The edge of IoT is where the action is as it includes a wide array of sensors, actuators and devices that keep communicating with the network in real time. Edge computing represents a shift in computing where intelligence from the Cloud is pushed to the Edge, localizing decision-making and analysis. Since devices are at the Edge, they will not be affected by network latency and the reduced traffic will enable quicker response times by selectively relaying the appropriate data to the cloud. The Edge has more features and performs more functions than any other layer in the network topology.
Across industries, the application of advanced analytics, machine learning, and artificial intelligence is disrupting traditional approaches to manufacturing. Manufacturers can become more competitive by gaining predictive insights into production by using machine learning. By using advanced data analytics and AI, manufacturers can combine inputs from many sensors and comb through the data to find out any equipment failure and other potential problems. Over time, the technology will be able to enhance its ability to detect failures.
Industrial Internet of Things (IIoT) is a transformative manufacturing strategy that helps to improve quality, safety, productivity in an industry. Read more
Simulator-based training is an effective way of training factory staff. IIoT-enabled technologies such as gaming, augmented/virtual reality, 3D immersive and wearable devices can improve learning and help develop skills by replicating real-life plant scenarios. The applications include testing and validation of software, aiding in system migrations etc. This technology can help manufacturers understand how employees will react in worst-case scenarios and thus plan emergency procedures. Rockwell Automation’s industrial chatbots, Amazon’s Alexa and Microsoft’s mixed-reality Hololens platform are all examples of consumer technologies being used in the industrial realm.
As IIoT grows, manufacturers will have to spend a lot of time testing new systems on the floor. While connected networks will help, creating digital twins of the products/services and testing them thoroughly in a virtual environment before going live also will help manufacturers avoid downtime problems and save them from committing actual resources. Besides, it will help them in fixing issues on the factory floor before going live and allow for continuous design and manufacturing improvements. The real-time data from integrated sensors can be used for analytic tasks like condition monitoring, failure diagnostics, prescriptive and predictive analytics. I think I would like a twin! It would be so cool to experiment on him.
Nearly 96% of security professionals in organizations are expecting increasing cyber-attacks on IIoT infrastructure, according to a survey by Tripwire. While an overwhelming majority felt the need for enhancing the existing infrastructure, more than said they do not feel adequately prepared for such attacks. The recent global ransomware outbreak through the WannaCry virus, which wreaked havoc at dozens of NHS trusts and hit thousands of computers in 150 countries, underscores the need for strengthening cyber security across industries as the number of connected devices increase rapidly. Blob wonder why the authorities called the virus “WannaCry”. Are they asking a question or suggesting the outcome?
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