IoT and Edge Computing

Extracting Insights in Real-Time

Up to $11.1T/Year

The IoT market will have a total potential economic impact of $3.9 trillion to $11.1 trillion a year by 2025¹

507.5ZB by 2020

By 2020, more than five million smart sensors and other IoT devices will be in use around the world, and will generate at least 507.5 zettabytes of data²

47B by 2021

It is estimated that there will be 47 billion connected devices by 2021³

What makes real-time analytics at the edge become possible or even preferred, not just now but in years to come, is the possibility of conducting artificial intelligence and machine learning (ML). AI and ML are becoming increasingly more complex, versatile and sophisticated to enable real-time analysis at the edge, on the hub and, ultimately, in the cloud to get more value from all of the IoT data collected. Data can be sent to the cloud, where machine learning and AI can be trained to watch for patterns and gain insights from large data sets over time.

SOURCE: UNTAPPED DATA – GETTING MORE FROM IOT DATA AT THE EDGE AND IN THE CLOUD BY CHRISTOPHER BERGEY, WESTERN DIGITAL (WESTERN DIGITAL BLOG, 5/6/18)

HOW TO EXTRACT VALUE FROM EDGE DATA

IoT is Driving Real-Time Analysis at the Network’s Edge

For many IoT applications, it has become critical for data to be screened and analyzed where it is generated - from sensors in a car, surveillance cameras, drones, personal devices, robots, gateways, etc. – and even transformed there. The ability to deliver real-time analytics at the network’s edge can improve operational efficiencies, provide safer driving, create more secure environments, foresee upcoming maintenance, identify customer buying behaviors, and enable a world of opportunities.

Network latency is a challenge. It takes too long to store and forward data, whose value exists now. Edge storage manages data captures and provides the compute capabilities that aggregate and analyze that data in real time, to deliver immediate and actionable insights at the device level.

THE VALUE OF EDGE ANALYSIS

Edge Analysis Delivers Real-Time Value

Artificial intelligence (AI), machine learning (ML), image, voice and gesture recognition, and other technologies deployed onto edge devices interact with captured data in real time to deliver valuable insights. The full digestion of analytics can be transferred to the cloud where it can be used to further train AI models for machine learning or archived for future use. The ability to access this information in real time, ultimately, creates a more efficient and effective business, operation, or environment, enabling greater opportunities for monetization of the IoT application.

Enabling the Power and Possibilities of Data at the Edge

Western Digital Offers an Extensive Portfolio of Products from Devices to Systems and Platforms Designed to Enable the Power and Possibilities of Data Driven by IoT and Edge Computing

IOT DATA LAKE

Effectively Managing Internet of Things Data

One of the biggest challenges that enterprises encounter when exploring how to improve their businesses using Internet of Things (IoT) data is the sheer volume created by sensors. This staggering amount of data impedes the ability to efficiently access, manipulate, and gain insights from the vast and diverse world of data collected.

Cloud object systems were designed to handle the enormous volume of IoT data and can help you aggregate, store, manage and protect data in a centralized hybrid cloud system, while providing the ability to collaborate and share that data across the ecosystem.

Scalable Capacity to Handle Iot Data

Object storage solutions built on Western Digital Ultrastar platforms can be designed to handle massive amounts of data, such as that generated by IoT. Our high-density, low-power footprint and compelling economics means you can keep more data online versus deciding what to delete or take offline.

Ultrastar Data60 Storage Platform

A cost-effective 4U, 60 bay JBOD for software-defined storage (SDS) that delivers high density and the flexibility to balance performance with cost and provides up to 1.3PB¹ of raw storage in a compact and efficient form factor.

OpenFlex Data24 NVMe-oF Storage Platform

Extends the high performance of NVMe flash to shared storage. It provides low-latency sharing of NVMe SSDs over a high-performance Ethernet fabric to deliver similar performance to locally attached NVMe SSDs.

Ultrastar Data102 Storage Platform

Advanced storage platform for next-generation disaggregated Software-Defined Storage (SDS) environments. Extremely dense form factor provides up to 2.2PB¹ of raw storage in just 4U with the flexibility to balance capacity, performance and cost.

Ultrastar Edge Transportable Edge Server

A high-performance edge server that enables remote data capture and analytics at the cloud edge. Processing data closer to where it is generated reduces the latency associated with sending data from a remote location to the core for processing.