Data Interworking Model and Analysis for Harmonization of Smart Metering Protocols in IoT-Based AMI System.

Area of Science:

• Energy sector
• Information Technology
• Telecommunications

Background:

• The convergence of Advanced Metering Infrastructure (AMI) and the Internet of Things (IoT) has blurred traditional boundaries.
• The Device Language Message Specification (DLMS) protocol remains dominant in the AMI industry for smart meters.
• Existing methods for integrating DLMS with IoT protocols like Lightweight Machine-to-Machine (LwM2M) face efficiency challenges.

Purpose of the Study:

• To propose a novel data interworking model that integrates the DLMS protocol within the LwM2M protocol for AMI systems.
• To establish a 1:1 conversion model by analyzing and correlating object modeling and resource management between DLMS and LwM2M.
• To leverage a RESTful architecture for improved efficiency in smart metering data management.

Main Methods:

• Developed a 1:1 conversion model correlating DLMS and LwM2M protocols.
• Analyzed object modeling and resource management specific to both LwM2M and DLMS.
• Implemented the model using a RESTful architecture, aligning with LwM2M's strengths.

Main Results:

• Achieved significant improvements in average packet transmission efficiency (52.9%p) and packet delay (9.9%p) for both plaintext and encrypted data.
• Reduced packet delay by 11.86 ms compared to KEPCO's current LwM2M encapsulation method.
• Demonstrated the model's effectiveness in enhancing data transmission performance.

Conclusions:

• The proposed model successfully unifies DLMS and LwM2M protocols for remote metering and device management in AMI.
• This integration is expected to substantially improve the operational and management efficiency of KEPCO's AMI system.
• The findings provide a key strategy for standardizing protocol usage in smart energy infrastructures.