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IoT vs. Edge Computing: Key Differences

Today’s society is moving towards IoT implementations as most consumers purchase smart home devices or wearables. Smart homes, smart cars, and other personal devices are all connected and powered by computers at the network’s edge. The problem is that these edge devices have little to no security compared to traditional PCs running on the cloud. Many solutions have emerged to solve this issue, such as Edge Computing, which allows for multiple workloads on a single piece of hardware. This article will describe IoT, and edge computing, their differences, and their benefits.

What Is IoT?

IoT is essentially devices communicating with each other that don’t require a network connection to share information and data over short distances by way of radio waves or any other similar technology. This is especially useful for smart home appliances, sensors, and physical objects that use electricity and microprocessors to do something. For example, a thermostat connected to the internet would require online access to connect with an app or website to change the temperature of its home using a smartphone on a nearby table.

What Is Edge Computing?

This refers to computing power from various devices located at the edges of networks that are not traditionally used for general cloud computing purposes. This is because this type of edge computing is typically used for processing data about things or people located between the edge and the cloud. For example, a Jeep can be connected to the internet to allow it to send data about its engine, climate control settings, and other information to an app on your smartphone.

What Are Some Edge Computing Devices?

The following are some of the various devices and tools you can use to make use of edge computing:

  • Smartphones with embedded or external microprocessors
  • Digital cameras, GPS units, motion detectors, etc.
  • Digital thermometers, alarms, security systems, and satellite communications receivers.
  • Programmable logic controllers and sensory signals.
  • Drones, automated vacuum cleaners, security cameras, and similar items.

5 Differences Between IoT and Edge Computing

When comparing these two technologies, it can be easy to conflate them because they have a lot of similar characteristics. The following are five differences between them:

The main difference between the two is that IoT is used to talk about devices connected to the internet, while edge computing refers to devices at the edge of a network used for data processing.

It’s possible to add intelligence and connectivity to everyday items without IoT devices on the cloud. Still, with edge computing, you need devices at the edges of networks for them to work effectively.

IoT devices often gather and provide data about people or things over a long period. Edge computing is typically used to process data collected to make it available for nearby users.

IoT devices send data over the internet, whereas edge computing relies on direct contact between devices close to each other.

The main difference between these two technologies is that IoT refers to a network of objects on the internet. In contrast, edge computing refers to a network of processing devices at the edges of networks.

4 Benefits of IoT

The following are some of the benefits associated with using IoT devices:

  • Allowing machines to exchange data without human intervention.
  • Helping people become more productive by automating repetitive tasks.
  • Managing home and business functions.
  • Making processes more efficient, especially in cases where a business is working with an external supplier or partner.

Edge Computing Benefits

The following are some benefits associated with using edge computing:

1. Faster processing of data

Edge computing can help to process data in real-time, enabling individuals and businesses to get information faster. The processing power of edge computing is also more cost-effective than traditional cloud computing.

2. Improved operations

Because data is processed at the edges of networks, businesses and individuals can use that information to make smarter decisions. For example, if your smart fridge knows that you’re running low on milk, it could send you a text message, or if your smart thermostat notices that you’ve been home for several hours, it could adjust the temperature for you.

3. Saving resources

Suppose servers at the edges of networks are being used. In that case, this can result in small energy savings because electricity isn’t being wasted by collecting data without actual processing, which would need to be done at the cloud or data center.

4. Gathering and analyzing data

People can get access to real-time data, which means they can use it on their own devices more efficiently, which can result in cost savings or improved quality because they’re not paying for the costs associated with moving their data from the edge to the cloud.

Why IOT edge analytics?

Edge Analytics is the process of taking data from the edge to make it available for use. The main advantage of doing this is that data can be processed faster. While cloud computing requires data to be sent over a network, where it needs to be filtered through a server and then sent back, with edge computing, people can get a more detailed analysis of the device itself.

For example, if you were running a retail store connected to an app, you could use a tablet or smartphone as your home base to track inventory and manage stock levels throughout your store. This saves time and energy because you don’t have to move anything from point A to point B.
In conclusion, it is much more convenient to manage inventory using an edge-based computer rather than a traditional remote server. It is advisable to consult an expert during the initial stage of software development because the needs of these two platforms differ significantly, and it is essential to distinguish which one is better for your needs.

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