Democratizing Intelligent Edge — Accelerate Series
By Amol Ajgaonkar, CTO of Intelligent Edge at Insight
The pace of intelligent edge innovation and disruption across industries has never been faster, and momentum will only increase from here. Insight’s Accelerate series explores angles of this phenomenon from a variety of technical experts who are seeing these innovations through, from technology development at the ground floor to enterprise-wide implementation.
Better data leads to better decision making for an organization, but when some of the most essential data for a business needs to be captured on the production line or at the check-out aisle, how can businesses leverage their infrastructure to not only capture this data but process it on-site? The answer is the Intelligent Edge — an on-premises system that collects, processes and acts upon data.
According to a 2020 Gartner report, by 2024, 60% of consumer-generated data will be created or developed outside of the data center or single-cloud environment. What does this look like in action? It means that machines on a production line or cameras in a retail store are able to not only generate data but process that data for insights “at the edge”, or away from a data center.
With an edge-processing unit, when decisions need to be made in real-time based on the data collected at these sites, there is no need to wait for data to be transferred to a centralized location. Valuable outputs are given in the moment to increase efficiency and lower costs across industries.
For example, in manufacturing, computer vision can be applied with edge-processing and custom vision models to detect defects during production to shift the burden away from employees who may otherwise have to spend time painstakingly monitoring for defects themselves. Human-error is not only reduced with this method, but employees are actually freed up to address more important tasks that truly require their expertise.
When Newcrest Mining was struggling to maintain efficiency of ore production, which required precise human monitoring of underground ore bins in challenging conditions, Newcrest was able to implement an intelligent-edge solution that used real-time data to predict bin levels with 85% accuracy. The project has saved millions of dollars in operational efficiency and allowed employees to re-allocate precious time and resources.
How does the architecture work?
The edge-gateway captures data and processes on-site and is able to send messages or commands to other devices in the system. Precision increases as data can be garnered from an increased number of sensor sites and processed remotely, away from the data center. This amassed data gathered allows for historical patterns to be tracked to allow innovative machine learning that creates predictive analytics, an output that enables an organization to be ahead of the curve.
How does a business get started?
1) Prioritize use cases
Identify your organization’s opportunities for highest ROI when implementing an intelligent edge solution — where would these tools create the most impact in efficiency, safety, customer service, or cost reduction?
2) Select a high-priority, high-impact use case to implement on
Once priorities are arranged, begin implementation with the use case that will create the most impact for your business.
3) Develop the next highest-priority use case and repeat
Begin the process of scaling out implementation by continuing to build upon your organization’s infrastructure with edge processing.
4) Maintain a focus on building a foundational framework that provides consistency across use cases and the organization on the whole
Throughout the process of implementing by use case, keep in mind the factors that will create a strong foundation for successful scaling business-wide. Considerations to keep in mind include security and post-production processes. Have a plan in place for managing deployment of intelligent edge by educating team members.
The future of competitive advantage lies at the edge, and this is why democratizing information on intelligent edge solutions and where to get started for businesses is essential. With accelerated adoption constantly moving the needle, we’re seeing organizations feeling increased urgency to begin planning for implementation today in order to have the intelligent-edge infrastructure necessary to remain competitive tomorrow.
You can watch Amol’s Accelerate expert speaker series presentation, Democratize Edge, here.
Amol Ajgaonkar is the CTO of Intelligent Edge at Insight. Amol draws upon more than 17 years of experience to drive thought leadership and strategy for outcomes-focused edge solutions. He’s a hands-on technical leader with a passion for building IP and designing secure, easy-to-manage systems that run at the edge and scale through the cloud. He specializes in helping organizations architect and operationalize AI models at the edge in a sustainable way.
