An expert system for automating image and video editing services using AI, cloud and blockchain technologies
Nguyen Duc Xuan (),
Nguyen Ngoc Khang () and
Pham Van Khanh ()
Edelweiss Applied Science and Technology, 2025, vol. 9, issue 7, 2365-2381
Abstract:
In the digital age, high-quality visual content plays a critical role in marketing, real estate, and personal branding. However, traditional image and video editing workflows remain manual, fragmented, and time-consuming. This paper proposes an expert system that automates the entire service chain of photo, video, and virtual architectural editing by integrating advanced technologies such as AI, chatbots, cloud computing, and blockchain. The system intelligently analyzes customer requests, assigns tasks to AI modules or human editors, ensures quality control, and securely manages payments through smart contracts. Designed as a cloud-native, microservice-based architecture, the platform is scalable and resilient, offering services through both web and mobile interfaces. Simulation results show a significant reduction in turnaround time, enhanced consistency in output quality, and increased processing capacity. By automating both technical and operational processes, the proposed system aims to transform digital content services into a seamless, efficient, and trusted experience. It has strong potential to attract customers and investors, especially in industries demanding fast, cost-effective, and scalable media solutions.
Keywords: Artificial intelligence; Blockchain payment integration; Chatbot-driven customer interaction; Cloud-native architecture; Expert system; Photo and video editing automation. (search for similar items in EconPapers)
Date: 2025
References: Add references at CitEc
Citations:
Downloads: (external link)
https://learning-gate.com/index.php/2576-8484/article/view/9185/3039 (application/pdf)
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:ajp:edwast:v:9:y:2025:i:7:p:2365-2381:id:9185
Access Statistics for this article
More articles in Edelweiss Applied Science and Technology from Learning Gate
Bibliographic data for series maintained by Melissa Fernandes ().