Opportunistic Crowd-Based Service Platform for Mobile Sensor Data Aggregation
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Solution Overview
Problem
Current crowd-based service platforms lack an efficient method to opportunistically collect and aggregate data from multiple locations using mobile devices, limiting their ability to provide targeted and high-quality information to users.
Innovation Solution
A system and method that utilizes mobile devices as a network of sensors to opportunistically collect data based on their current locations, aggregates and processes this information, and delivers generated content to users through a platform comprising a collection module, database, data provisioning module, data analysis module, and service layer.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If mobile devices are used as a network of sensors to collect data from multiple locations, then data collection efficiency and coverage are improved, but data quality control and aggregation complexity increase
Solution Approach 1:
The system segments data collection by selecting mobile devices based on their current locations to target specific areas for data gathering. The data is then segmented by type (e.g., audio, video, image) and processed through specialized modules (audio module, video module, image module) that handle each data type separately, reducing overall aggregation complexity while maintaining high collection efficiency
Solution Approach 2:
A central server acts as an intermediary between mobile sensor devices and the final content delivery system. The server receives raw data from multiple locations, aggregates and processes it through various modules, and then delivers processed content to users. This intermediary layer manages the complexity of data aggregation centrally while allowing distributed data collection from mobile devices
2Adaptability or versatility
If data is collected opportunistically from mobile devices, then service adaptability and user engagement are improved, but data quality assurance becomes more difficult
Solution Approach 1:
The system implements feedback mechanisms where the server monitors the quality of data received from mobile devices and provides feedback to improve data collection. Quality assessment is performed continuously, and the system adjusts collection parameters or selects devices based on their historical performance and current location accuracy, ensuring high data quality while maintaining opportunistic collection
Solution Approach 2:
The system changes collection parameters dynamically based on device capabilities, location accuracy, and data quality requirements. Different mobile devices are selected based on their current locations and capabilities, and collection parameters are adjusted to optimize both adaptability to different scenarios and data quality for the specific service being provided
3Quantity of substance
If multiple types of data are aggregated from various locations, then content richness and service quality are improved, but processing time and system resources increase
Solution Approach 1:
The system segments data processing by type, with dedicated modules for audio, video, and image data. Each module processes its specific data type independently using appropriate algorithms, reducing the processing time for multi-type data aggregation compared to a monolithic processing approach, while still producing rich, integrated content
Solution Approach 2:
The system performs preliminary processing actions at the mobile device level before data reaches the server, such as preliminary filtering, encoding, and formatting. This preliminary action reduces the amount of data that needs to be processed centrally, thereby reducing overall processing time while maintaining content richness through comprehensive data aggregation
Data Source
AI summary
A method and apparatus for providing an opportunistic crowd based service platform is disclosed. A mobile sensor device is identified based on a current location and/or other qualities, such as intrinsic properties, previous sensor data, or demographic data of an associated user of the mobile sensor device. Data is collected from the mobile sensor device. The data collected from the mobile sensor device is aggregated with data collected from other sensor devices, and content generated based on the aggregated data is delivered to a user device.