System and method for interactive engagement of users using machine learning based on environmental factors
An integrated system using machine learning and AI dynamically adjusts schedules and activities based on environmental factors to address real-time disruptions, ensuring seamless user interactions and enhanced satisfaction.
WO2026154499A1PCT designated stage Publication Date: 2026-07-23POONIA BOBBY SINGH +1
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Patent Information
- Authority / Receiving Office
- WO · WO
- Patent Type
- Applications
- Current Assignee / Owner
- POONIA BOBBY SINGH
- Filing Date
- 2025-07-10
- Publication Date
- 2026-07-23
AI Technical Summary
Technical Problem
Existing interactive systems fail to adapt to environmental changes and user preferences in real-time, leading to fragmented and disjointed user experiences due to the inability to integrate diverse data streams and predict disruptions, resulting in reduced user satisfaction and inefficiencies.
Method used
An integrated system using machine learning and artificial intelligence dynamically adjusts schedules and activities based on environmental factors, predicting disruptions and autonomously reconfiguring plans to ensure seamless user interactions.
Benefits of technology
The system provides robust, scalable, and intelligent user engagement by ensuring continuity and relevance in dynamic environments, enhancing user satisfaction and coordination.
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Smart Images
Figure IN2025051025_23072026_PF_FP_ABST
Abstract
An integrated system (106) for interactive engagement using machine learning based on environmental factors. The system (106) receives data associated with one or more users, where the data comprises information associated with interaction among the one or more users during one or more activities for a predefined schedule. The system (106) analyzes, the data to determine one or more environmental factors associated with the interaction of a plurality of users among the one or more users during the one or more activities. The system (106) dynamically configures, via a machine learning engine (214), the one or more activities for the predefined schedule based on the determined one or more environmental factors. The system (106) enables, interaction among the plurality of users using the dynamically configured one or more activities for the predefined schedule.
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