Traffic Safety Server Decision Layer Model
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Solution Overview
Problem
The increasing frequency and severity of traffic accidents due to vehicle malfunctions, inadequate transportation infrastructure, environmental factors, and driver-related issues pose challenges in real-time monitoring and quick response to prevent and manage traffic incidents.
Innovation Solution
A method and apparatus utilizing IoT sensors to monitor transportation infrastructure and vehicles in real-time, employing a decision layer model to classify sensor data, calculate safety scores, and predict traffic incidents, allowing for quick decision-making and simulation to prevent secondary damage.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If IoT sensors are deployed to monitor transportation infrastructure and vehicles in real-time, then traffic incident prevention capability is improved, but system complexity and cost increase
Solution Approach 1:
The system divides the monitoring network into multiple layers: sensor layer (data collection), network layer (data transmission), and application layer (data processing and analysis). This segmentation allows each layer to be developed and maintained independently, reducing overall system complexity while enabling comprehensive real-time monitoring of transportation infrastructure and vehicles.
Solution Approach 2:
A gateway device is introduced as an intermediary between sensors and the central server. The gateway performs local data preprocessing, filtering, and protocol conversion, which reduces the burden on the central server and simplifies the communication architecture. This intermediary layer enables reliable traffic incident prevention through distributed intelligence.
2Measurement precision
If comprehensive sensor data is collected and processed centrally, then measurement precision and safety scoring accuracy are improved, but data transmission time and processing delay increase
Solution Approach 1:
The gateway device performs preliminary data processing including filtering, aggregation, and preliminary analysis before transmitting data to the central server. This preliminary action reduces the volume of data requiring central processing and enables faster generation of safety scores, thereby improving both measurement precision and reducing time loss.
Solution Approach 2:
The system implements a two-stage processing approach where critical safety parameters are processed partially at the gateway level for immediate safety scoring, while comprehensive analysis is performed centrally. This partial action at the edge enables timely safety assessments without sacrificing the precision benefits of comprehensive central processing.
3Reliability
If real-time safety monitoring and incident prediction are implemented, then traffic safety is improved, but computational resources and energy consumption increase
Solution Approach 1:
Computational tasks are segmented and distributed across multiple devices: sensors perform local data acquisition, gateways perform preliminary processing and filtering, and the central server performs comprehensive analysis. This segmentation reduces the computational burden on any single device, lowering overall energy consumption while maintaining high traffic safety through distributed real-time monitoring and incident prediction.
4Difficulty of detecting and measuring
If multiple sensors and processing layers are deployed, then detection capability and incident prediction accuracy are improved, but device complexity and maintenance difficulty increase
Solution Approach 1:
The gateway device is designed as a universal multi-functional unit that can handle multiple sensor types, perform various data processing operations, and support different communication protocols. This universality reduces the number of specialized devices needed, simplifies the overall system architecture, and eases maintenance by providing a standardized interface and configuration framework for diverse sensing and processing functions.
Data Source
AI summary
A method for providing a traffic safety service of a traffic safety service server communicating with a client terminal includes: receiving sensor data of each sensor from the client terminal; classifying the sensor data into data according to at least one specific time slot for each sensor and calculating a safety score of each of the at least time slot; calculating an average of the safety scores of the at least time slot and calculating a safety score for each sensor, and calculating a safety index on the basis of the safety score for each sensor and a weight assigned to each sensor.