Dynamic Traffic Transfer System Using ML Event Detection
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Solution Overview
Problem
The existing DSA technology for traffic transfer in IoT systems has inefficiencies due to statically determined transfer destinations, leading to reduced transfer and application processing efficiency, especially with the rapid increase in IoT devices and varying service requirements.
Innovation Solution
A traffic transfer system that dynamically identifies service-supported events using machine learning, selectively transferring high-bit-rate traffic data only when necessary by leveraging low-bit-rate data from IoT devices, and adjusting IoT device operation based on event detection, thereby enhancing transfer and processing efficiency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If DSA technology is used to transfer high-bit-rate traffic data from all IoT devices, then service quality is maintained, but transfer efficiency and application processing efficiency are lowered due to unnecessary data transfer
Solution Approach 1:
The system performs preliminary action by collecting and analyzing low-bit-rate traffic data before transferring high-bit-rate video data. The traffic transfer apparatus analyzes sensor data (acceleration, illuminance, sound, humidity, temperature, rainfall) to predict whether a service-supported event will occur, and only then triggers transfer of high-bit-rate data from cameras in the predicted area, avoiding unnecessary data transfer.
Solution Approach 2:
The patent introduces low-bit-rate traffic data as an intermediary that mediates between IoT devices and the traffic analysis apparatus. This intermediary data serves as a trigger mechanism that enables conditional transfer of high-bit-rate data, allowing the system to maintain service quality while improving transfer efficiency by filtering out unnecessary data.
2Reliability
If high-bit-rate traffic data is transferred continuously from all IoT devices, then service quality is maintained, but loss of energy and loss of substance increase
Solution Approach 1:
The system performs preliminary analysis of low-bit-rate sensor data before activating camera recordings. The traffic transfer apparatus predicts service-supported events using sensor information and only triggers high-bit-rate data transfer when events are detected, significantly reducing energy consumption compared to continuous monitoring and transfer.
Solution Approach 2:
The system transitions from continuous periodic transfer to event-driven periodic transfer. High-bit-rate data is transferred periodically only when service-supported events are detected through low-bit-rate data analysis, reducing energy consumption while maintaining service quality through selective data transfer.
3Device complexity
If static traffic transfer destinations are used, then device complexity is reduced, but adaptability to changing service requirements and events is lowered
Solution Approach 1:
The patent implements dynamics by transitioning from static transfer destinations to dynamic, event-driven transfer destinations. The traffic transfer apparatus determines transfer destinations based on real-time analysis of low-bit-rate data and prediction of service-supported events, allowing flexible adaptation to changing service requirements while maintaining manageable complexity through automated decision-making.
Data Source
AI summary
A data collection apparatus in a traffic transfer system collects and transfers low-bit-rate traffic data from an IoT device, and transfers high-bit-rate traffic data in an identified area. A traffic transfer apparatus performs determination as to whether or not a service-supported event occurs, by inputting the low-bit-rate traffic data into a learner and, when occurrence is determined, acquires and transfers the high-bit-rate traffic data in the identified area. The traffic transfer apparatus causes the learner to relearn a result of analysis of the transferred high-bit-rate traffic data and the low-bit-rate traffic data used in the determination.