In the age of digital transformation, we’ve become accustomed to living our lives immersed in technology. We maintain relationships that follow us seamlessly from the physical world to online platforms and social media, whether we are communicating with old friends or new retail brands. Consider how many times a retailer “follows” you across multiple websites with merchandise recommendations based on a recent purchase or online search.Content Continues Below
Of course, omnichannel scenarios are largely limited to a specific experience or company today. When it comes to coordinating actions or decisions across various vertical markets and use cases, humans are still very much involved. But given how far technology has come in a relatively short time, one might wonder if — or, perhaps, when — computing will become truly ambient and span these virtual siloes.
Consider, for example, the task of arranging a vacation, including hotel and car rental, flight reservations, pet boarding and scheduling time off work. Could a software system be enabled to drive various workflows to plan the entire vacation for me based on my specified interests and personal profile? Yes, this can happen … with the right help.
On the road to tomorrow
Many industries are already seeing how pervasive connectivity can be used to benefit business processes through the industrial IoT, which is growing at an annual rate of nearly 25%. The ability to predict equipment failure based on intelligent sensors and algorithms enables significant improvements in inventory management, cost control and resource availability, not to mention the ability to increase safety by preventing failures. The integration of data, analysis, intelligence, process integration and reporting is key to implementing IoT systems. Yet, human intervention and decisions are still required today. Could these diverse systems intelligently communicate without human intervention?
If we envision the next step in IIoT evolution, we can imagine a scenario such as the intersection of automotive IoT and smart city functionality, with a tremendous amount of data coming from smart streets and parking lots, drivers, as well as the vehicles themselves. Car manufacturers could learn from operational data and driving patterns, while municipalities could benefit from information related to traffic patterns, effects of emissions, pedestrian and driver safety, and emergency response situations.
At Aricent, we are actively engaged in a number of vertical markets to enable IoT systems for specific use cases. We see many use cases that are driving IoT development and 5G adoption, such as autonomous driving, smart grids, intelligent retail or healthcare. However, we have yet to see the industry working together to merge systems in an intelligent fashion in order to provide real value across vertical segments.
The key to achieving this vision will be readily available access to relevant data, and a method of translating this information to be understood across various systems. The ability to provide layered data architectures that are rapidly accessible across intelligent systems is paramount; and to that end, we are focused on developing artificial intelligence and machine learning technologies with associated services for vertically specific learning.
Are we there yet?
Essentially, we have the technology to do this today. Emerging 5G networks and other networking technology will enable these systems to scale across many millions of devices that will exist in an operational scenario. Business analysts can translate the current process environment into the next-generation automated workflow. However, enterprises first need to understand the value of integrating vertical systems in order to drive implementation of these scenarios and realize the vision of ambient computing.
Ambient computing allows enterprises to simultaneously use many sources of data, both internally and externally sourced, to improve customer experience, competitiveness, market relevance and product excellence. For example, a hotel chain may be interested in usage variables in order to maximize its appeal to particular consumer groups or business travelers. That data might be derived from rental information, events, sports activities and other consumer data associated with a specific geography or demographic. Collecting and analyzing broadly sourced information allows for more agile and responsive business processes, leading to greater returns.
Digital design plays an important role in all of this. Creating an experience, workflow, usage and integration patterns and, most importantly, a conceptual journey of where the enterprise needs to go in the next five years is central to design-focused engineering. Creating top-down plans that include opportunity discovery and conceptual design can drive the required technology, data and workflows needed for ambient computing systems.
Full speed ahead
As we move toward these more complex and data-rich services, AI and machine learning technologies will enable greater autonomy to identify usage patterns and variables, either as the result of direct information or inferred decisions. Machine learning intelligence can then directly update algorithms and data, thereby improving customer experiences and product offerings. In this way, we create a continuous improvement process to search for relevant information and trends across the entire ecosystem, while minimizing human interaction.
With a better understanding of how to integrate ambient computing into business processes and the back office, enterprises can enable access to real-time and relevant data across industries and vertical markets. And with a little help from digital design engineering, a world of business opportunities will be realized in the very near future.
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