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info@campbellsci.com.cn
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Kangbao Zhixin Measurement Technology (Beijing) Co., Ltd
Intelligent big data processing and evaluation software
NegotiableUpdate on 01/30
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Overview
The SwisensSoftware intelligent big data processing and evaluation software component combines all our experience in handling big data, artificial intelligence, and real-time measurement system operations. Swisens has always adhered to the concept of open data access, using open source technology, and providing customers with the greatest freedom.
Product Details
1 SwisensDataExplorerIntelligent big data processing and evaluation software
SwisensDataExplorerIntelligent big data processing and evaluation softwareIt is a browser based software with tools for checking measurement results and monitoring hardware components in the SwisensEcosystem. Both individual measurement systems and network systems can be used.
1. Characteristics
• Check the time series of measurement data and identification results
• Histogram evaluation based on particle size
• Monitor operating parameters and retrieve system status
Analyze current and historical time series, particle concentrations, and data
2. Instant access
You can use a browser to obtain and view measured particulate matter and analysis data within seconds.
3. Data analysis
Integrated analysis tools allow for fast and efficient data analysis, supporting both local and remote access.
4. Artificial Intelligence Interface
Processing datasets and machine learning models - integrated on one platform.
5. Open source
According to GLP standards, we can independently optimize and expand our application areas.
II SwisensDataAnalyzer
SwisensDataAnalyzerIt is a toolkit that enables effective in-depth analysis of large amounts of data in measurement systems. Due to the ability to measure aerosol particles in real-time, we can enter a big data environment.
For advanced data analysis or data visualization,SwisensDataAnalyzerOn the basis of Docker Containers, Jupyter Notebook Containers, and Python Modules, a clear and independent working environment is provided.
1. Data reprocessing
By relying on Docker Containers, data can be analyzed in a platform independent and reanalyzed manner.
2. Flexible data access
Data can be obtained from personal computers, external databases, or directly from SwisensPoleno.
3. Open source
According to GLP standards, we can independently optimize and expand our application areas.
4. SwisenDataExplorer integration
Used for quickly importing and exporting data from networks or measurement systems.
