Cognitive Data Analytics for Vehicular Communication via 5G Orchestration
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current telecommunications networks, particularly in 5G environments, face challenges in effectively sharing real-time driving conditions and road information between vehicular devices, limiting the ability to provide timely and accurate data-driven insights for safe navigation and decision-making in dynamic traffic situations.
Innovation Solution
A cognitive data analytics system utilizing IoT-enabled devices within a 5G network's service orchestration layer to detect, collect, analyze, and exchange real-time data between vehicles traveling in opposite directions, providing critical information on road conditions and geography to enhance situational awareness and driver response.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If real-time data collection and exchange between vehicular devices is implemented using 5G network, then information availability and decision-making speed are improved, but network complexity and data processing requirements increase
Solution Approach 1:
The patent introduces a service orchestration layer as an intermediary between vehicular devices and the 5G network core. This layer manages data collection, processing, and distribution, reducing the complexity burden on individual vehicles while ensuring comprehensive information availability across the network.
Solution Approach 2:
The system segments data processing into multiple layers: edge processing at vehicular devices, intermediate processing at base stations, and core processing at the service orchestration layer. This segmentation distributes computational complexity across different nodes, preventing any single device from becoming overwhelmed while maintaining real-time information availability.
2Reliability
If data is collected from IoT devices in vehicles traveling in opposite directions to provide insights for the road ahead, then situational awareness is improved, but data collection complexity and communication overhead increase
Solution Approach 1:
The service orchestration layer implements a universal data collection mechanism that handles multiple data sources (IoT sensors, vehicle telematics, infrastructure sensors) and multiple communication scenarios (same-direction vehicles, opposite-direction vehicles, infrastructure-to-vehicle) through a single standardized interface, reducing overall system complexity.
Solution Approach 2:
The system implements feedback loops where data from vehicles traveling in opposite directions is collected, analyzed, and used to generate actionable insights that are fed back to relevant vehicles. This feedback mechanism enhances situational awareness by providing predictive information about road conditions, hazards, and traffic patterns ahead.
3Reliability
If cognitive data analytics is implemented to provide data-driven insights for navigation, then safety and decision-making quality are improved, but computational requirements and processing time increase
Solution Approach 1:
The service orchestration layer performs preliminary data filtering, validation, and preprocessing before data is sent to cognitive analytics engines. This preliminary action reduces the computational burden on real-time decision-making systems and ensures that only high-quality, relevant data is processed, thereby reducing overall processing time while maintaining safety.
Solution Approach 2:
The system implements local quality processing where data is processed at different levels of detail based on its relevance and urgency. Critical safety-related data receives immediate full processing, while less critical information undergoes lighter processing. This differentiated approach reduces overall processing time while ensuring that safety-critical decisions are made with comprehensive analysis.
Data Source
AI summary
The present disclosure includes using cognitive data analytics for communication between vehicular devices using a 5G (fifth generation cellular network technology) telecommunications network. In a defined area, using an Internet of Things (IoT) enabled device in a first vehicle traveling in a direction, the present disclosure detects a second vehicle traveling in another direction in the defined area. Data is collected in the defined area using the detected IoT devices in the first and second vehicles. The collected data is analyzed to provide content data related to driving conditions for the first and second vehicles. The content data is exchanged between the IoT devices of the first vehicle and the second vehicle in the defined area, thereby providing real-time information related to the driving conditions to a vehicle traveling in another direction, and the exchanging of the content data, using the service orchestration layer of the 5G telecommunications network.