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Big Data Quality and Integrity, Fundamental Elements of the Industrial Internet of Things

In recent years, there has been an ever-increasing interest in developing solutions for Industrial Internet of Things (IIoT) applications. The interest spans many industries, with a large amount of the effort focused on predictive maintenance solutions. Predictive maintenance can be described as “extracting valuable business information from big data.” This is accomplished by applying complex analyses to vast amounts of data acquired from many thousands of sensors.

However, before proceeding with the analysis, the vast amounts of data should be collected safely and completely and translated into valuable protocols for OT and IT engineers.

Effortless Data Communication: I/O to IT/OT Multiple-Protocol Data Concentrator

The first step is to collect the comprehensive industrial device data from the field site for live data monitoring and big data analysis. The ioLogik 2500 Series can be used to collect the data from legacy meters and other industrial devices through Modbus RTU and Modbus/TCP devices, as well as field site sensors through various I/O interfaces. ioLogik 2500 Series smart remote I/O products, which support six different protocols, are ideal for applications that use a combination of IT and OT protocols. The ioLogik 2500 allows you to use the protocols that are most suitable for your system, without needing to install an extra protocol gateway to connect to your IIoT applications.

  • Modbus
  • EtherNet/IP
  • Active OPC tags (DI changes are actively pushed to MX-AOPC)
  • SNMP, SNMP traps
  • RESTful APIs
  • MXIO Library (C++)

Ensure Data Completeness: Supplement Data Automatically, On Demand, or on a Schedule

Everyone has heard the old adage, “garbage in, garbage out,” but the reality is that ensuring the quality and integrity of big data is not easy. A cause for concern is the inevitable unexpected connection interruptions that plague any network, and which could result in data loss and expensive shutdowns of important business processes. Moxa’s smart data acquisition method helps shrink the amount of data that needs to be transmitted and ensure data completeness. After each network connection, MX-AOPC UA Logger will compare historical data stored on the SD cards located in individual Moxa ioLogik 2500 devices with the real-time data it has already stored locally, and then supplements any missing data by requesting that the devices retransmit any lost data. Additionally, users can trigger data supplements at any time, on a specific date, or every day at a specified time to ensure data completeness. This kind of smart data acquisition enhances the quality and integrity of big data, resulting in more accurate analyses.

Active Data Acquisition and Data Completeness

Active Data Acquisition

In the IIoT era, legacy polling methods do not mix well with big data, particularly since by its very nature, polling results in the collection of tons of worthless data from thousands of sensors, leading to high data storage costs and time consuming data analytics. When your sensors spit out data at a frequency much smaller than the polling interval, such as is the case when monitoring a machine’s ON/OFF status, “update by exception” can reduce the amount of data storage and increase the efficiency of data analytics. Moxa smart I/O supports Moxa’s patented Active Tag function, which actively updates digital or analog sensor data to Moxa’s MX-AOPC UA Server by exception or per configured percentage of changes. Not only will you save network bandwidth, you will also reduce the amount of data storage required.

Data Completeness by Auto Mode, by on Demand, and by on Schedule

Most SCADA systems support saving data to a database in real time. However, data loss will occur when the network connecting the SCADA software with the remote I/O devices goes offline, or when the SCADA software crashes. A common solution to this problem is to back up data in local storage devices located near the remote I/O devices.

Moxa’s ioLogik 2500 series, MX-AOPC UA Server, and MX-AOPC UA Logger together form a turnkey solution for real-time data acquisition, data buffering in local storage devices, and ensure data completeness (data supplement by auto mode, by on demand, or by on schedule) after network failures. MX-AOPC UA Logger is used to import data from MX-AOPC UA Server into a database in real time. After the network fails and then recovers, the logger automatically retrieves data logs, with timestamp matching the duration of the disconnection, from the data buffers of specific ioLogik 2500 devices, and then pushes the supplementary data into the database.