Meta Model Data Compression for Low-Volume IoT Transmission
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Solution Overview
Problem
Current methods for monitoring power amount data from new renewable energy sources using meta model protocols face challenges in low volume transmission over IoT networks, which are prone to errors due to slow transmission rates and higher costs compared to IoT networks.
Innovation Solution
A method and system for transforming meta model data into packet meta model data using a key table, dividing, and compressing it for transmission over IoT networks, specifically using LoRa technology, to ensure efficient and error-free data transmission while maintaining data integrity.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If TCP/IP dedicated line or LTE wireless communication network is used for monitoring, then data transmission reliability is improved, but transmission cost increases to 20,000-30,000 won per month
Solution Approach 1:
The patent changes the transmission parameters by compressing meta model data into packet format with optimized data structures, enabling reliable transmission over cost-effective IoT networks while maintaining data integrity
Solution Approach 2:
The patent uses inexpensive IoT communication networks instead of expensive TCP/IP or LTE networks, accepting lower individual transmission reliability but achieving overall system reliability through data validation and error handling mechanisms
2Loss of energy
If IoT network is used for data transmission, then transmission cost is reduced to 200-2200 won per month, but transmission errors increase due to slow transmission rate
Solution Approach 1:
The patent segments meta model data into smaller packet units with headers containing validation information, enabling error detection and recovery during transmission over unreliable IoT networks
Solution Approach 2:
The patent implements feedback mechanisms through packet acknowledgments and data validation checks, allowing the system to detect and correct transmission errors that occur over low-quality IoT connections
3Loss of information
If meta model data is transmitted in full format, then data completeness is maintained, but transmission volume is too large for IoT networks
Solution Approach 1:
The patent extracts only the essential data elements from the full meta model structure, transmitting minimal necessary information in packet format while maintaining data completeness for monitoring purposes
Solution Approach 2:
The patent transforms the data representation from full meta model format to a compressed packet dimension, encoding data in a more compact form that fits within IoT network transmission constraints
Data Source
AI summary
Disclosed herein is a method for transforming data for low volume transmission of a meta model based protocol which monitors power amount data of new renewable energy, including: generating energy sensing data; receiving, by a client, the energy sensing data and transforming the received energy sensing data into meta model data including a meta model and meta data; generating packet meta model data by dividing and compressing the meta model data; transmitting the packet meta model data to a server through an Internet of Things (IOT) communication network; and parsing, by the server, the packet meta model data to output the meta model data.