Abstract
In an era of information overload, artificial intelligence plays a pivotal role in supporting everyday decision-making. This paper introduces EverydAI, a virtual AI-powered assistant designed to help users make informed decisions across various daily domains such as cooking, fashion, and fitness. By integrating advanced natural language processing, object detection, augmented reality, contextual understanding, digital 3D avatar models, web scraping, and image generation, EverydAI delivers personalized recommendations and insights tailored to individual needs. The proposed framework addresses challenges related to decision fatigue and information overload by combining real-time object detection and web scraping to enhance the relevance and reliability of its suggestions. EverydAI is evaluated through a two-phase survey, each one involving 30 participants with diverse demographic backgrounds. Results indicate that on average, 92.7% of users agreed or strongly agreed with statements reflecting the system’s usefulness, ease of use, and overall performance, indicating a high level of acceptance and perceived effectiveness. Additionally, EverydAI received an average user satisfaction score of 4.53 out of 5, underscoring its effectiveness in supporting users’ daily routines.
Author supplied keywords
Cite
CITATION STYLE
Pardo B, C. E., Iglesias R, O. I., León A, M. D., & Quintero M, C. G. (2025). EverydAI: Virtual Assistant for Decision-Making in Daily Contexts, Powered by Artificial Intelligence. Systems, 13(9). https://doi.org/10.3390/systems13090753
Register to see more suggestions
Mendeley helps you to discover research relevant for your work.