Distributed NFSM Rule Engine for Context-Aware Mesh Devices
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Solution Overview
Problem
Conventional IoT automation systems lack the ability to provide users with context and decision-making capabilities, leading to user confusion and potential conflicts between user actions and system states, which can result in safety concerns.
Innovation Solution
Implement a control mesh node that generates non-deterministic finite-state machine (NFSM) models for IoT devices, providing additional context and allowing dynamic rule definition, and enables real-time state updates with explanations, while supporting mobility and environmental changes.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If conventional IoT automation systems are used, then device control is achieved, but user understanding of system states is poor leading to confusion and conflicts
Solution Approach 1:
The patent implements a feedback mechanism where the system continuously monitors device states and provides explanations to users about why state changes occur. The NFSM model generates human-readable explanations that feedback to users, transforming internal system states into understandable information that reduces user confusion and improves comprehension of device behavior.
Solution Approach 2:
The patent introduces an intermediary layer (the NFSM model and explanation generation system) between the physical IoT devices and the user. This intermediary translates complex device states and transition logic into comprehensible explanations, serving as a mediator that bridges the gap between system operations and user understanding.
2Loss of energy
If distributed rule engine is deployed to edge devices, then bandwidth usage is reduced, but device complexity increases
Solution Approach 1:
The patent segments the rule engine functionality and distributes it across multiple edge devices in the mesh network. Instead of centralizing all processing, the system divides rule evaluation capabilities among devices, allowing local decision-making that reduces bandwidth consumption while managing complexity through modular distribution rather than centralized burden.
Solution Approach 2:
The patent creates a universal NFSM model that can be deployed across multiple device types and scenarios. This multi-functional model serves different purposes (state tracking, rule evaluation, explanation generation) across various edge devices, reducing the need for device-specific implementations and managing complexity through a unified approach.
Data Source
AI summary
A system and method of a distributed and partitioned state machine for mesh devices. The method includes obtaining a first capability dataset indicating capabilities of a first mesh node of a first mesh network system to provide a first service for a first object. The method includes obtaining a second capability dataset indicating capabilities of a second mesh node of a second mesh network system to provide a second service to a second object. The method includes generating a set of NFSM models for the first object and the second object, each NFSM model to provide the first service for the first object or the second object. The method includes providing the set of NFSM models and a partition dataset to cause a first gateway device and a second gateway device to use a single NFSM model to provide the first service to the second object.