Edge computing today is one of industry’s most promising technology opportunities. Used in production by just over a quarter of manufacturers, it’s a tool that is expected to be trialed by more than half of U.S based manufacturing firms within the next two years. As a technology with revolutionary potential, it’s one that every manufacturer, tech firm, and company should be highly aware of and at least considering for production.
Reaching the full potential of edge computing is now closer and more attainable than many throughout industry think. Far from having to rebuild or re-tool from the ground up, it’s very often a process of gradual and incremental change that brings about steady improvements and efficiencies.
Looking at why edge computing is proving so popular and how to reach its abundant advantages, this blog post looks at what edge computing is, how it relates to IoT technologies, and how you can bring it into your business in a practical way.
What Is Edge Computing?
Technology focused on collecting, process, analyzing, and acting on data close to where it’s collected—edge computing is a deceptively simple idea. Performing tasks on the edge of the network rather than a central server or cloud solution, these devices are often physically located close to sensors, networking hardware, and peripheral networking nodes.
The key advantage of this system is in improving speeds and reducing the high networking burden placed on systems by an ever-increasing amount of sensors and inputs being added to the network to collect data.
Data is a manufacturing tool frequently proving to be a double-edged sword for many in industry. The access and insights created by a recent explosion in the availability and collection of data are undoubtedly changing the face of data science, but they are also presenting significant challenges in the storage, bandwidth, and processing requirements placed on businesses.
Thankfully, edge computing is making vast strides in changing things for firms. By creating opportunities to add devices and systems that can process, discard, and even act on data in real-time, edge capabilities turn data liabilities into efficiency generating data assets.
By allowing manufacturers additional flexibility in processes, eliminating time delays in production, and decreasing the reliance on bandwidth and network accessibility—edge computing is proving to be truly revolutionary for businesses who have deployed it so far.
IoT, IIoT, and Edge Computing
IoT devices are physical, network-connected, devices capable of reporting back data gathered from sensors and machines. Uses outside of industrial applications IoT devices make up much of today’s internet-connected consumer technologies that utilize smart capabilities.
Smart home thermostats, smart TVs, and wearable devices are all examples of IoT devices readily adopted by consumers.
In industry, the most common application of IoT is IIoT (Industrial Internet of Things) devices that have been designed specifically with industrial applications and requirements in mind. Commonly, these devices are used to connect to machines to gather data, monitor processes, link machines together, and occasionally act on data as needed.
While these devices can be connected directly to the cloud, they benefit from having additional edge computing resources within the network to decrease latency and automate decision-making when working with industrial processes.
By combining the benefits of IIoT and edge within business, the advantages that companies are able to reach include:
- Local data processing, aggregation, and rapid decision making via analytics algorithms and machine learning
- Scalable processing network comprised of low-cost components
- Increased industrial capabilities from off-the-shelf hardware sensors and parts
- Faster response times and increased operational efficiency
- Reduces the use of networking bandwidth during operation
- Improved resilience against poor network connectivity
IIoT devices are a way to provide data to edge resources, coordinate diverse edge computing assets within the network, and act on data processed at edge nodes. The efficiencies these assets create for businesses and the automation capabilities they create are some of the key reasons they are revolutionizing industries at a rapid pace.
Despite the power that IIoT can provide for companies, it’s a locally managed network simple enough to be broken down into just a few key parts. Far from a complex design of inter-dependent nodes, IIoT architecture is made up of just four capable components applied well to new or existing processes and machines.
The eyes and ears of IIoT technology, sensors are everything that can detect conditions in or around industrial processes and machines. These can include anything from temperature and humidity to barcodes, RFID tags, and even visual or audio recognition of what is happening within the environment.
the ‘hands-on’ part of IIoT systems, actuators are capable of making changes to the environment based on inputs. Actuators may simply inform other machines of processes being started or completed, physically move things around, or start and stop processes as needed.
Critical to combining IoT with edge computing capabilities, computers that live close to the heart of industrial systems and processes often implement previously trained machine learning algorithms to allow IIoT devices access to advanced automated capabilities.
Acting as a conductor for several different inter-related devices, the gateway enables data transfer between local devices and the cloud, where necessary, to create a highly capable complete manufacturing system. Key to smart industry infrastructure, the gateway decides how data should be acted on, discarded, or processed before use.
One of the most important factors of IIoT architecture and edge computing is that no two systems will ever look identical. The number and type of sensors, actuators, and processing devices used throughout a business will vary according to a company’s size and need. The gateway, however, is a core component in creating transformational systems that create revolutionary business changes. It’s no exaggeration to say that it’s universally central to successful IIoT edge implementations.
The IIoT Gateway
In IIoT systems, the gateway creates greater visibility, orchestrates faster systems response, and improves the throughput of data before even considering its interaction with the cloud. In short, it’s a piece of your IIoT network that enables everything else to work together.
Some of the features that today’s smart gateway devices enable for industry include:
- Real-time Processing and Decision Making.
Increasingly powerful processing capabilities are creating the opportunity for improved and more widespread automations in decision-making with reduced latency and connectivity requirements.
A key example of utilizing these capabilities within industry and manufacturing comes from systems able to respond to anomalies and errors that appear during operation using pre-trained machine learning models. IoT devices are able to take action to disable a broken workflow, retire a machine, or order replacement inventory before production is even interrupted.
- Active Monitoring.
Smart gateways also enable businesses to monitor the health of assets, the effectiveness of workflows, and the maintenance needs of critical equipment.
