The ability to process data at the network edge and capture insights from that data on a real-time basis without any latency issues is essentially why edge computing is gaining prominence across industry verticals. Primarily, an extension to cloud computing, edge computing helps businesses delve deep into data for analysis and make informed decisions along with solving a range of issues related to network latency, governance, and security.

Applications of edge computing is widespread given the ability to completely revolutionize the way businesses deal with data. So, let’s find out what are the three most crucial real-world application of edge computing –

Smart Grid

Smart Grid is a new-age concept of setting up a two-way communication between the distribution infrastructure and consumers. Grid edge computing solutions help utilities monitor and analyse the tons of data generated by renewable power generating resources in real time. The edge computing solution, smart meters in this case, helps utilities to determine the amount of energy available and required, allowing the demand response to become more efficient and avoid peaks along with reducing costs.

Traffic Management

Traffic management within the smart transportation systems is another example of how edge computing solutions are applied effectively. With the increased implementation of Internet Of Things (IoT) devices and sensors, the amount of data generated that require processing has grown manifold. Edge computing solutions typically analyse and process data on the traffic sensors itself and filter out unnecessary traffic data to transmit only relevant information across network.

Check out the Research on Global Markets report featured in this article:

Global Edge Computing Market (2018 – 2023)
May 2019 | 140 Pages | SKU: 201843

Autonomous Vehicles

Despite the fact that autonomous vehicles are yet to officially hit the road, there’s no denying that it is arguably the most cutting-edge deployment of edge computing technologies to date. Without edge computing, this mode of transport would be near impossible. Distributed edge computing solutions facilitate hosting of artificial intelligence (AI) applications at the edge of the network in autonomous to reduce latency levels between data being generated and then used to run a vehicle.

The growing popularity of edge computing solutions among businesses is also reflecting in the long-term outlook for the global edge computing market. Research firm Netscribes expects the market to witness considerable growth in the foreseeable future.