IoT Data Transmission via Asynchronous Metering Queues
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Solution Overview
Problem
Existing Internet of Things (IoT) data transmission systems face challenges in layer separation and high synchronous transmission channel requirements, leading to inaccurate timestamps, limited remote upgrade capabilities, and increased error rates.
Innovation Solution
An IoT data transmission method and system that includes an IoT platform, concentrator, and meters, where downlink data is processed into asynchronous delivery queues based on forwarding priority, allowing the concentrator to autonomously execute and report periodic tasks, reducing the workload on the IoT platform and minimizing channel requirements.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If the concentrator is responsible for compatibility with multiple protocols (MODBUSTCP, IEC104, MQTT), then the function of the concentrator is strengthened, but the communication between the Internet of Things platform and the concentrator is separated from the communication between the concentrator and the meter, causing timestamp inaccuracy and insufficient remote upgrade capability
Solution Approach 1:
The patent introduces a standardized packet structure as an intermediary layer between the concentrator and meters. This packet format includes explicit timestamp fields and protocol-agnostic data structures that allow accurate time recording at the meter level while maintaining protocol compatibility through the concentrator. The intermediary packet structure resolves the separation issue by providing a common format that preserves timing information across protocol boundaries.
2Reliability
If the Internet of Things platform synchronously collects data from all meters, then the platform can communicate directly with underlying meters, but the synchronous collection manner has high requirements on real-time performance of the communication channel and is prone to error failure
Solution Approach 1:
The patent implements periodic metering tasks where the concentrator autonomously initiates data collection from meters at predetermined intervals. This periodic action eliminates the need for synchronous coordination between the platform and all meters simultaneously, reducing channel requirements while maintaining data freshness. The concentrator acts as an autonomous collector that periodically gathers data and forwards it to the platform asynchronously.
Solution Approach 2:
The patent establishes predetermined metering task schedules in advance, where the concentrator is configured with task parameters including timing information. This preliminary action allows the concentrator to autonomously execute data collection without real-time platform intervention, reducing the complexity of synchronous channel requirements while ensuring systematic data collection across all meters.
3Productivity
If each periodic metering task is actively initiated by the Internet of Things platform, then the platform maintains control, but the role of the concentrator is shelved and the platform workload increases
Solution Approach 1:
The patent enables the concentrator to autonomously manage periodic metering tasks by configuring task parameters in advance. The concentrator self-initiates data collection from meters according to predetermined schedules without requiring the platform to actively initiate each task. This self-service approach transfers the automation burden from the platform to the concentrator, reducing platform workload while maintaining systematic data collection.
Solution Approach 2:
The platform performs preliminary configuration of metering task parameters (such as collection intervals, data types, and timing) in advance, then the concentrator autonomously executes these pre-configured tasks. This preliminary action allows the concentrator to operate independently for routine data collection, reserving platform resources for higher-level management and analysis functions.
Data Source
AI summary
Disclosed are an Internet of Things data transmission data and system. The method comprises a downlink transmission step: obtaining first downlink data delivered by an Internet of Things platform; parsing the first downlink data to obtain a target meter of a metering task and a forwarding priority in a first packet; obtaining second downlink data; adding the second downlink data to an asynchronous delivery queue according to the forwarding priority; and delivering the second downlink data to the target meter according to the asynchronous delivery queue, so that the target meter completes the metering task. The present method makes full use of concentrators as intermediate devices while maintaining the integrity of core task data, lowers the channel requirement due to asynchronous execution and is especially suitable for periodic metering tasks.