Combined with the right sensors, assets, and equipment—the gateway should be a key window into how well manufacturing is running and where process improvements can be made to boost efficiency. This data could be available locally on networked machines or accessible globally through a cloud management service available to relevant staff.
- Connectivity and Data Collection.
The IoT gateway acts as a driver of connectivity for an edge capable network. Responsible for collecting data from diverse areas of the network and translating it into a single common interface for data storage, transfer to the cloud, or local monitoring and storage.
With smart capabilities, modern gateway devices can make decisions about discarding or pre-processing data for more efficient use of resources. For businesses, this means greater flexibility, reliability, and security in business-critical systems that are vital to the company.
Implementing an intelligent gateway solution can be key to a strong and scalable IIoT and edge computing solution that meets your future requirements.
Combine Edge Computing with the Cloud
Three powerful technologies that are greater than the sum of their parts when combined, using IIoT and edge computing together with cloud technologies does more than save resources in industry. Cloud-based and edge technologies work well together to address the limitations of both platforms and create a best of both worlds solution.
The limited power and scalability of computing at the edge can be tackled by effectively integrating scalable and high-powered cloud platforms in the right places.
Conversely, the high-latency cloud response can be augmented by shifting some high-bandwidth computing tasks to edge devices to negate costs and time spent on data transfer.
A key example of combining these two approaches for a business use case would be using data collected from processes that IIoT devices couldn’t yet action. Without a trained ML model to work from, IIoT devices may be entirely blind to new processes. The raw data collected by these devices, however, is inherently valuable for creating new models that can later be applied.
Passed back to the cloud, the data captured at source can be used to train new models using the inherent capabilities of cloud computing. Using your chosen cloud service provider, you can then build assets to be deployed to the edge to manage future responses.
Leaning on popular ML packages such as TensorFlow, Azure ML, or Amazon SageMaker can bring these capabilities into your services at low cost and rapid pace.
Edge and cloud computing combined create a truly symbiotic relationship that thrives on the advantages of both technologies. Leaning on intelligent communication between the two platforms will create a high-performance system that enables continued improvements throughout its lifetime.
Your business should look to combine a capable cloud solution with edge technologies right from day one. Having the plug-in capabilities of the cloud readily available will encourage future growth and make scaling to new use-cases and capabilities far easier than applying the same solution retroactively would be.
Services Offered by Edge to Cloud Connections
- Predictive Maintenance.
The ability for devices to analyze data captured locally creates the opportunity for continuous monitoring by cloud-based analysis platforms. These tools can create automated alerts, improve maintenance schedules in response to incoming data, and reduce the likelihood of unplanned downtime.
- Improved Energy Efficiency.
Industry accounts for 33% of energy consumption in the United States, making it a big target for efficiencies and reductions. For businesses, it’s an area that impacts costs, capacity, and environmental footprint in a very significant way. With rising energy costs and a greater environmental awareness, many industries are looking at everything from smart devices and better equipment to the programming languages they use to reduce energy consumption and improve efficiency.
The use of edge computing can improve energy consumption by offering a detailed breakdown of statistics, intelligently managing resources within the firm, and cutting waste with data-based optimizations and automations.
- Data-Driven Optimisation.
Edge computing offers organizations the chance to interrogate their data all the way down to the granular scale of individual machines and products. This can mean automated ordering, pre-emptive replacement, and just-in-time manufacturing techniques capable of creating industry-defining optimizations within your business.
Getting Started with Industrial Edge Computing
Access to IIoT and edge computing tools is more attainable today than it’s ever been before.
Software integrations are making more and more things possible with automations available for reporting, actioning, and processing captured data through the cloud. SAP Internet of Things is an example of a business technology platform that can fully utilize IIoT services to enhance processes that include product design, manufacturing, delivery, and operation.
One of the key software assets that have brought edge computing to the forefront of modern tools has been containerization. A technology that allows runtime environments and dependencies to be bundled together with software solutions, containers enable entire environments to be moved from the cloud to the edge without compromising reliability.
Kubernetes is a leading open-source platform for deploying containers across cloud-edge solutions. For all businesses, being able to lean on these technologies, amongst others, has been truly game-changing in making edge computing accessible at scale.
When it comes to deploying the hardware necessary to connect to these software solutions, the equipment to do so is increasingly available off-the-shelf for businesses. Even legacy machines can be incorporated into the network by adding readily available hardware sensors and actuators to enable automated capabilities and reporting across the network.
Combining cloud solutions, IIoT devices, and edge computing capabilities with off-the-shelf hardware components has the potential to create a low-cost access point for edge computing tools and advanced cloud capabilities.
If you’re yet to apply IoT, IIoT, or Edge computing technologies into your organization then there’s never been a better time than now. Within this blog post, we’ve outlined the performance advantages, opportunities, and resources the technology provides to allow organizations the chance to revolutionize their services.
Introducing the individual components of this tech and the benefits they can bring to industry, we’ve highlighted the role each part of the system plays in creating an edge computing network and the services they enable for companies. From here, you should be able to identify a starting point to bring the services that matter into your organization and get started with an industrial edge computing network.
Perhaps this is a process that’s already been started in your organization? Let us know what stage you’re at, or tell us what’s keeping you from implementing IIoT technologies within your business with a comment below.
We’d love to start a dialogue on where IIoT and edge computing can and should go in the very near future and how you’d like to see it improve.