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4 Impacts Of The Growth Of Edge Computing

The trending buzzword in the computing ecosystem is edge computing – a set of emerging technologies that can handle computations, applications and user services to devices on the “edge” of the cloud network, rather than at the core. But this concept is not entirely novel; before the conception of cloud computing, data processing was done at edge devices such as Windows desktops.  The expansion of the internet infrastructure has led to generation of large amounts of data, with the CISCO Global Cloud Index estimating that by 2019, there will be 500 ZB of data produced by people, machines and things. This, coupled with great advanced in big data processing, machine learning and other artificial intelligence innovations that have made data processing on devices feasible, has led to the development of edge computing as an organic innovation that enables faster, powerful and more efficient capability of cloud networks. In a world of rapidly evolving technological innovations that rely on low latencies between data generation and processing, a traditional cloud infrastructure dependent on central data processing is just too slow. Latency, the coveted quantity of the cloud, not only brings faster data processing and real time response for the user, but also faster service communication between devices, lower bandwidth through reduced cloud loads which greatly expands the network to encompass more devices. These benefits do not solely come to few network and computing based industries (think data-centers), but to the vast majority of industries that utilize cloud infrastructure. Here are some of the few industries that could greatly benefit from edge computing architecture.

1. Next Generation 5G. The next frontier for network internet speeds is breaching the 20 GBPs mark, requiring less than 1ms in latency on the Radio Access Network. A wide variety of edge innovations are helping this, including Mobile Edge Computing (MEC), supported by NFV-SDN (Network Functions Virtualization – Software Defined Networking) edge platforms that enhance flexibility in designing networks. Another such opportunity is micro-data centers. Kelly Quinn, research manager at IDC who studies edge computing, predicts that as telecom providers build 5G into their wireless networks they will increasingly add micro-data centers that are either integrated into or located adjacent to 5G towers. Business customers would be able to own or rent space in these micro-data centers to do edge computing, then have direct access to a gateway into the telecom provider’s broader network, which could connect to a public cloud provider. This sector, which is predicted to be a $6.3 billion market according to MarketsandMarkets has seen some new entrants such as DataBank, EdgeConnex and EdgeMicro which lease container sized data center space in buildings that may not have a main data center use.

2. Smart Cities. Smart cities are a collection of buildings, homes, hospitals, and transportation systems using technology to increase efficiency. Streaming such large amount of data into the cloud would be both extremely space-intensive and time-consuming. Therefore, it is necessary for these smart cities to have micro-data centers connected to the public cloud to analyze and store data locally, which could improve community services such as medical emergencies and traffic detection. One such example is the city of Palo Alto which is investing in a host of edge-friendly IoT projects, such as a parking space sensor program that will notify drivers about available parking spaces, thereby reducing traffic congestion and air pollution. Likewise, a new $3 million smart traffic signal project will enable traffic lights to work in sync with connected vehicles, so drivers aren’t forced to sit at empty intersections, waiting for the traffic light to turn green. Other smart city innovations include video surveillance where city cameras can be used to analyse large quantities of video data in a variety of situations such as vehicle license plate identification using image recognition processing done on site.

3. Autonomous Vehicles and Drones. Although automated vehicles are still in the developmental stages, industry giants like Google and Uber wish to make self-driving cars a consumer reality by 2020. However, self-driving cars create massive amounts of data including location and movement data, sensor information among others, much of which needs to be shared to neighboring cars. Edge computing ensures information is processed and transmitted to other vehicles quickly, improving service communication between these devices. Already, GE is using this in its Transportation Evolution Series Tier 4 locomotive. Due to the locomotive’s onboard edge computing system, the train is able to apply algorithms in real-time, enabling it to perform at or near its maximum potential. Similarly, autonomous drones send frequent location and status data to the cloud to coordinate movements, which can be optimized through the edge infrastructure. PwC estimates $45.2b value of prospective drone applications in global infrastructure development, with 60% of drone sales revenue coming from commercial drone sales, and a 34% increase in sales of personal and commercial drones in 2017 from 2016. One startup utilising edge computing in drone technology is Animusoft, which has developed a flexible and secure end-to-end unmanned systems management solution for all best-in-breed autonomous vehicles.

4. Retail. With the emergence of cloud computing, retail has never been easier for the online shopper and business. Edge computing applications on Point of Sale systems such as cloud offloading can enable much of the customer facing tasks and data (think of adding, dropping or computing the price of items on a shopping cart) to be affected and cached on edge devices, enhancing the user experience. Companies such as Max2 are creating distributed edge computing solutions to deliver a wide range of new or enhanced services at retail locations, in-commercial or residential buildings, or on campuses such as cost effective and improved connectivity to IoT devices in retail locations. But businesses too can achieve better targeted merchandise, sales, and promotions, for example facial recognition software that recognizes customers as they enter the store, smart fitting rooms to enable augmented reality (AR) mirrors (no need to try on tons of clothes to pick out your color), and infrared beacon technology to generate in-store traffic patterns in large stores. Since these tasks typically involve generating large sets of data and therefore powerful on-site servers, edge computing has the potential to leap this hurdle.

With the smart devices that have perpetrated the consumer market, from smart watches, smartphones, wearable sensors, and city wide sensors due to Intelligent Transport Systems, the potential for cloud based Internet of Things applications has exponentially grown. In the coming years, many analysts have predicted that IoT will grow, and, although estimates of the number of IoT devices vary, estimates put them in the range of 20 billion devices (Gartner) to 50 billion (McKinsey) by 2020. Edge computing in particular represents a sector for potential growth with BI Intelligence estimating that 5.3b devices connected to IoT edge solution in 2020 powered by an estimated 14-18% CAGR (estimated by Morgan Stanley) in IoT devices, and a potential $3.7T market for IoT devices in factory settings such as manufacturing and supply chains. Large industry players are taking notice such as Amazon with its Greengrass platform, Microsoft’s Azure, Akamai Technologies and Nippon Telegraph and Telephone Corporation which have pioneered greater investments in development of supporting software, security and computing platforms. However, the applications of edge computing are still vast, and several startups are rising to meet the needs of agriculture, energy, healthcare, smart city and autonomous vehicle technology using edge computing. The time to capture the benefits of edge computing has arrived, and we are excited to see its new developments.

If you liked “Four Impacts of Edge Computing” and want to read more content from the Bowery Capital Team, check out other relevant posts from the Bowery Capital Blog Special thanks to Yixuan Li and Emmanuel Murungi Mwebaze for their contributions and work on this topic.

Michael Brown
Michael Brown
Michael is a Founder & Managing Partner at Bowery Capital based in New York. Prior to Bowery Capital, Brown was a Co-Founder and General Partner at AOL Ventures. Before AOL Ventures, Brown worked for the investment arm of Richard Branson’s Virgin Group. He began his career at Morgan Stanley as an equity research analyst. Outside of his professional life, Brown serves on the Board of Directors of the National Forest Foundation and the Columbia College Alumni Association. He holds a B.A. from Columbia University.