Data Acquisition
Top 5 Control Engineering articles December 2-8
Articles about the Engineers' Choice finalists, data acquisition, cut-to-length cable, IT/OT convergence, and industrial virtualization were Control Engineering’s five most clicked articles from December 2-8. Miss something? You can catch up here.
Eight data acquisition best practices
To discover which real-time data adds value to improve operational efficiencies and increase competitive edge in the marketplace, first understand data acquisition systems and consider the eight essential best practices for data acquisition success
Making things work as part of the IIoT
Sensors are on the front line of the data gathering process, which is vital for the Industrial Internet of Things (IIoT).
Perfecting power distribution data quality
Data produced by power distribution networks is critical, but so is perfecting data quality and governance.
Finding common ground between industrial automation and mobile technology
Mobile technologies are challenging traditional data handling practices as they move into the industrial arena.
Improve decisions by optimizing data from mobile devices
Good mobile software promotes efficiency by delivering data on intuitive screens that empower users to integrate information and saves trips back to the control room or to the site.
The data historian’s history told
Momentum around time-series data storage suggests a new chapter for a legacy offering.
Three data types companies need to prioritize
Not all data is equal and some require greater attention and priority than others. Industrial companies managing networks need to focus on information-based, mission critical and real-time data.
Machine-learning algorithms used to make agriculture taste better
MIT researchers have developed a method using machine learning to reveal optimal growing conditions to maximize taste and other features.
Researchers develop architecture to reduce data center energy and space constraints
MIT researchers have developer a flash-storage system designed to cut the energy and physical space required to store and manage data in data centers by half.