This capacity is essential for guaranteeing the best possible use of resources, avoiding waste, and preserving the equilibrium between energy production and consumption. Optimizing energy use is another important area where the digital economy could be helpful. Machine learning algorithms can make recommendations for ways to improve energy efficiency by analyzing usage patterns and user behavior. This contributes to general energy conservation, which is in line with environmental goals, in addition to perhaps saving consumers money.
The concept of a digital twin with rich visualization
is introduced as a particularly intriguing application. Creating a virtual
representation of a real system or process allows for comprehensive tracking,
assessment, and optimization. The paragraph argues that the energy sector's
efforts to manage energy more effectively can benefit significantly from the
adoption of digital twins. Moreover, the potential advantages of digital twins
extend to the healthcare sector, where modeling and digitalization can address
challenges in this field.
In addition, the conversation presents the idea of
digital platforms that offer rewards for environmentally conscious actions
within the energy sector. These platforms can use innovative market mechanisms
to encourage actions that contribute to environmental goals. The discussion
claims that digital platforms can encourage demand response and energy
conservation by offering users incentives to adjust their energy consumption
patterns in response to market or environmental signals. The focus on sustainability
draws attention to how integrating digital platforms into energy markets might
help society and the environment more broadly. Incentives for demand response
and energy conservation not only encourage the more economical use of resources
but also contribute to global initiatives aimed at lowering carbon footprints
and mitigating the effects of climate change.
The 5th International Scientific
Conference on Innovations in Digital
Economy: SPBPU IDE-2023 has already been
held on 12
- 13 October 2023 at Peter the Great St.
Petersburg Polytechnic University located at Novorossiyskaya, Saint Petersburg, Russia,
with interesting topics such as (i) Economic efficiency and the social
consequences of implementing digital innovations, (ii) Regional innovation
systems and clusters as drivers of economic growth during the Fourth Industrial
Revolution, (iii) Industrial, service and agricultural digitalization, (iv)
Responses of the educational system and labor market to digital-driven changes
in the economic system, (v) Digital transformation in the government sector,
(vi) Digital transformation in the financial sector. This conference is
organized by the Graduate School of Industrial Economics (GSIE) of Peter the
Great Saint Petersburg Polytechnic University (SPbPU) and the Centre for
Sustainable Infrastructure Development (CSID) of Universitas Indonesia (UI). SPBPU IDE-2023 is expected to have a significant impact on the
economic, social, and environmental aspects of both regional and national
levels.
A thorough examination of this phenomenon was evident
in the 21 papers that were presented, which mostly focused on researching
important aspects such as support systems, finance structures, and regulatory
frameworks that control industry operations. The expected results of these
research efforts include increased efficiency in investment use, enhanced
competitiveness of businesses, and a significant shift towards an ecologically
conscious approach to industrial activity. Especially in industrial activities,
there is a significant impact on the progress in the economic, social, and
environmental conditions of regions and the country as a whole in Russia. The
discussion is supported by the presentation of 21 papers, which primarily
examine the main forms of support, financing, and regulation of industrial
activities, identifying problematic aspects of state support for them. Their
approaches are expected to result in more efficient investment utilization,
enhanced competitiveness of enterprises, and a shift towards an environmentally
focused approach in industrial activities.