Common Data Collection Infrastructure for Mobile Sensors
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Solution Overview
Problem
Existing data collection methods from networked devices, such as smartphones and sensors, are inefficient due to vertical integration, leading to resource competition, redundant data collection, and lack of flexibility, as each application requires its own software agent and middleware, resulting in inefficient data processing and high resource consumption.
Innovation Solution
A common infrastructure for real-time data collection from mobile devices and sensors, utilizing a phenomenon layer to specify data collection requirements and an edge layer to identify and process raw data, allowing for data reuse across multiple applications, improving bandwidth utilization and energy efficiency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If each application uses its own software agent and middleware for data collection, then the application can be optimized for its specific needs, but resource competition and redundancy occur leading to inefficiency
Solution Approach 1:
The patent merges multiple application-specific software agents and middleware into a single common infrastructure that serves multiple applications simultaneously. This common infrastructure includes shared data collection modules, processing pipelines, and resource management mechanisms that eliminate redundancy while maintaining application-specific functionality through configurable parameters and interfaces.
Solution Approach 2:
The patent creates a universal data collection infrastructure that can serve multiple different applications with diverse data needs. The system uses configurable data collection templates, parameterized processing pipelines, and adaptable interfaces that allow a single infrastructure to fulfill the specific requirements of different applications without requiring separate dedicated systems for each.
2Adaptability or versatility
If multiple applications collect the same raw data from physical sensors, then each application gets its needed data, but resources are consumed repeatedly causing waste
Solution Approach 1:
The patent implements continuous data collection at the infrastructure level where raw data from physical sensors is collected once and continuously made available to multiple applications. The system maintains persistent data streams and processing pipelines that prevent redundant collection actions, ensuring that the same physical sensing operations serve multiple applications simultaneously without repeated energy expenditure.
Solution Approach 2:
The patent introduces a common infrastructure as an intermediary layer between physical sensors and multiple applications. This intermediary collects, processes, and distributes raw data to all requesting applications through standardized interfaces, eliminating the need for each application to directly access and collect data from sensors independently.
3Reliability
If applications use customized middleware for their specific data needs, then the middleware is optimized for that application, but it cannot support diverse applications simultaneously
Solution Approach 1:
The patent implements a dynamic middleware architecture where processing pipelines, data collection parameters, and configuration settings can be adjusted at runtime to accommodate different application requirements. The system uses configurable templates and parameterized processing logic that can be dynamically instantiated and modified to serve diverse applications while maintaining a single shared infrastructure.
Solution Approach 2:
The patent employs parameter changes to enable a single middleware infrastructure to adapt to different application needs. By varying collection parameters, processing thresholds, data formats, and configuration settings, the same underlying middleware can be optimized for different applications without requiring separate customized implementations for each.
Data Source
AI summary
A common infrastructure collects diverse data and information from large numbers of mobile devices and traditional sensors at Internet scale to support multiple different applications simultaneously. The infrastructure includes a backend phenomenon layer that provides high level abstractions to applications such that they can express their data and information needs in a declarative fashion and coordinate the data collection and processing activities for all applications. An edge layer that manages devices, receives collection requirements from the backend layer, configures and instructs devices for data collection, and conducts aggregation and primitive processing of the data. This layer contains network edge nodes, such as base stations in a cellular network. Each node manages a set of local data generating networked devices. The device agent data layer using common agents on the data generating networked devices receives data collection instructions from the edge layer, performs data collection.