Systems, apparatuses, and methods for a distributed robotic network of data collection and insight generation
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Solution Overview
Problem
Existing robotic systems collect a vast amount of data, much of which is of marginal utility for the robots' primary functions, but could be valuable for additional functionalities, human insights, or improved robotic efficiency.
Innovation Solution
A distributed robotic network with an AI marketplace system that aggregates data from various sources, including robotic devices, IoT devices, and stationary sensors, to generate insights. This system allows for data storage, dynamic filtering, and the execution of applications that utilize this data to produce actionable insights.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If robots collect extensive data from multiple sensors to improve operational capability, then the quantity and variety of available data increases, but most of the collected data is of marginal utility to the robots' primary functions
Solution Approach 1:
The patent segments data utility into two categories: data useful for robot operation (processed by robots) and data useful for human insight (processed by human operators). This segmentation allows the system to handle large volumes of data efficiently by routing different types to appropriate processing entities, resolving the contradiction between data quantity and utility.
Solution Approach 2:
The patent introduces a communication network as an intermediary between robots and human operators. This intermediary enables the transfer of collected data to human operators who can extract insights, thereby giving utility to data that would otherwise be of marginal value to the robots themselves.
2Quantity of substance
If a distributed system aggregates data from multiple sources including robots and IoT devices, then the wealth of available data increases for insight generation, but the complexity of managing and processing this distributed data increases
Solution Approach 1:
The patent creates a universal data marketplace that serves multiple functions: storing data from diverse sources, enabling robot operations, and facilitating human insight generation. This multi-functional platform reduces overall system complexity by providing a single infrastructure that handles various data processing needs.
Solution Approach 2:
The system enables self-service through automated data collection by robots and IoT devices, automatic data storage in the marketplace, and on-demand insight generation. This self-service approach reduces the need for complex centralized management while handling large volumes of distributed data.
3Productivity
If robots utilize collected data to improve their operational efficiency, then robotic productivity increases, but the data may be of marginal utility to the robots while being valuable for human insights
Solution Approach 1:
The patent merges robot operations with human insight generation by creating a unified data marketplace where data collected for robotic functions is simultaneously made available for human analysis. This merging ensures that data serves dual purposes: improving robotic efficiency while providing valuable insights to human operators.
Solution Approach 2:
The system implements feedback loops where insights generated from collected data are fed back to improve robot operations. This feedback mechanism ensures that data initially of marginal utility to robots becomes increasingly valuable as insights are extracted and applied, resolving the contradiction between robotic efficiency and data value.
Data Source
AI summary
Systems, apparatuses, and methods for a distributed network of data collection and insight generation by server are disclosed herein. According to at least one non-limiting exemplary embodiment, the server may be configured to receive data from a network of data sources, receive an application from an application creator, and execute the application based on the data from the network of data sources to generate at least one insight, wherein the network of data sources may comprise mobile robots, stationary devices, IoT (Internet of Things) devices, and/or public data sources. The at least one insight may be utilized by robots to improve efficiency of operation or by humans to gain useful insights to the environment in which the data sources operate.