Time-Series Data Shaping for Lower Monitoring Load
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Solution Overview
Problem
Existing data collection systems face high loads in transmitting and processing sequential time-series data from multiple sources, which can overwhelm network resources and processing capabilities in monitor control apparatuses.
Innovation Solution
A data collection apparatus is introduced to control and filter output data from various data sources, applying data shaping rules to reduce the amount of data transmitted to the monitor control apparatus, thereby alleviating the load on both the network and processing resources.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If all sequential time-series output data from data sources is transmitted to the monitor control apparatus, then complete data availability for phenomenon detection is improved, but data transmission load and processing load increase significantly
Solution Approach 1:
The data collection apparatus performs preliminary data shaping and filtering before transmission. It applies data shaping rules to aggregate, sample, or filter time-series data from multiple data sources, transforming raw data into a reduced and optimized format that retains essential information for phenomenon detection while minimizing transmission volume and processing requirements at the monitor control apparatus.
Solution Approach 2:
The data collection apparatus acts as an intermediary between data sources and the monitor control apparatus. It receives raw output data from data sources, applies data shaping rules to transform and reduce the data, and then transmits the shaped data to the monitor control apparatus, thereby reducing the burden on both the network and the monitor control apparatus while preserving detection capability.
2Loss of energy
If data shaping rules are applied to reduce transmitted data, then transmission load and processing load are reduced, but data transmission completeness may be compromised
Solution Approach 1:
The system dynamically adjusts data shaping parameters such as sampling intervals, aggregation periods, and filtering thresholds based on the specific characteristics of the data sources and the monitoring requirements. This allows optimization of data reduction while preserving the essential features needed for accurate phenomenon detection, balancing load reduction with information completeness.
Data Source
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AI summary
[PROBLEM] To reduce the load of transmission of output data and the load of processing in a monitor control apparatus configured to detect a possible phenomenon from the output data of various data sources. [SOLVING MEANS] A data collection apparatus according to embodiments includes a data collection section configured to receive sequential time-series output data pieces for each of data sources, a data shaping section configured to perform data shaping processing on the sequential time-series output data pieces based on a predetermined data shaping rule set for each of the data sources such that the resulting data pieces are reduced in number or in data amount as compared with the output data pieces output from the data source, a data transmission section configured to transmit the output data pieces to the monitor control apparatus, and a data shaping rule control section configured to receive the data shaping rule set for each of the data sources from the monitor control apparatus and to set the received data shaping rule in the data shaping section.