Innovation is flourishing on the intelligent edge. Organizations are conceiving products and services not possible until recently.
Introducing capabilities at the edge means more than simply shifting resources to smaller devices networked across the Internet of Things. It means discovering new paths to innovation, and even new business concepts.
Having processing power at endpoints enhances the delivery of real-time insights, continuous experimentation, on-the-spot analytics, and services.
The ability to deploy data analytics both functionally and strategically drives innovation, freeing up businesses and employees to design and create new types of products and services. “Innovation from analytics is surging,” note Sam Ransbotham and David Kiron in a report published in MIT Sloan Management Review.
Looking at the results of a survey of 2,600 executives, they found that “Organizations with strong analytics capabilities use those abilities to innovate not only existing operations but also new processes, products, services, and entire business models.” Further, the report states that “ … the ability to innovate with analytics is driving the resurgence of strategic benefits from analytics across industries.”
Intelligent Edge Computing means empowerment for organizations not attainable through the existing hub-and-spoke model that defines the IoT. Whether in remote, out-of-network locations or in environments requiring crucial, microsecond responsiveness, intelligent edge provides the ability to build and package services and capabilities with data as it is created. Intelligent edge makes advanced initiatives such as artificial intelligence a compelling working reality for all types and sizes of organizations.
“Smart machines create an opportunity for innovative thinking. Smart machines that draw inferences from data on their own and learn by using algorithms to discern patterns in masses of data are no longer confined to research labs and limited applications such as speech recognition,” Ransbotham and Kiron state in the MIT Sloan report. “The most analytically mature companies use artificial intelligence to augment human skills and to take on time-consuming tasks, freeing managers to spend more time on strategic issues.”
Consider some of the compelling products and services now possible through the intelligent edge:
Overcoming constrained network resources. Intelligent edge computing provides enterprise-class insights without the need to go through an enterprise. A construction company with projects in multiple locations around a region or around the globe may find its network resources limited, or maybe even unavailable when needed, such as in remote mountainous or forested sites. With intelligent edge analytics, data regarding equipment locations or condition, for example, is managed onsite, and perhaps even repaired before projects are disrupted. Think about trucks and cranes fitted with sensors that can track their progress and performance as they move about a worksite.
Providing highly personalized transportation. Edge Computing plays a role in enabling highly functioning and responsive autonomous or semi-autonomous vehicles. A bus, for example, can interact with riders to get them to their destinations in the most efficient manner possible. In addition, people with disabilities may benefit from visual or audio messaging of their destinations en route. On a small-scale level, edge processing can power autonomous luggage, capable of following passengers as they navigate airports and train stations.
Addressing security and privacy concerns. On-the-spot analytics helps alleviate concerns about sensitive data being sent off-location. For example, there are privacy issues (and, as part of Europe’s GDPR rules) associated with the distribution of people’s images. By processing and analyzing images locally, and only distributing the resulting analysis, organizations can accomplish initiatives while still maintaining privacy and security. For example, a hotel chain that sought to measure customer sentiment at checkout desks via video imaging was able to generate analysis through local devices without violating customers’ privacy.
Manage device performance within constrained or inaccessible environments. Even in places with a strong network or wireless access, many devices or systems still need to be able to respond instantly – often within microseconds – to changes or events. This requirement is giving rise to products that can deliver responsiveness on the spot. For example, medical devices regulating body functions need to respond instantaneously to changes in patients’ conditions or to provide a diagnosis. Or an autonomous vehicle needs to be responsive to road conditions or be able to react to potential collisions. The rapid response times enabled through internal processing within edge devices or systems provides for these requirements.
Enable energy sourcing based on changing local conditions. Alternative sources of electrical power – from wind to solar – have become a viable industry, rivaling traditional coal-fired utility plants. However, many homes and businesses cannot rely entirely on weather-dependent sources and need the capability to efficiently measure supplies versus consumption and adjust accordingly. With analytics and AI running within power configurations, sensors can switch between solar and conventional power sources as temperature and available power supplies dictate.
Intelligent Edge Computing means more than simply redistributing capabilities to endpoints. It opens up innovation and enables businesses to leverage AI and advanced analytics to conduct new ways of doing business.
