One of our clients said it best when they told us, “Each signal matters.” This client used this phrase to describe the importance and the function of edge computing in a health monitoring edge computing application we helped them construct to support their operations in caring for the elderly. In bypassing the cloud and processing data from wearable devices at the edge, local devices can respond immediately to any change in vital signs and immediately make a call to alert the relevant care professionals. Each signal matters and no signal gets missed.
Unlike cloud computing, edge computing technology handles the data where it is generated. Rather than centralizing in the cloud, it is decentralized. This decentralization allows much less latency and rapid responses to new events. This is why edge computing is particularly appealing to Industries with significant risks, such as healthcare, mining, and extractive industries. If you can’t always count on a stable connection to the cloud, or if you can’t wait for your data to make a round trip into the cloud and back, then edge computing is a perfect solution.
Read on for just some of the benefits that IoT and edge computing can unlock for your business:
- Monitoring, insights, and intelligent decision-making can all take place in real-time
- Lightning-fast response to malfunctions, customer requests, or accidents
- Lower spending for cloud computing and web traffic servicing
Now, we’ll look at several edge computing real-life examples from several industries.
Traditional retailers can stay relevant and compete against online newcomers by using edge computing to improve their customers’ experience. However, this doesn’t mean that a brick-and-mortar retailer needs to buy and install numerous connected devices in their store instead of a carefully curated stock display. In the world of conventional, real-world retail, real estate is the biggest limiting factor, and space is money. For these reasons, modern iot development services and edge computing solutions combine multiple functions into a single device.
The California-based IT company, Cohesity, prides itself on its data management solutions. It counts a range of high-profile global companies among its clients, with some retailers among them. Cohesity’s devices replace multiple alternative pieces of hardware, enabling retailers to reduce space utilization and free up more room for displaying the products they aim to sell. The data management solution runs on a Point of Sale (PoS) machine with relatively modest computing power and electricity demands. This solution integrates scanner data and weighing equipment data with surveillance footage from the checkout area to improve returns and reduce losses.
Mining continues to be one of the world’s most hazardous jobs, where inadequate controls or bad data can lead to extremely serious incidents. But setting up Wi-Fi and digital connectivity in underground tunnels and shafts is difficult and expensive. These dangerous and logistically difficult environments mean that cloud solutions simply aren’t the best choice. At the same time, the industry continues to view safe working conditions as a critical goal to work toward, and this goal just isn’t reachable without continued process automation. In many of these remote and hazardous environments, efforts toward automation necessarily imply that devices must collect and process data at the edge and not in the cloud.
Bolodine is a giant among global mining companies. Bolodine recently partnered with Ericsson to digitalize Aitik, a Swedish underground mine. Bolodine’s objective was to begin by automating the most dangerous processes, such as drilling blast holes. Starting by automating the most dangerous processes promised to rapidly and significantly improve safety in a “low-hanging fruit” situation.
Bolodine retrofitted sensors and cameras onto drilling rigs to achieve this objective to facilitate remote control. Edge computing applications now enable these machines to continue their work remotely and autonomously, keeping human workers out of harm’s way.
When it becomes necessary for an operator to modify a work process, they can make the required changes without going into harm’s way, often without even being on site. Edge computing takes human workers out of the physical loop while still keeping them connected through data and controls.
We’ve already briefly mentioned one example of edge computing applications in caring for seniors, but the market for edge computing within healthcare goes far beyond this. In 2021, the American Hospital Association conducted a survey of bedside devices which yielded a staggering total of close to 14 million such devices already deployed. Collecting medical data safely and reliably from all of these wearables and medical sensors is no mean feat. And making effective use of this growing mountain of data while complying with evolving expectations and rules on data security can be even more complicated. Fortunately, edge computing offers an optimal solution for real-time analysis of continuous data flows, even when these take the shape of large files. Plus, it’s a perfect solution for a post-COVID world of virtual visits to the doctor and increasingly sophisticated consumer wearables. Edge computing and IoT allow clinicians to receive accurate and appropriate alerts outside hospital walls and exam rooms.
We’ve got another excellent use case from Barcelona, Spain. In a connected ambulance, onboard medical devices collect and analyze patients’ biometric data and then compare it with their Electronic Health Records (EHR). This data and insights let paramedics determine the best treatment with minimal consideration before reaching the hospital. Personnel within the emergency room also receive alerts about the best preparation for the patient’s care needs.
Construction companies spend millions of dollars annually on various pieces of capital equipment. However, no matter how much you spend, things can still go wrong, and unnoticed wear and tear can lead to unexpected breakdowns. Because of the size and expense of these pieces of equipment, a single failure can lead to justified panic, extended downtime, and significant cost increases or even overruns.
All these factors help explain why so many construction businesses find predictive maintenance solutions so irresistible and why edge computing is such a critical part of successful implementation in so many cases. These technologies continuously monitor valuable assets, such as mission-critical capital equipment, and then use this data to detect signs of unexpected wear and tear and predict equipment failures. This allows companies to be proactive in their maintenance and to schedule repairs before the failures become catastrophic. This precautionary approach to the health of mission-critical construction equipment helps to extend these valuable assets’ life and dramatically reduce equipment repair costs.
The industrial giant General Electric (GE) is one of the largest and oldest US industrial names. Among its other fields, GE is active in energy production, manufacturing engines, steam turbines, gas turbines, generators, and high-voltage equipment. However, a major problem within its production cycle was equipment health. Due to insufficient controls and data, General Electric couldn’t detect issues in a timely fashion. The result: manufacturing yields fell, and expenses increased in the form of multi-million-dollar scrap costs.
Everything changed when General Electric empowered its winding machines with IoT and edge computing technologies. Now, the deployed edge computing equipment analyzes raw sensor data to rapidly and proactively identify failing machinery. This proactive, efficient, and distributed approach protects the entire manufacturing floor from unnecessary disruptions and production delays.
To Sum Up
Every business wants the best data. Every business wishes it could act and respond to problems in real-time, even when telecommunications equipment is unstable or offline. However, most businesses now rely on cloud-based autonomous systems to perform the analysis and quick decision-making these objectives demand. Can you afford the bandwidth for such significant data throughputs from systems continuously sending raw data over your network? Even more, is this the most efficient way to address this problem, and can this approach remain compatible with evolving rules and expectations on data privacy and security?
Edge computing addresses all these concerns by using real-time data cost-effectively, without transporting it offsite or into the cloud. In edge computing, you can bypass the cloud and do the data processing locally, sometimes on the same device that harvests a piece of data. This approach saves you time and money, helps reduce the risk and compliance cost from possible data breaches, and lets your business move forward with autonomous, lightning-fast, insight-driving autonomous actions. Schedule a consultation with one of our experts today to see how IoT and edge computing can help your business.
This UrIoTNews article is syndicated fromGoogle News