IoT Automation Policy Verification Using Integrated Behavior Models
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Solution Overview
Problem
Traditional systems for controlling IoT automation systems lack dynamic verification of control logics, leading to inefficiencies in identifying policy violations due to static analysis, which fails to account for the dynamic behavior of variables in real-time system operation.
Innovation Solution
A method and system for dynamically verifying control logics in IoT automation systems by constructing an integrated model that incorporates rules, building energy, ambient temperature, and occupancy count models, allowing for the identification of policy violations through a Model Verifier Component, which checks for conflicts in rule executions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If static analysis of system models is used to control IoT automation systems, then the system structure is simple and easy to implement, but the ability to identify policy violations dynamically is insufficient
Solution Approach 1:
The patent segments the system model into multiple independent sub-models including building energy model, ambient temperature model, occupancy count model, and rules model. Each sub-model handles specific aspects of system behavior, allowing dynamic verification without requiring a single complex monolithic model. This segmentation enables targeted analysis of policy violations while maintaining manageable model complexity.
Solution Approach 2:
The patent implements dynamic verification by constructing integrated models that can be executed with varying input parameters representing different system states. The model checker dynamically evaluates control logics across multiple scenarios by varying environmental conditions, occupancy patterns, and energy consumption levels, enabling identification of policy violations that static analysis would miss.
2Measurement precision
If dynamic verification through integrated models is implemented, then policy violation identification accuracy improves, but the time and computational resources required increase
Solution Approach 1:
The patent performs preliminary construction of integrated models before actual verification execution. The building energy model, ambient temperature model, occupancy count model, and rules model are pre-configured with their respective parameters and relationships. This preliminary setup enables faster execution during verification by avoiding repeated model construction, thus reducing the time loss associated with dynamic verification.
3Adaptability or versatility
If multiple sub-models are integrated for comprehensive verification, then system behavior coverage is improved, but the integrated model construction complexity increases
Solution Approach 1:
The patent creates a universal integrated model framework that can accommodate multiple types of sub-models (building energy, ambient temperature, occupancy count, rules). This framework uses standardized interfaces and parameter structures that allow different sub-models to be combined systematically. The model checker is designed to work with this universal framework, enabling comprehensive system behavior verification without requiring separate verification processes for each sub-model type.
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AI summary
Identifying policy violations for controlling behavior of an Internet of Things (IoT) automation system is provided. Traditional systems and methods provide for controlling IoT based automation system based upon a static analysis of a system model and rules. The embodiments of the proposed disclosure provide for controlling behavior of the IoT automation system by identifying one or more policy violations, wherein the one or more policy violations are identified by generating a plurality of models representing behavior, relationships and functions of one or more sub-systems corresponding to the IoT automation system; extracting a set of modelled rules; constructing, using each of the plurality of models and the set of modelled rules, an integrated model; and identifying, from the integrated model, the one or more policy violations via a Model Verifier Component for controlling behavior of the IoT automation system.