Dec 13, 2018
The Industrial Internet of Things (IIoT) is practiced through numerous industries like manufacturing, logistics, transportation, energy/utilities, oil and gas, aviation and other industrial sectors. It integrates machine learning and big data technologies to utilize the sensor data, automation technologies and machine to machine communication. The driving values behind IIoT are accurate and constant capturing and collaboration of real-time data with the process.
It is mainly aimed at combining machines, producing data, performing analytics and acquiring useful insights for enabling the user to take proactive actions in order to improve operations in industries. IoT fetches data from all the sources, sends it to the cloud and with the help of data analytics, it is visualized for obtaining useful insights.
Industrial Internet of Things focuses on the improvement of the operational competences, automation, efficiency, and maintenance. It unlocks abundant opportunities in automation, optimization, smart manufacturing, and asset monitoring.
In the current scenario, organizations are concentrating more on digital and cloud
Digitization of the business process and adoption of the cloud are two main criteria for which the organizations are transforming themselves. As per the present market demand for automation, these transformations have to leverage the power of the Internet of Things for better results.
The most common challenges that are faced during digital transformation projects
IIoT offers several opportunities that can be used to overcome the above-said challenges. By analyzing the huge amount of data produced by devices, the organizations can make better business decisions. At times the action can be taken on devices while in other cases, it can be regarding the robotic process automation. With the help of technologies and applications like artificial intelligence, machine learning, blockchain, and other supportive technologies, a connected, augmented, and smart ecosystem can be generated for business improvements.
IIoT has several prospects for organizations, they are:
The above-mentioned prospects can help upcoming programs for digital transformations in connecting the devices to the internet.
On the other hand, edge computing is also in focus these days due to its capability of supporting the scaling of the ecosystem. Some of the benefits of edge computing are:
Real-time data analysis – This is because the data is analyzed at the local device level.
Smaller operating costs – Since the data management expenses of local devices are less in comparison to clouds, the operating costs are less.
Less network traffic –The data is transmitted from local devices via a network to cloud and that result in reducing the network traffic.
Improved application performance – The applications that do not tolerate latency, can acquire lower latency levels on the edge and that improves their performance level.
These advantages give an idea that edge computing has the potential to become a mainstream technology sometime in the near future.
According to a 2015 survey of about 200 automation executives conducted by Morgan Stanley (an American multinational investment bank and financial services company) and Automation World magazine, the following chart shows the most important drivers among manufacturers for adopting IIoT.
The process of digitization in a business comes from specific vital modifications in the business operating model. And this is possible due to the digital disruption across industries. Digital has reached the business core and it is more than the addition of certain tools and technologies to the current infrastructure. Digitization is connecting devices and extracting enormous data to give useful insights for multiple purposes. Whether it is monitoring, evaluation, cost-saving on maintenance or expansion, it is giving a great ROI eventually. Thus, organizations must identify that digital is a facilitator and a catalyst that is changing the course of businesses on the whole.
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