THE PROBLEM OF ENERGY EFFICIENCY OF SYSTEMS BASED ON ARTIFICIAL INTELLIGENCE OF THE INTERNET OF THINGS (AIOT)
The article reveals the economic, energy, and environmental aspects of the integration of the Internet of Things (IoT) and artificial intelligence (AI) in the technology of the artificial intelligence of the Internet of Things (AIoT). The scientific problem is defined as the commercial attractivenes...
Saved in:
| Main Author: | |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Igor Sikorsky Kyiv Polytechnic Institute
2025-02-01
|
| Series: | Ekonomìčnij Vìsnik Nacìonalʹnogo Tehnìčnogo Unìversitetu Ukraïni "Kiïvsʹkij Polìtehnìčnij Institut" |
| Subjects: | |
| Online Access: | https://ev.fmm.kpi.ua/article/view/324402 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| Summary: | The article reveals the economic, energy, and environmental aspects of the integration of the Internet of Things (IoT) and artificial intelligence (AI) in the technology of the artificial intelligence of the Internet of Things (AIoT). The scientific problem is defined as the commercial attractiveness of artificial intelligence in the Internet of Things and energy savings. The focus is on compliance with the provisions of sustainable development, particularly the seventh goal, "Affordable and Clean Energy," and the ecological footprint. Additional energy costs and increased carbon emissions can become significant with more complex AIoT neural architectures. The feasibility of using a metric based on the energy cost of the AIoT life cycle (eCAL) is emphasized. Scaling AIoT is possible when building a Smart City or similar locally concentrated structures. The emphasis is on allocating conventionally fixed and conventionally variable costs for AIoT. It was determined that integrating artificial intelligence functionality into the IoT infrastructure provides the opportunity to store big data for processing using artificial intelligence elements capable of conducting predictive analysis to make informed management decisions. AIoT energy efficiency can be ensured on the basis of the following: selection of machine learning methods, hardware improvement, software optimization, network planning, effective model design, and energy consumption testing with subsequent conclusions for comprehensive improvement. The scientific novelty is a methodological approach to a thorough study of the processes of AIoT implementation in technological development based on energy efficiency, considering the cost of energy in the AIoT life cycle (eCAL), and the ecological footprint of AIoT systems. The direction of further scientific research is determined, which consists of the need for economic and mathematical analysis of production systems formed based on artificial intelligence of the Internet of Things. |
|---|---|
| ISSN: | 2307-5651 2412-5296 |