IoT and edge computing – what is it and how will businesses benefit from it

The Internet of Things, or IoT, refers to the billions of physical devices around the world that are now connected to the internet, collecting and sharing data. The idea of adding sensor and intelligence to basic objects was discussed as early as the 1980s, excluding some early projects such as internet-connected vending machine, adoption was slow because the technology wasn't ready. Eventually, prices dropped, and processors, devices and connectivity became cheap. IoT adoption accelerated and turned into a billion-dollar industry.

Many of us already use IoT, on a regular basis. From wearable health monitoring devices, smart surveillance systems to predictive maintenance and supply chain optimization in the industry. IoT is pioneering the next phase in the Internet’s evolution. At an even bigger scale, smart cities projects are filling entire areas with sensors to help us understand and control the environment in order to improve quality of life

Gartner forecasts that the number of connected devices is expected to exceed 25 billion by 2021 according to Gartner, producing big volume of data. “Data is the fuel that powers the IoT and the organization’s ability to derive meaning from it will define their long-term success,” said Mr. Nick Jones, research vice president at Gartner.

Then what is edge computing, why does it matter and how does it relate to IoT?

Let’s start with the definition of edge computing. Edge computing is a distributed computing paradigm which brings computation and data storage closer to the location where it is needed, to improve response times and save bandwidth according to Eric Hamilton. Alex Reznik, Chair of the ETSI MEC ISG standards committee, has a broad definition, "anything that’s not a traditional data center could be the ‘edge’ to somebody."

Hence, instead of having a centralized, remote cloud to do all the work, the data is handled and stored locally, i.e. on the IoT device itself or at the nearest network node.

Some IT professionals might argue that edge computing is not that different from traditional distributed computing, which saw computing power move out of the data center and into business departments and offices several decades ago. Edge computing is different because of the way edge computing is tethered to IoT data that is collected from remote sensors, smartphones, tablets, and machines.

What drives edge computing?

First, to understand what impact edge computing will have, it is important to know how it evolved. There are a broad set of use cases and conditions in which they operate. Edge technologies can operate in places that might limit or require intermittent connectivity to the cloud for services like computing, storage, backup, and analytics. Furthermore, edge use cases often require data to be processed instantly. These devices and platforms need to be able to do analytics locally, without first sending data to the cloud, so decisions can be made rapidly.

The potential business value of edge computing could be more than 200 billion usd in hardware value by 2025, according to McKinsey, across all industry sectors and comprising more than 100 use cases.

How does edge computing work?

Every IoT device produces data. In the case of cloud computing, the data is instantly transferred to the cloud where it’s processed and stored. An application in the cloud, may analyze and send back response to device to act. The whole process is fast but there might be situations when the response may be delayed or interrupted due to poor network performance and between data center and device.

In the case of edge computing, you don’t need to send the data acquired by the IoT sensors anywhere. The device itself or the nearest network node is responsible for data processing and can respond in a proper manner if action is required. Consequently, the IoT device is no longer dependent on the network performance or distance and can function as a standalone computing node.

What are the benefits and real-life use cases for edge computing in IoT?

It is all about decentralizing data handling. This results in several advantages over the traditional cloud.

1.     Reduced operational costs

When you store and process most of the data “at the edge”, you don’t need an abundance of cloud storage. Plus, you can filter out the unnecessary information and backup only the relevant data. As a result, your infrastructure costs will inevitably go down.

2.     Better responsiveness

By processing the data close to its source, you reduce the lag time Consequently, you can analyze the data in real-time, without delays. In manufacturing, by detecting an irregular machine pattern and automatically take appropriate actions to avoid downtime might mean saving millions of dollars.

3.     Increased data security and compliancy

The data is decentralized and distributed among the devices where it is produced, it’s difficult to take down the whole network or compromise all the data with a single attack. The less sensitive information is sent through your network and stored in your cloud, the better it is from a compliancy perspective.

4.     Improved business efficiency and reliability

Lower data traffic and reduced cloud storage can improve operations financially. As an example, in oil industry where you have oil rigs geographically distributed. An oil rig in the ocean that has thousands of sensors producing large amounts of data, most of which could be inconsequential; perhaps it is data that confirms systems are working properly. That data doesn’t necessarily need to be sent over a network as soon as its produced, so instead the local edge computing system compiles the data and sends daily reports to a central data center or cloud for long-term storage. By only sending important data over the network, the edge computing system reduces the data traversing the network which reduces bandwidth costs.

In some cases, you can avoid connectivity issues because your devices can work independently, without internet connection.

Edge computing really shines when it comes to time-sensitive tasks. It is applicable to all industries. Let′s go through a few interesting use cases.

Use cases:

Financial services

Edge deployments allow data to be processed closer to the source, resulting in low-latency, low-cost network transport. Today a common use case in trading. Banks are also adopting interactive ATMs that quickly process data to provide better customer experiences.

Automotive

A moving self-driving vehicle simply cannot rely on a remote server to decide if it needs to stop when there’s a pedestrian crossing the road in front of it. The decision needs to be made immediately. The data must be processed on the spot, regardless of the internet connection.

Logistics and fleet management

Logistics providers use a combination of IoT and edge computing in their warehouses and distribution centers to track the movement of goods through the warehouses and in the warehouse yards.

Healthcare

Remote health monitoring where you keep track of the patient’s chronic conditions. For example, a heart rate monitor can analyze health data independently, can instantly provide the necessary response to alert caregivers when a patient needs their help. A life saver.

Retail

Retailers use edge computing to collect point of sales data at each of their stores. They transmit the data later to their central CRM and financial systems for further analysis and execution.

Mining

Mining companies deploy edge computing with IoT sensors on trucks to track the vehicles as they enter remote areas. These companies also use edge computing to monitor equipment on the trucks to prevent goods in transit from being stolen for resale in the black market.

Security solutions

Surveillance cameras can detect motion, smoke, identify trespassers, and instantly alert users in case of trespassing or suspicious activity. Video format also tends to generate big amounts of data. Processing this data at the edge will save bandwidth costs.

How about the future of Edge compute?

By 2022, 75% of enterprise data will be processed outside of the cloud (as well as traditional data centers), according to Gartner. As a result, the size of the edge computing market will surpass $13 billion worldwide within the same timeframe.

Business executives, entrepreneurs and developers should seriously analyze, explore and consider edge compute for their roadmaps or risk loose competitiveness to other players that take full advantage of this technology.