Developing a Green AI Platform for SMEs to Analyze Open-source Information with the Approach of Society 5.0


Akarslan H., Sağiroğlu Ş.

SN COMPUT. SCI., cilt.5, sa.923, ss.1-26, 2024 (Hakemli Dergi)

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 5 Sayı: 923
  • Basım Tarihi: 2024
  • Doi Numarası: 10.1007/s42979-024-03287-1
  • Dergi Adı: SN COMPUT. SCI.
  • Sayfa Sayıları: ss.1-26
  • Gazi Üniversitesi Adresli: Evet

Özet

Management and information systems are considered two major disciplines that have to be combined to benefit from knowledge for rational decision-making which means strict procedures utilizing objective knowledge and logic for many years. Effective and efficient use of already invested organizational resources is a key subject to gain a competitive advantage by making decisions with the help of AI techniques which benefit from both internal and external knowledge. This paper introduces a new model to get benefits from open-source intelligence (OSINT) in the context of external knowledge with a green computing approach for solving global organizational challenges in the scope of Society 5.0. This research has a dual background, theoretical and practical. Problem defining and hypothesis formulation was carried out by literature review. Then, the application developed according to the proposed model was put into action in some organizations for testing, and feedback from experts who participated in the proof of concept (POC) activities was evaluated and discussed empirically. Finally, the findings of our research, the advantages of our model, and both academic and business future work were summarized. It has been practically determined that the model and application we have developed are largely successful in line with our hypotheses. However, the weaknesses and advantages of our study were also revealed. Our research is the first study that combines Management Information Systems and Open-Source Intelligence disciplines with the approach of Society 5.0 to support SMEs in analyzing open-source information to build better decision-making mechanisms. The developed application in this study can also be applied to solving other green distributed computing needs in different domains