Data Acquisition

Courtesy: CFE Media
IIoT, Industrie 4.0 July 30, 2019

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).

By Suzanne Gill
Figure 2: Smart devices are enablers that generate substantial volumes of data from utilities, which can put pressure on infrastructure. Courtesy: Cyient
Energy, Power June 28, 2019

Perfecting power distribution data quality

Data produced by power distribution networks is critical, but so is perfecting data quality and governance.

By Sunil Kotagiri
Older architectures for mobile access present problems, but newer implementations provide greatly simplified solutions. Courtesy: Opto 22
Mobility June 13, 2019

Finding common ground between industrial automation and mobile technology

Mobile technologies are challenging traditional data handling practices as they move into the industrial arena.

By Benson Hougland
Figure 2: Users can claim ownership of process notifications so that others know those alarms are being investigated. Courtesy: Emerson
Data Acquisition, DAQ June 3, 2019

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.

By Danny Strinden and Mariana Dionisio
Figure 2: Time-series databases are experiencing explosive growth because they efficiently can store and provide access to large volumes of data. Courtesy:
Data Acquisition, DAQ April 27, 2019

The data historian’s history told

Momentum around time-series data storage suggests a new chapter for a legacy offering.

By Michael Risse
Courtesy: CFE Media
Data Acquisition, DAQ April 13, 2019

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.

By Jonathan Simpson
Researchers in MIT’s Open Agriculture Initiative grow basil under controlled environmental conditions to study how taste and other features are affected. Courtesy: Melanie Gonick, MIT
AI and Machine Learning April 10, 2019

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.

By Anne Trafton
MIT researchers’ modified flash storage drives hold promise to cut in half the energy and physical space required to store and manage user data in power-hungry data centers. Courtesy: Chris Vavra, CFE Media
Data Centers April 3, 2019

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.

By Rob Matheson
A robotic car controlled by an ultra-low power hybrid chip is placed into an arena to demonstrate its ability to learn and collaborate with another robot. Courtesy: Allison Carter, Georgia Tech
Robotics March 25, 2019

Top 5 Control Engineering articles March 18-24

Articles about low-power hybrid chips for robots, gaining the edge in automation, connecting quality and process data, manufacturing and process facility trends, and the Engineers' Choice Awards were Control Engineering’s five most clicked articles from March 18-24. Miss something? You can catch up here.

By Chris Vavra
Figure 1: Product quality is impacted and controlled in various stages before the customer uses it. Courtesy: TrendMiner
Data Acquisition, DAQ March 12, 2019

Connecting quality data to process data

Using advanced analytics can help assure product quality and overall operational efficiencies. See case study example.

By Edwin van Dijk