The typical smart factory is said to produce around 5 petabytes of data per week. That’s equivalent to 5 million gigabytes, or roughly 20,000 smartphones.

Managing such vast amounts of data in one facility, let alone a global organization, would be challenging enough. Doing so on the factory floor, in near-real-time, to drive insights, enhancements, and particularly safety, is a big dream for leading manufacturers. And for many, it’s becoming a reality, thanks to the possibilities unlocked with edge computing.

Edge computing brings computation, connectivity, and data closer to where the information is generated, enabling better data control, faster insights, and actions. Taking advantage of edge computing requires the hardware and software to collect, process, and analyze data locally to enable better decisions and improve operations.

At Hannover Messe 2022, Intel and Google Cloud will demonstrate a new technology implementation that combines the latest generation of Intel processors with Google Cloud’s data and AI expertise to optimize production operations from edge to cloud. This proof-of-concept project is powered by the Edge Insights for Industrial platform (EII), an industry-specific platform from Intel; and a pair of Google Cloud solutions: Anthos, Google Cloud’s managed applications platform, and the newly-launched Manufacturing Data Engine.

Edge computing exploits the untapped gold mine of data sitting on-site and is expected to grow rapidly. The Linux Foundation’s “2021 State of the Edge” predicts that by 2025, edge-related devices will produce roughly 90 zettabytes of data. Edge computing can help provide greater data privacy and security, and can accomodate the reduced bandwidth needs between local storage and the cloud.

Imagine a world in which the power of big data and AI-driven data analytics is available at the point where the data is gathered to inform, make, and implement decisions in near real-time.

This could be anywhere on the factory floor, from a welding station to a painting operation or more. Data would be collected by monitoring robotic welders, for example, and analyzed by industrial PCs (IPCs) located at the factory edge. These edge IPCs would detect when the welders are starting to go off spec, predicting increased defect rates even before they appear, and adding preventive maintenance to correct the errors without any direct intervention. Real time, predictive analytics using AI could substantially prevent defects before they happen. Or the same IPCs could use digital cameras for visual inspection to monitor and identify defects in real-time, allowing them to be addressed quickly.

Edge computing has powerful potential applications in assisting with data gathering, processing, storage and analysis in many manufacturing sectors, including automotive, semiconductor and electronics manufacturing, and consumer packaged goods. Whether modeling and analysis is done and stored locally or in the cloud, or is predictive, simultaneous, or lagged, technology providers are aligning to meet these needs. This is the new world of edge computing.

The joint Intel and Google Cloud proof of concept aims to extend the Google Cloud capabilities and solutions to the edge. Intel’s full breadth of industrial solutions, hardware and software, are coming together in this edge-ready solution, encompassing Google Cloud industry-leading tools. The concept shortens the time to insights, streamlining data analytics and AI at the edge.

The Intel-Google Cloud proof of concept demonstrates how manufacturers can gather and analyze data from over 250 factory devices using Manufacturing Connect from Google Cloud, providing a powerful platform to run data ingestion and AI analytics at the edge.

In this demonstration in Hannover, Intel and Google Cloud show how manufacturers can capture time-series data from robotic welders to inspect welding quality and show how predictive analytics can benefit the factory operators. In addition, the video and image data is captured from a factory camera to show how visual inspection can highlight anomalies on plastic chips with model scoring. The demo also features zero-touch device onboarding using FIDO Device Onboard (FDO) to illustrate the ease with which additional computers could be added to the existing Anthos cluster.

By combining Google Cloud’s expertise in data, AI/ML and Intel’s Edge Insight’s for Industrial platform that was optimized to run on Google Anthos, manufacturers can run and manage their containerized applications at the edge, in on-premise data center, or in public clouds using an efficient and secure connection to the Manufacturing Data Engine from Google Cloud. It forges a complete edge-to-cloud solution.

Simplified device onboarding is available using Fido Device Onboard (FDO)—an open IoT protocol that brings fast, secure, and scalable zero-touch onboarding of new IoT devices to the edge. FDO allows factories to easily deploy automation and intelligence in their environment without introducing complexity into their OT infrastructure.

The Intel-Google Cloud implementation can analyze that data using localized Intel or third-party AI and machine learning algorithms. Applications can be layered on the Intel hardware and Anthos ecosystem, allowing customized data monitoring and ingestion, data management and storage, modeling, and analytics. This joint PoC facilitates and support improved decision making and operations, whether automated or triggered by the engineers on the front lines.

Intel collaborates with a vibrant ecosystem of leading hardware partners to develop solutions for the industrial market by using the latest generation of Intel processors. These processors can run data intensive workloads at the edge with ease.

Putting data and AI directly into the hands of manufacturing engineers can improve quality inspection loops, customer satisfaction, and ultimately the bottom line.

The new manufacturing solutions will be demonstrated in person for the first time at Hannover Messe 2022, May 30–June 2, 2022. Visit us at Stand E68, Hall 004, or schedule a meeting for an onsite demonstration with our experts.

Cloud Firestore is a NoSQL document database that simplifies storing, syncing, and querying data for your mobile and web apps at global scale.

Cloud Firestore is a fast, fully managed, serverless, cloud-native NoSQL document database that simplifies storing, syncing, and querying data for your mobile, web, and IoT apps at global scale.

Its client libraries provide live synchronization and offline support, while its security features and integrations with Firebase and Google Cloud Platform (GCP) accelerate building truly serverless apps.

Here’s other stuff it’s good at:

Sync data across devices, on or offline

With Cloud Firestore, your applications can be updated in near real time when data on the back end changes. This is not only great for building collaborative multi-user mobile applications, but also means you can keep your data in sync with individual users who might want to use your app from multiple devices.

With Firebase Realtime Database, we felt we had built the best force-plate testing software on the market. Thanks to Cloud Firestore, in only two weeks, we built a system that’s significantly better and includes features we never thought possible to ship on Day 1.

Chris Wales, CTO, Hawkin Dynamics

Cloud Firestore has full offline support, so you can access and make changes to your data, and those changes will be synced to the cloud when the client comes back online. Built-in offline support leverages local cache to serve and store data, so your app remains responsive regardless of network latency or internet connectivity.

Simple and effortless

Cloud Firestore’s robust client libraries make it easy for you to update and receive new data while worrying less about establishing network connections or unforeseen race conditions. It can scale effortlessly as your app grows. Cloud Firestore allows you to run sophisticated queries against your data. This gives you more flexibility in the way you structure your data and can often mean that you have to do less filtering on the client, which keeps your network calls and data usage more efficient.

Enterprise-grade, scalable NoSQL

Cloud Firestore is a fast and fully managed NoSQL cloud database. It is built to scale and takes advantage of GCP’s powerful infrastructure, with automatic horizontal scaling in and out, in response to your application’s load. Security access controls for data are built in and enable you to handle data validation via a configuration language.

Cloud engineers face a constant barrage of new cloud services, products, and innovations. By late 2021, Google Cloud alone had released thousands of new features across hundreds of services. Couple this with other technologies and service releases, and it quickly becomes a herculean task for engineers to navigate, consume, and stay current on the ever changing technology landscape. We have heard from engineers this often leads to anxiety and frustration as engineers struggle to keep up. They are faced with a plethora of training options but often lack the time and funding. 

Google Cloud has reinvigorated technical training to make it more informative and applicable to public sector customers and partners. We aim to maximize your training experience so you can get targeted training when you need it. The Google Cloud Public Sector Technical Learning Series addresses customer feedback and provides fun and practical training. Sessions are currently running every two weeks. 

“Short and sweet” technical topics geared to subjects you care about

Generic training doesn’t always resonate with public sector technologists. Our new curriculum targets specific public sector use cases, is delivered by customer engineers, and can be accomplished in less than two hours.  This means participants can apply the learnings directly to real-life challenges quickly. 

Easy to find, easy to enroll 

Training opportunities should always be at your fingertips. Our automated training platform will ensure that you only need to enroll once. The system will automatically notify you of upcoming sessions so you can plan in advance and at your convenience. Sessions will be offered on a recurring basis to meet the needs of your organization.

Fun and engaging

Typical training sessions often include a sea of glazed eyes, unresponsive to basic prompts, falling asleep at our desks, we have all been there. But it doesn’t have to be this way. Our goal is to infuse Google culture into our training through interactive exchanges and tangible rewards to keep participants inspired and engaged.

Traditional technology training doesn’t always help you navigate the nuts and bolts of how to effectively introduce a product into an organization. But we know that technology doesn’t operate in isolation; it supports and becomes part of a living organism, managed by humans and confined by other components of an organization’s structure (e.g. existing systems or decentralized business units). 

Part of a larger community of like-minded engineers

Learning with – and from – a community of peers is one way to overcome the challenges and complexities of applying new technology within a complex organization. We created the Public Sector Connect community for this very reason. It is one example of how we surface best practices for public sector innovators. During weekly “Coffee Hours” and working sessions, our community members share their journey and lessons learned with each other. We know that innovation evolves through iteration and diverse perspectives, and Public Sector Connect is committed to helping surface critical challenges and solutions, and connecting those who are solving similar problems. Join the community today.