IoT vs. Edge Computing

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Over the past few years, access to low-cost computing, reliable sensors, and good connectivity have contributed to the commercial adoption of the Internet of Things. Thanks to IoT, we can connect sensor objects to the internet, exchange data, and monitor their interactions. No wonder, according to recent surveys, companies worldwide are rapidly adopting IoT solutions.

But given the number of IoT devices and the explosion of resultant data, sending all that information to the cloud is feasible. Better alternatives are required. Edge computing is well-positioned to fill this gap and take on this massive onslaught of data. By analyzing data at the source, edge computing reduces the pressure on data centers, mitigates latency, and ensures businesses work more efficiently.

Also see: Trends Shaping the Future of IoT

What is IoT?

The Internet of Things (IoT) is a system of interconnected physical, digital, mechanical, and computing devices or “things” embedded with unique identifiers (UIDs) that allow them to interact with each other over the internet. These devices run the entire gamut from commonplace objects to sophisticated tools.

IoT devices are fitted with sensors that make them “smart.” These sensors collect information leading to the creation of large volumes of data. An IoT gateway acts as a router and sends the data to the cloud via several data protocols, like HTTP and MQTT (MQ Telemetry Transport). Once the data reaches the cloud, analytical tools process the data and extract vital information. This information is then sent back to the end-user through an API.

What is Edge Computing?

The growing adoption of IoT is, in fact, a powerful driver for edge computing. As more and more IoT devices get connected, they will generate enormous amounts of data. But sending all this data to the cloud for processing can be counterproductive.

First, the costs of sending every piece of data to the cloud can be prohibitive. Second, sending so much data to the cloud can cause latency and bandwidth issues.

Edge computing pushes data processing near the point of origin (the sensor devices) instead of sending it to a centralized cloud located thousands of miles away. It is especially necessary where data is time-sensitive, and split-second decisions must be taken. Edge devices perform advanced analytics on the available information at the network edge and provide organizations with much-needed predictions and solutions in real-time.

Also see: 7 Enterprise Networking Challenges 

IoT vs. Edge Computing: How Are They Similar?

IoT and edge computing share certain similarities. In essence, both technologies work to capture data across a distributed computing environment. Both technologies:

  • Use sensors to capture data.
  • Produce data on a large scale.
  • Both are innovative technologies that are revolutionizing the way we use data.

IoT vs. Edge Computing: Differences Between the Two? 

While IoT shares similarities with edge computing, they’re not the same. Here’s how the two technologies differ:

  • In edge computing, the data processing is done locally, while in IoT devices, the data is sent to the cloud for data analysis. This is one of the most significant differences between IoT and edge devices.
  • IoT devices have to be internet-enabled for proper functioning. In edge devices, this feature is optional.
  • Each IoT device can perform a specific function only, while a single edge device can handle more than one function.
  • IoT devices have few data processing needs, so they are best suited for simple tasks. In contrast, edge devices run complex operating systems; therefore, they can support a range of data processing capabilities. 
  • Edge devices can handle large numbers of IoT devices.

Also see: Top Enterprise Networking Companies

Use Cases in IoT

Automotive IoT—Automotive IoT comprises equipping vehicles with sensors, gadgets, and internet access so that they can do predictive maintenance in real-time and be assured of safety. Thanks to IoT, connected car owners can monitor their vehicle’s health and receive updates on its upkeep and maintenance.  

Smart Homes—The smart home is one of the most popular IoT apps at present. In a smart home, your everyday devices are connected to the smart home system that allows you to monitor and operate your devices, even from a distance.  

Smart Cities—Smart cities depend on a massive IoT ecosystem equipped with apps and sensors to collect data. Analyzing the data at the source will help cities to improve their services and work more efficiently.

Industrial IoT—Industrial IoT comprises devices used in factories and other industrial sectors. These devices connect to an internal monitoring system that monitors KPIs and ensures things run smoothly.

Also see: Best Cloud Networking Solutions

Use Cases in Edge Computing

Manufacturing—Edge computing allows manufacturers to gather real-time information about the manufacturing process and make quicker decisions. By deploying sensors throughout the plant, manufacturers get insights into machine health and thus identify production issues before an error occurs.   

Autonomous Vehicles—Autonomous vehicles are one of the best examples of edge computing. Vehicle data must be analyzed in real-time when it is in motion; otherwise, it is useless. Edge devices study the data in real-time and convey instantaneous results to help with vehicle navigation.

Healthcare—Edge computing is having a transformative effect on the healthcare sector. With instantaneous data processing, hospitals are able to deliver better patient care even beyond the hospital walls. For instance, wearable healthcare gadgets support remote monitoring of chronic patients and notify caregivers whenever a problematic reading or unusual patient behavior occurs. 

Other uses include using augmented reality and VR to train staff, remote management of the movement of health equipment, and enabling robot-assisted surgery.

Future Trends in IoT and Edge

Increasingly, organizations are using edge computing and IoT to increase efficiencies and unlock business value. Here are some IoT and edge computing trends that will rule in 2022.

Set for Greater Growth

The edge computing market was worth $36.5 billion in 2021. It is expected to grow to $87.3 billion by 2026. This huge jump in numbers can be attributed to enterprises experiencing high growth by using IoT and edge devices.

5G to Gain Ground

The success of an IoT device depends on how fast it can connect to the cloud or other devices. With 5G touted to be much faster than 4G, organizations are expected to harness its speed to develop new use cases. In addition, consumers benefit from 5G as these networks can handle many devices without a breakdown.

Security to be Given More Importance

Edge computing centers can also be prone to security breaches. Distributed Denial of Service (DDoS) attacks, software injections, and routing attacks are some ways edge devices can be compromised. As edge computing start handling more confidential information, it is imperative they employ a Secure Access Service Edge (SASE) framework. The model includes a zero-trust network access (ZTNA), firewall as a service (FWaaS), and cloud access security broker (CASB), which ensures secure access irrespective of location.

Stakeholders will Adopt AI

As the volume of data generated by IoT devices snowballs, deriving actionable insights from them is vital. AI helps networks think intelligently. So, devices can learn from past activities and predict future actions without human intervention.    

Susnigdha Tripathy
Susnigdha Tripathy
Susnigdha Tripathy is a full-time writer and editor based in Singapore, and a regular contributor to Enterprise Networking Planet. She has over 10 years of experience writing, editing, and delivering exceptional content for a variety of international technology brands such as Virtasant, a cloud technology company, and Krista Software, a provider of intelligent automation solutions. She has also appeared in ServerWatch and other industry publications.

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