Edge Computing Drives the Internet of Things

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Edge computing drives IoT Internet of Things

Edge computing may not be as well-known as cloud computing, but it will be soon. Revenue generation within this market is expected to jump from $2.8 billion in 2019 to $9 billion in 2024. One of the big reasons is that edge computing drives the Internet of Things (IoT), which is also expected to grow considerably in the coming years. 

But, what exactly is edge computing, how does it support the IoT, and what does all of this mean for consumers and businesses? Here we explore these questions and more. 

 

What Is Edge Computing?

While cloud storage and computing, such as online backup services, happen far away from end-users and their devices, edge computing brings processing closer. For example, a small business might have security cameras set up that, in the past, would send data to the cloud for analysis and storage. Now, edge computing allows data processing to happen on an on-premise system that can analyze data more quickly and send out timely alerts. 

According to Network World, other devices that might make use of edge computing “can include many different things, such as … an employee’s notebook computer, their latest smartphone … or even the internet-connected microwave oven in the office break room.” 

Edge computing can be used in conjunction with cloud computing as when data is processed immediately on the edge and later moved, in part or completely, to a storage location in the cloud. Edge computing solves problems presented by cloud computing, including slow speeds and high costs. The following video provides a detailed explanation of edge computing. 

 

 

Edge Computing Pros and Cons

Like any other technology, edge computing has its pros and cons. One of the pros is cost savings. When companies can limit the amount of data being processed in cloud-based locations, they can save money on cloud services. 

Another pro is low latency (delay), which enables the ability to collect, send, analyze, and retrieve data with minimal lag time. Another is connection reliability. As edge computing becomes more prevalent within mission-critical infrastructures, this quality is increasingly essential. 

Cons include the problems that result when an edge-computing system is used by an increasing number of devices. In this case, the transmission may suffer from latency. In this case, bandwidth costs may increase. Other potential cons are physical and virtual security challenges and system setups that are too complex and difficult to manage. 

 

IoT on the Edge

The IoT has had to rely on cloud computing for data processing, yet this process can take more time than is appropriate for many applications. For example, according to IoT For All, “In a factory setting, if a sensor logs a reading as being too hot, then a machine may need to be shut down immediately. By not sending that data for processing in a central cloud server, action can be taken more quickly.” 

This enhanced speed offers benefits including lowering repair or maintenance costs, protecting worker safety, and avoiding the time that would be lost if part of a production line had to be shut down.

Edge technology is useful not just for network edges, but for physical edges as well — that is, places that are removed from central computing locations. Such places could include satellite offices of retail or financial enterprises, which require fast business-critical processing, especially in remote positions, or even study locations such as below the earth’s surface or a jungle. 

 

IoT and Edge Applications

Together, the IoT and edge computing provide the foundation for numerous applications, some of which have been mentioned above. Additional use cases include the following. 

  • Farms. IoT devices can be used to detect plant growth and soil conditions and edge computing used to analyze appropriate water and nutrition. 
  • Autonomous vehicles. Self-driving cars and trucks use sensors to send information about traffic conditions and receive feedback to make decisions, including potentially life-saving ones, such as stopping at a crosswalk where pedestrians are present.
  • Homes. Increasingly, smart homes include devices that, in combination with fast processing, can detect and send alerts about break-ins or problems with home systems. 
  • Healthcare. Mobile applications and wearables can be used to record patient data and quickly send it to healthcare professionals. 
  • Electricity. Power companies use sensors on equipment to monitor health and age, enabling them to take care of small problems or replace parts before more costly interventions are needed.

All these uses can benefit from edge computing either to increase speed or to reduce the amount of data (and therefore minimize costs) of being sent to the cloud.

 

Security on the Edge

As with all digital information, security must be a primary consideration. The chance of interference within an edge computing environment is increased by the number of devices potentially accessing it. IoT devices are targets for hackers because of their notoriously lax security features. Also, the physical environment may not be as protected as a cloud-based hosting service, which typically has layers of security measures in place. 

Deloitte notes, “Maintaining the physical and cybersecurity position of all assets in the edge is a complex and critical challenge.” However, these problems can be resolved by developing strict security standards for edge security systems, using data encryption, and deploying robust access-control methods. