Multi-Level Control Platform for Context-Aware Communication
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Solution Overview
Problem
Current electronic networks lack multi-level control, variable access, and multi-user capabilities for real-time contextually relevant data communications among network-connected devices as they move or data flows change, particularly in integrating context awareness, sensor fusion, and CRM systems for enhanced experiences and interactions.
Innovation Solution
A multi-tenant contextual intelligent communication platform (MTCICP) that delivers real-time contextually relevant content and offers while gathering performance data, using sensor fusion, proximity beacons, and NFC tags to provide curated experiences and control access across multiple layers and users, integrated with CRM systems for enhanced interactions and feedback loops.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If a comprehensive contextual intelligent communication platform is implemented with multi-level control, variable access, and multi-user capabilities, then the system's functionality and intelligence are improved, but the device complexity increases
Solution Approach 1:
The platform is divided into multiple hierarchical levels (first level, second level, third level) with distinct control functions. Each level handles specific communication tasks and data processing, allowing the complex system to be managed through modular, manageable segments rather than a monolithic structure.
Solution Approach 2:
The patent introduces a multi-dimensional control architecture with hierarchical levels and variable access permissions. This adds dimensions of control (level, user, context) that organize the complexity systematically, transforming a flat complex system into a structured multi-dimensional framework.
2Loss of information
If real-time contextually relevant data communication is enabled across multiple devices and users, then the information relevance and user experience are improved, but the data processing requirements and system resource consumption increase
Solution Approach 1:
The system processes and filters data locally at each hierarchical level, maintaining only the contextually relevant information for transmission upward. Each level applies local filtering based on its specific context, reducing the overall data processing burden while preserving information accuracy.
Solution Approach 2:
Context filtering and data preparation are performed in advance at lower hierarchical levels before data reaches higher levels. This preliminary processing reduces the computational load on upper levels and ensures that only refined, relevant information is transmitted across the network.
3Reliability
If multi-level control and variable access permissions are implemented, then the system security and access management are improved, but the control mechanism complexity increases
Solution Approach 1:
Access control is segmented into multiple hierarchical levels, with each level having defined permissions and control authorities. This segmentation allows security to be implemented in manageable layers rather than requiring a single complex access control system.
Solution Approach 2:
The hierarchical control structure serves multiple functions simultaneously: it provides security access control, organizes data flow management, and enables contextual filtering. This multi-functionality reduces the need for separate mechanisms for each function.
4Adaptability or versatility
If sensor fusion and context awareness capabilities are integrated, then the contextual intelligence and communication relevance are improved, but the system complexity and integration requirements increase
Solution Approach 1:
Sensor inputs and context data are processed separately at different hierarchical levels according to their specific requirements. This segmentation allows diverse sensor types to be integrated without requiring a single complex integration mechanism, as each sensor stream can be handled independently at appropriate levels.
Data Source
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AI summary
[00467] An interactive, electronic network that enables multi-level control, variable access, multi-user communications of real-time contextually relevant data or information among network-connected devices, and actions based on those communications, as the network-connected devices move from one location to another and/or the data/information flow among those devices change over time.