Four big challenges for the industrial Internet of Things
A quest to become a smarter world where all systems with local processing and sensors are connected to share information is gaining momentum. Connecting these systems with each and other and users helps businesses make informed decisions.
This overarching idea has got many labels, but the most well-known is the Internet of Things (IoT). The big sphere of IoT involves smart homes, mobile fitness devices, and connected toys and its subset the Industrial Internet of Things (IIoT) includes smart agriculture, smart cities, smart factories, and the smart (utility) grid, says Danish Wadhwa, a strategic thinker and an IT Pro.
The Industrial Internet of Things (IIoT) refers to an interconnected network of systems, platforms, physical objects, and applications that have been programmed to interact and share intelligence with each other and external environment. The significant adoption of the IIoT is being triggered by the higher availability of sensors, processors that facilitate capture of and access to data in real time.
Moreover, Industry 4.0 has empowered the industrial users to use the data and analytics for predictive analysis with minimal machine downtime, higher storage and remote asset tracking. With so much hype around, IIoT also has its own set of challenges that enterprises need to address to reap all its benefits in the future.
Lack of standards
The paucity of standards and documented practices put a great impact on the potential of IoT devices. APNIC’s Geoff Huston states that a lack of standards can result in bad behaviour by IoT devices.
In the absence of standards, developers might design products that run in disruptive ways. When designing and configuration is not right, such devices might lead to bad results for networking resources. This is likely to happen because of cost constraints that put down many things and lead to the need for a product to release faster than competitors.
Additionally, problems related to managing and configuring IoT devices generate the need for innovative design. Thanks to this need, the fine-tuning of configuration tools, interfaces, and methods will be critical in the future. These tools help in data manipulation, data communication, data visualisation, and data analysis which are inclined to AI. Therefore, most developers, to work according to standards, will work best if they take an online AI course to stay abreast of the internet of things.
Data protection from corporations
Apart from hackers, organisations that develop and distribute interconnected devices could also get hands on your data using these devices. This is particularly dangerous during money transfers.
Most organisations like BP are giving out Fitbits to their employees to analyse their health conditions so they can get minimum health insurance premiums. Moreover, even if organisations stop monitoring workers’ health on a regular basis, there is the question of how corporations can use the data they have collected so far.
RadioShack is one such example. This corporation has tried to send or even sell collected data to other organisations. This puts a question mark over our individual privacy rights.
Today, a consumer’s safest bet is to go through every clause prior to buying a device. Also, consider the device’s corporation policies to keep data secure. It may result in refusing to use IoT devices, but it is essential to avoid security issues.
Supply chain integrity
Rather than functionality, manufacturers would need to address many other issues in the future. Reliability and cost also play a major role as early adopters compete to make their IIoT transition successful. As integrated systems significantly move to enterprises, manufacturers would be responsible to maintain their supply chains integrity throughout manufacturing.
Patrick Miller, a trusted advisor for the protection of critical infrastructures says this challenge is not lost on him. He added, “During the use of IIoT elements within a critical infrastructure, supply chain concerns will be associated with public opinions and politics.
To overcome this resistance, organisations need to plug processes so as to enhance transparency and standardisation during the manufacturing process. This can put stress on the development of devices on the basis of an agreed-upon open standard that can be gauged in a bid to ensure that the required hardware and software is involved.”
Today, most manufacturers use machine learning to make the most of BI. To do this, they focus on collecting data from internal repositories to perform predictive analytics. There are different types of analytical techniques like predictive modeling, process optimisation, machine learning, simulation, and many more that help you to understand these tools.
In addition to privacy, many legal and regulatory questions revolve around the Internet of Things. This really needs to be addressed the right way. Legal issues related to the Internet of Things devices are not restricted to civil rights violation as law-enforcement surveillance plays a vital role.
Cross-border data flow, the legal liability when it comes to unintended use, privacy failures and security attacks are many other issues that need thoughtful consideration. Moreover, technology is rising faster than regulatory policies, and the service providers charged with IoT guidelines cannot keep pace.
The Internet of Things is a growing technology with major advancements in market development. Similar to other waves of technological revolution, it is influenced by fragmentation, innovation, confusion, emerging standards, and competitive jostling. Beginners are shaking up the current status as settled technology-driven organisations react and adjust.
The IoT is likely to embrace the cloud, big data, smartphones and social networks to offer advanced sensors and devices. When this happens it will offer robust applications and use cases that will reshape existing business models and revenue sources. Moreover, it might threaten many industries, markets, and products while impacting disrupting trends like the IoT has the power to fasten the “sharing economy.”
By unlocking different ways to organise smaller things, it will enhance the sharing of affordable items beyond houses and cars. Many implications make the IoT the logical extension of the “long tail” technique. This takes devices to granular levels and results in the development of new uses, applications, services and business models that otherwise were not viable economically.
As the IoT grows, a part of the whole value will move from devices to comprehensive solutions and services. This unlocks opportunities for value creation, reshape business models and unlock revenue streams for leaders.
The author of this blog is Danish Wadhwa, a strategic thinker and an IT Pro
About the author:
Danish Wadhwa is a strategic thinker and an IT Pro. With more than six years of experience in the digital marketing industry, he is more than a results-driven individual. He is well-versed in providing high-end technical support, optimising sales and automating tools to stimulate productivity for businesses.