Sensor Data Valuation Algorithm for Gateway Assignment
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Solution Overview
Problem
In IoT sensor networks, there is a lack of feedback on the value of data being exported to higher-level business logic, leading to inefficient data distribution, potential data security risks, and inadequate maintenance of sensors, as the value of sensor data is unknown at the point of ingest, resulting in suboptimal management and security measures.
Innovation Solution
Implementing data valuation techniques that calculate the value of sensor data using algorithms and cascade this value back to gateways and sensors, enabling informed decisions on data transformation, security, and maintenance, such as encrypting high-value data and prioritizing sensor maintenance based on its value.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If data is distributed from sensors to higher-level business logic without valuation, then data flow is maintained, but data security risks increase and resource allocation becomes inefficient
Solution Approach 1:
The system performs data valuation at the point of data ingest, before data is distributed to higher-level business logic. This preliminary valuation determines the security requirements and resource allocation for each data element, allowing appropriate security measures to be applied only to high-value data rather than all data uniformly.
Solution Approach 2:
The invention applies different security measures and resource allocation strategies to different data elements based on their individual valuation. High-value data receives enhanced security measures such as encryption and prioritized maintenance, while low-value data uses standard processing, creating localized quality adjustments throughout the data pipeline.
2Productivity
If all sensor data is processed and distributed uniformly, then complete data availability is maintained, but processing efficiency decreases and business value is not optimized
Solution Approach 1:
The system changes the parameter of data prioritization based on valuation results. High-value data is assigned higher priority for processing, maintenance, and security measures, while low-value data receives standard or reduced processing. This parameter change optimizes overall system productivity by focusing resources on the most valuable data.
Solution Approach 2:
The invention implements a feedback loop where valuation results are fed back into the data management system to influence processing decisions. The valuation information flows back to determine which data elements require enhanced processing, maintenance, or security measures, creating a closed-loop system that continuously optimizes resource allocation based on actual data value.
3Reliability
If data valuation algorithms are implemented at the gateway, then data security and resource allocation improve, but system complexity increases
Solution Approach 1:
The gateway acts as an intermediary between sensors and higher-level business logic, incorporating data valuation algorithms to assess and prioritize data before it leaves the edge device. This intermediary function allows the valuation logic to be centralized at the gateway rather than distributed across all sensors or centralized in the cloud, managing system complexity while improving data management quality.
Data Source
AI summary
Data valuation techniques in a sensor data environment are provided. For example, a method obtains at least one sensor data element generated by at least one sensor associated with a set of one or more sensors operatively coupled to a gateway. At least one data valuation algorithm is applied to the at least one sensor data element to compute at least one value. The computed value is distributed for assignment to one or more of the gateway, the at least one sensor, and the at least one sensor data element.