Reimagining Digital Governance With Artificial Intelligence And IoT
While digital transformation has remained a focus for industries all over the world for a long time now, the Covid-19 pandemic has brought it into the limelight again.
In fact, reimagining a tech-enabled future using technologies like artificial intelligence (AI) and Internet of Things ( IoT) devices will be beneficial and equally challenging for all businesses.
Because people are now depending upon tech companies for most aspects of their everyday life — from checking their fitness levels and procuring education to managing huge monetary funds and data — business leaders must realize that just one leakcould cause their companies to lose millions of dollars and see a huge dent in their integrity and reputation.
An increasing number of people are working remotely, and cloud collaboration has almost become the norm, so companies will have to get even more vigilant when it comes to securing crucial data spread across thousands of devices unrestricted by geographic locations.
As of late, IoT and AI have been used together in a new piece of jargon. Termed Artificial Intelligence of Things (AIoT), it promises a transformative impact on processes and people alike.
To put it simply, streaming data across connected devices (IoT) and using it for predictive analytics (AI) is interesting. In all honesty, IoT was always built around AI. The very purpose of streaming data through a network makes sense only if it is used for analysis. That’s exactly why the use of AI products in the IoT ecosystem is growing at a CAGR of 26%.
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Take a simple example of a fitness band that captures your pulse. It can send your health data in real time to a physician, who further uses inputs to make predictions and raise alerts. Or, when working from home, the data captured from multiple systems at your home desk is somewhere assuring others that you aren’t misusing the opportunity.
On a grander scale wherein IoT is spreading across industries, AI is undeniably useful in an ocean of unstructured data. The industry that was mostly considered limited to use case analysis is expected to reach a value of $124 billion by the end of 2021.
AI-Enabled IIoT: Digitizing The Most Complicated Processes
In the past year, there has been an increase in Industrial Internet of Things (IIoT) enabled systems driving predictive monitoring and maintenance of the assembly line. Such a setup makes comprehensive use of IoT and AI alike.
Here are a few ideas that can make this whole process secure and more organized. For instance, using remote access control systems, the machinery OEM can be connected with cloud apps that store and send data for real-time analytics. This allows anytime access to data insights on mobile devices.
Since IIoT systems work closely with ERP systems, they can stream machine performance data and map it against KPI standards in an interactive dashboard. Any mismatch, therefore, hints at repair work needed. Subsequently, automatic alerts can be sent to the service teams, whether in-house or outsourced to vendors. Needless to say, these insights are accessible on mobile.
For inventory management, IIoT systems can further enhance the transparency of the procurement workflows. With sensors, the fill-levels of containers can trigger real-time alerts. The fill level and time of the alert can be customized. Accordingly, inventory data can be closely analyzed in tandem with the location of raw materials in transit, thus improving the overall logistics ecosystem.
WFH, Cybersecurity And Public Clouds On The Rise
It would be unfair to discuss the pandemic's impact and not mention the millions of people working from home. By mid-May 2020, half of the workforce in 58% of global corporations was pushed indoors. Such an immediate shift to remote offices wherein an average of 11 devices per user were connected to the web, it is safe to believe that IoT adoption will only grow.
But homes are different. They do not assure uninterrupted bandwidths of the commercial spaces, nor do they provide complete protection against cyberattacks.
Ever since the lockdown, there’s been a 260% rise in cyberattacks all over the world. These include hacking and phishing attacks at the personal and mass levels. Citing concerns about the future of corporations in times when permanent WFH could be a reality for many, cybersecurity in the cloud has become an important layer in the digital transformation stack.
Amid all the chaos, cloud services emerged as the ultimate savior for global enterprises. The opportunity to drive business processes remotely from data centers has flocked millions of small- and medium-scale companies to host their data in the cloud. In fact, 2021 will see the public cloud market reach $4.1 billion in worth, which is the greatest ever growth for the business.
Subsequently, services such as Azure IoT Hub, which connect your devices in an IoT network to the cloud, will gain mass acceptance. This will enable business partners to develop fully customized and hybrid IoT apps in the cloud.
Getting Started With AIoT
Going forward, all IoT ecosystems should be incorporating AI in some form through predictive analytics, communication bots and more. Finding readily available workers skilled in AI and IoT domains is difficult. This applies especially to IoT. Its required stack of engineers (hardware, software and firmware), design interoperability experts (PCBs, software UIs), prototyping intelligence professionals, procurement experts and manufacturing and assembly line consultants makes it a convoluted space. Therefore, it is safe to outsource product development or engage in a partnership with a vendor skilled in these disciplines if necessary.
When choosing workers, look for those who possess the ability to perform critical cross-platform developments and manage multiple release cycles. At the same time, it is imperative to ensure security compliance across the line. I suggest hiring a cybersecurity expert to ensure protocol implementation across networks (device-cloud and cloud-cloud), data encryption, UI-to-wireless connectivity and more. Remember, this is important because AIoT systems are always at risk of an attack.