Mobile Agent Network for Real-Time Road Data Digitization
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Solution Overview
Problem
Conventional systems for gaining visibility of road conditions are expensive, limited in geographical coverage, and unable to provide real-time insights, as they rely on expensive stationary hardware or mobile hardware that struggles to capture and update large amounts of data effectively.
Innovation Solution
A collaborative network system utilizing edge devices like smartphones and cloud nodes to digitize and map public spaces in real-time, leveraging mobile agents with cameras and sensors to capture data on-demand, and employing cloud-based machine learning for scene understanding, which generates high-frequency localized road data and provides insights into traffic patterns and infrastructure management.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional stationary hardware systems are used to gain visibility of road conditions, then measurement precision is improved, but device complexity and cost increase significantly
Solution Approach 1:
The patent replaces expensive stationary hardware with mobile devices (smartphones, tablets) that are already widely deployed. These devices capture road data temporarily during their normal operation, eliminating the need for permanent infrastructure installation. The mobile devices are inexpensive compared to stationary systems and can be deployed rapidly across large geographic areas.
Solution Approach 2:
The system creates digital copies of road conditions through images and sensor data captured by mobile devices. These digital representations are then processed and stored in the cloud, allowing multiple users and applications to access the same road condition information without requiring physical presence or additional hardware at the location.
2Area of stationary object
If mobile hardware systems are used to capture road data, then geographical coverage is improved, but data update frequency and real-time capability deteriorate
Solution Approach 1:
The patent combines mobile data collection devices with cloud-based processing infrastructure. Mobile devices capture data across wide geographic areas, while the cloud system aggregates, processes, and distributes this data in real-time. This merging allows the system to maintain both extensive coverage and high update frequency, as the cloud can process multiple data streams simultaneously and push updates to users instantly.
Solution Approach 2:
The cloud-based platform serves as an intermediary between mobile data collectors and end users. It receives raw data from numerous mobile devices, processes and validates the information, then distributes processed road condition data to users in real-time. This intermediary layer enables scalable real-time updates across large geographic areas without requiring direct peer-to-peer communication between mobile devices and users.
3Productivity
If mobile agents capture data continuously, then data update frequency is improved, but communication overhead and energy consumption increase
Solution Approach 1:
The system implements selective data transmission where mobile devices only send road condition data when changes are detected or when requested by the cloud platform. Rather than continuously transmitting all sensor data, the system transmits only relevant updates (e.g., when a new obstacle is detected, road conditions change, or traffic patterns shift). This partial action approach maintains high data freshness while dramatically reducing communication overhead and energy consumption.
Solution Approach 2:
The cloud-based platform implements a feedback mechanism where it queries mobile devices for specific road condition information based on user requests or system needs. Instead of continuous one-way transmission, the cloud sends targeted queries and receives only the necessary data responses. This feedback-driven approach optimizes communication by transmitting only the data that is currently needed, reducing energy consumption while maintaining real-time capability.
Data Source
AI summary
A networked system for providing public space data on demand, including a plurality of vehicles driving on city and state roads, each vehicle including an edge device with processing capability that captures frames of its vicinity, a vehicle-to-vehicle network to which the plurality of vehicle are connected, receiving queries for specific types of frame data, propagating the queries to the plurality of vehicles, receiving replies to the queries from a portion of the plurality of vehicles, and delivering matched data by storing the matched data into a centralized storage server, and a learner digitizing the public space in accordance with the received replies to the queries.