New Spin-Out Mirlo Systems is Driving the Edge Computing Revolution
ECE Professor Edmund Yeh’s spin-out company Mirlo Systems is a cutting-edge video delivery service that uses edge computing to improve speed and quality.
Picture this: an advanced tech manufacturing plant inspecting the factory floor to ensure flawless operations, a ‘grab and go’ convenience store at the airport offering seamless touchless transactions and no wait times, and an online gaming company rendering and streaming real-time graphics that captivate users. What ties these diverse scenarios together?
These scenarios are all enabled by cutting-edge technologies such as computer vision, video analytics, machine learning, and, most importantly – edge computing.
Edge computing is a groundbreaking computing and networking paradigm that brings computation, machine learning, and data storage capabilities closer to the network edge, where data is generated. This paradigm increases bandwidth and reduces latency while enhancing autonomy and security for a broad range of commercial applications.
In the computing and networking industries, where speed, volume, security, and privacy are paramount, Mirlo Systems emerges as a beacon of innovation. This Northeastern spin-out company is reshaping the landscape with a revolutionary data-centric platform that places data storage, computation, and learning at just the right place to deliver the performance needed for your application.
A new type of edge computing platform
Mirlo Systems leverages edge computing to process various types of data close to its origin, leading to unprecedented processing speed and volume gains.
The revolutionary edge-computing platform is the brainchild of Professor Edmund Yeh and his team, who have seamlessly integrated efficient, high-performance edge computing with advanced data caching and forwarding for various high-impact applications.
Research relevant to Mirlo Systems began nearly a decade ago, in 2014. Over the last ten years, the team has built its in-depth knowledge and expertise concerning the architecture, theory, algorithms, software, interfaces, and implementation underlying the commercialization effort to bring its platform to market.
The team is currently working to validate the platform by innovatively addressing several challenges to enable a more refined and powerful edge computing solution.
“I have always been fascinated by how mathematics and science can be utilized to improve people’s lives,” says Yeh. “Electrical and computer engineering provides a great pathway for achieving this, and we hope that our technology will have a strong positive impact on many.”
Commercialization plans for Mirlo Systems
Mirlo Systems is poised to become one of the leading young companies in the edge computing space.
The start-up company plans to work with customers in high-growth application areas. They envision many important applications for their platform and strive to make a deeply positive technological and societal impact on industries such as manufacturing, retail, and gaming.
Awards and funding
Northeastern CRI’s Spark Fund Award partly funds this technology, as the team was selected as one of the Spring 2023 Spark Fund awardees. This award provides financial support for their PhD students and resources such as external consultants in user experience interfaces.
In addition to funding, Northeastern CRI has also provided important support in connecting Mirlo with an entrepreneur-in-residence and other consultants specializing in developing pitch decks and website design.
The company has five issued patents in its portfolio.
Key takeaways: revolutionizing data storage, movement, and analysis with edge computing
Mirlo Systems is positioned to elevate edge computing technology to new heights. Its revolutionary data-centric platform is underpinned by a decade of groundbreaking research conducted at Northeastern.
Mirlo’s patented platform, which seamlessly integrates computation placement, data delivery, and machine learning, promises to revolutionize how we analyze and compute with massive data in real-time, and has the potential to strongly impact a wide range of use cases.
Written by Elizabeth Creason, Center for Research Innovation