IoT Data Stream Integration via Schedule Objects
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
The increasing amounts of data from IoT devices pose challenges in efficient processing and utilization, particularly in managing and interacting with this data effectively, as existing systems struggle to provide efficient processing and user-friendly interfaces for real-time data management and automation.
Innovation Solution
A monitoring component that utilizes schedule data objects to associate, process, and display information from IoT devices, enabling categorization, alert generation, and automated actions based on predefined conditions, along with a data aggregation and visualization service that renders information in a user-friendly format, facilitating efficient data management and automation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If data from multiple IoT devices are collected and processed, then the amount of available information increases, but the complexity of processing and managing the data increases
Solution Approach 1:
The patent segments the data processing system into multiple independent components: a monitoring component that receives and categorizes data from IoT devices, a data aggregation service that processes and stores data, and a visualization service that presents processed information. This segmentation allows each component to handle specific tasks independently, reducing overall system complexity while managing large volumes of data effectively.
Solution Approach 2:
The patent introduces intermediary elements such as schedule data objects and activity definitions that act as mediators between raw IoT data and user-facing applications. These intermediaries standardize data formats, define processing rules, and enable automated responses without requiring complex custom processing logic for each data stream, thereby simplifying the management of multiple data sources.
2Speed
If real-time processing of IoT data is implemented, then the responsiveness of the system improves, but the computational resources required increase
Solution Approach 1:
The patent implements preliminary action by pre-defining schedule data objects, activity definitions, and response rules before data arrives. When IoT devices send data, the system matches incoming data against pre-configured criteria and triggers predefined responses, eliminating the need for complex real-time analysis and reducing computational overhead while maintaining fast response times.
Solution Approach 2:
The patent applies partial action by processing only the specific portions of IoT data that match predefined activity definitions and schedule criteria. Rather than analyzing all incoming data streams in full detail, the system selectively processes relevant data points, reducing overall computational resource consumption while maintaining real-time responsiveness for critical operations.
3Productivity
If automated actions and alerts are generated based on sensor data, then the operational efficiency improves, but the system complexity increases
Solution Approach 1:
The patent implements self-service automation where the system automatically monitors IoT device data, compares it against predefined criteria, generates alerts, and executes actions without human intervention. Schedule data objects and activity definitions enable the system to autonomously determine when conditions are met and automatically trigger appropriate responses, improving operational efficiency while the standardized framework keeps complexity manageable.
4Ease of operation
If user interfaces for interacting with IoT data are created, then the ease of operation improves, but the time required to process and display data increases
Solution Approach 1:
The patent applies preliminary action by pre-configuring schedule data objects, activity definitions, and visualization templates before user interaction. When users access the system, data is already processed, categorized, and formatted according to predefined specifications, allowing user interfaces to display information immediately without requiring time-consuming processing or transformation at the moment of access.
Data Source
AI summary
Techniques and solutions are described for processing and displaying information received from a plurality of remote computing devices, such as internet of things (IOT) devices. Data from the IOT devices, including from sensors associated with the IOT devices, can be received and processed by a monitoring component. The monitoring component can include a plurality of schedule data objects, which can be associated with categories. Data received from the IOT devices can be associated with a category, including by associating the data with one of more of the schedule data objects. The schedule data objects can be used to determine information that will be rendered for display to a user. The schedule data objects can also be used to generate alerts or notifications, or to automatically taken actions based on triggers or conditions associated with a respective schedule data object.