Blockchain Map Crowdsourcing for Real-Time Data Verification
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current map data collection methods are resource-intensive and often result in outdated data, failing to provide real-time information, especially for indoor areas, and are inefficient in facilitating cooperation between data collectors and service providers in crowdsourcing models.
Innovation Solution
A blockchain-based crowdsourcing platform that enables map data collection and distribution through smart contracts, allowing data collectors to submit data directly to service providers, with automated processing and authorization, reducing the need for centralized management and increasing data accuracy and timeliness.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If traditional map data collection methods are used, then map data can be collected, but the data is incomplete, lacks real-time updates, and does not reflect actual road conditions
Solution Approach 1:
The system enables users to automatically contribute map data through their own device sensors and location information. Users passively provide location data, road condition images, and traffic information without manual intervention, transforming end-users into active data contributors who serve the system themselves
Solution Approach 2:
The system implements continuous feedback loops where user-contributed data is processed, validated, and used to update map information in real-time. The blockchain network provides feedback mechanisms to verify and reward accurate data contributions, ensuring data quality while maintaining real-time update capabilities
2Reliability
If centralized server architecture is used, then map data can be stored and processed, but the system is vulnerable to single points of failure and security breaches
Solution Approach 1:
The system divides the centralized map data storage and processing function into multiple distributed nodes across the blockchain network. Each node maintains a copy of the map data and can independently validate and process data contributions, eliminating single points of failure while distributing system complexity across multiple participants
Solution Approach 2:
Different blockchain nodes perform specialized functions such as data validation, storage, and processing based on their local capabilities. The system allows nodes to contribute different types of data (location, images, traffic information) and process them locally before consensus, reducing overall system complexity while maintaining high availability
3Productivity
If user contributions are not verified, then data collection is simple, but the system is susceptible to fraudulent or inaccurate data
Solution Approach 1:
The system implements automated feedback mechanisms where contributed data is validated against multiple criteria including consistency with existing map data, plausibility checks, and cross-verification with other user contributions. Blockchain smart contracts automatically verify data authenticity and reward verified contributions, maintaining high data accuracy without reducing collection efficiency
Solution Approach 2:
The system performs preliminary validation and verification of user contributions before incorporating them into the map database. Data is pre-screened for basic accuracy criteria, and the blockchain network pre- validates contributor credentials and data format compliance before full processing, ensuring accuracy while maintaining efficient data collection
Data Source
Figure 1
Figure 2
Figure 3
AI summary
Map data is received at a map-service provider associated with a blockchain from a data collector. The map data is transmitted to a data-service provider for processing. Non-crowdsourced data is received at the map-service provider from a data provider. The non-crowdsourced data is transmitted to the data-service provider for processing with the map data. A request is received for processed map data from a service user. The processed map data that is generated from the map data and the non-crowdsourced data is retrieved from the data-service provider. The processed map data is transmitted to the service user in response to the request.