IoT Events Dictionary Generation via Local State Monitoring
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Solution Overview
Problem
In a distributed Internet of Things (IoT) network, there is a lack of an efficient mechanism to automatically generate a machine-to-machine (M2M) events dictionary, which is essential for inter-operability among IoT devices from different vendors, as traditional methods require significant collaboration and a centralized infrastructure.
Innovation Solution
An Events Monitor and Dictionary Generator (EMDG) component is introduced to monitor events in the IoT network, compare states of IoT devices before and after events, and create generic entries for common state changes, mapping diverse event descriptions to a unified dictionary, allowing IoT devices to understand and respond to M2M events without prior collaboration among vendors.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If traditional centralized methods are used to generate M2M events dictionary, then inter-operability among IoT devices can be achieved, but significant collaboration and centralized infrastructure are required, increasing device complexity and deployment difficulty
Solution Approach 1:
The system enables automated generation of M2M events dictionary through local monitoring and analysis of device events. Each IoT gateway independently observes events from connected devices, extracts state changes, and generates the events dictionary locally without requiring centralized collaboration infrastructure, thereby achieving inter-operability while reducing deployment complexity
Solution Approach 2:
The IoT gateway acts as an intermediary between diverse IoT devices and the events dictionary generation process. It monitors events from multiple device types, standardizes the event data, and generates the unified M2M events dictionary, enabling inter-operability without direct collaboration between device vendors
2Extent of automation
If automated event monitoring and dictionary generation is implemented, then centralized infrastructure requirements are eliminated, but significant data processing and analysis capabilities are needed, increasing device complexity
Solution Approach 1:
The automated dictionary generation process is segmented into distinct functional modules: event monitoring module that collects device events, state change detection module that identifies transitions, and dictionary generation module that creates the M2M events dictionary. This modular approach distributes processing complexity across separate components, making the system more manageable while achieving high automation
Solution Approach 2:
The system performs preliminary monitoring and collection of device events before generating the M2M events dictionary. By continuously observing device states and capturing event data in advance, the system prepares the necessary information groundwork, reducing the computational burden during actual dictionary generation and lowering overall processing complexity
Data Source
AI summary
Methods and systems are disclosed for automatically generating an events dictionary in an Internet of Things (IoT) network. In an aspect, a device receives a notification of an event from an IoT device, determines a state of the IoT device before and after the event, compares the states of the IoT device, determines a type of state change of the event, determines whether the type of the state change of the first event is present in the events dictionary, creates a generic entry based on the type of the state change of the first event not being present in the events dictionary, and stores, in the events dictionary, a mapping of an event description of the event to the generic entry.