Multi-dimensional Array Indexing for Sensor Data Retrieval
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Solution Overview
Problem
Existing sensor networks face challenges in efficiently indexing and querying large volumes of multi-dimensional sensor data, particularly in real-time environments, due to the complexity of spatial and temporal data correlations, which hinders effective data retrieval and analysis.
Innovation Solution
A hierarchical multi-sink sensor network architecture that utilizes a multi-dimensional array indexing system, where sensor data is aggregated and indexed using spatial and temporal dimensions, allowing for efficient querying and data retrieval through a search engine that translates user queries into the indexed format, and employs secure communication protocols to manage data access.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If sensor data is indexed using traditional methods, then data retrieval is simple, but retrieval efficiency deteriorates with large volumes of multi-dimensional sensor data
Solution Approach 1:
The patent applies multi-dimensional array indexing where sensor data is organized along multiple dimensions including spatial coordinates and temporal sequences. This dimensional transformation enables efficient querying of complex sensor networks by mapping multi-dimensional data relationships into a structured array format, resolving the contradiction between retrieval efficiency and system complexity.
2Productivity
If sensor data is aggregated and indexed in real-time, then data analysis efficiency is improved, but energy consumption increases
Solution Approach 1:
The system performs preliminary aggregation and indexing of sensor data in real-time, organizing data into multi-dimensional arrays before queries are executed. This advance preparation reduces the computational burden during actual data retrieval operations, improving analysis efficiency while managing energy consumption through proactive data organization rather than reactive processing.
3Reliability
If comprehensive sensor data is stored for analysis, then data integrity is improved, but storage requirements and access complexity increase
Solution Approach 1:
The patent segments sensor data into distinct multi-dimensional arrays based on spatial and temporal characteristics. This segmentation preserves complete sensor data for integrity purposes while organizing it into manageable segments that can be efficiently queried and accessed, reducing the complexity of managing comprehensive datasets through structured division.
Data Source
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AI summary
In particular embodiments, a method includes receiving a query for particular sensor data among multiple sensor data from multiple sensors. The plurality of sensor data has been indexed according to a multi-dimensional array. One or more first ones of the dimensions include time, and one or more second ones of the dimensions include one or more pre¬ determined sensor-data attributes. The method includes translating the query to correspond to the indexing of the plurality of sensor data. The translated query includes one or more values for one or more of the dimensions of the multi-dimensional array. The method includes communicating the translated query to search among the plurality of sensor data according to its indexing to identify the particular sensor data.