Multimodal Crowdsourcing Workflow for Sensor Data Alignment
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Solution Overview
Problem
Current crowdsourcing and microtasking platforms lack a streamlined workflow for defining projects that collect multimodal data from various sensors on modern electronic devices, limiting their ability to efficiently utilize the diverse sensing capabilities of workers.
Innovation Solution
A software and hardware facility is developed to provide a tailored workflow for customers to define multimodal data collection projects, allowing for the collection and processing of data from multiple sensor types using smartphones and fitness wearables, including heart rate, location, and other sensor data, with features like data synchronization and alignment.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If a traditional crowdsourcing platform uses a general-purpose task definition interface, then it can accommodate diverse task types, but it lacks streamlined workflow for defining multimodal data collection projects
Solution Approach 1:
The patent segments the project definition workflow into distinct modular steps: configuring crowd parameters, setting environment parameters, selecting sensor types, defining data collection parameters, and specifying processing requirements. Each step is independently configurable through specialized interface elements, allowing customers to systematically define complex multimodal data collection projects without being overwhelmed by a monolithic interface.
Solution Approach 2:
The interface dynamically adapts based on customer selections. When customers select specific sensor types (e.g., heart rate sensor, location sensor), the workflow automatically presents relevant configuration options and parameters. The interface evolves through the workflow, showing only necessary controls for each project type, making the system both versatile and easy to operate.
2Productivity
If the platform collects data from multiple sensor types simultaneously, then it enhances data collection efficiency, but it increases complexity in data synchronization and alignment
Solution Approach 1:
The patent implements preliminary action by having customers pre-configure all data synchronization and alignment parameters during project definition. Customers specify timing relationships, synchronization protocols, and alignment criteria before data collection begins. This upfront configuration eliminates the need for complex real-time synchronization logic during execution, simplifying the actual data collection process while maintaining high efficiency.
Solution Approach 2:
The patent introduces an intermediary processing layer that handles multimodal data from various sensors. This intermediary component receives data from different sensor types, applies pre-configured synchronization and alignment rules, and outputs integrated results. This mediator abstracts the complexity of multimodal data integration from the customer interface while enabling efficient parallel data collection from multiple sensors.
Data Source
AI summary
A facility for providing a workflow tailored to defining a project for collecting multimodal data from each of a set of crowdsourcing or microtasking platform workers is described. The facility enables customers of a crowdsourcing or microtasking platform to easily define multimodal data collection projects. The facility enables customers to define any of the following types of information associated with multimodal data collection projects: worker requirements, project environment parameters, video data, audio data, physiological data, and/or location-related data. Some of this data is collected using different kinds of sensors in one or more devices (e.g., smart phones, fitness wearables, etc.) associated with the crowdsourcing or micro-tasking platforms' workers. Prior to computing data results generated by executing a multimodal data collection project, the facility an align at least a first portion of the collected data with a second portion of the second data.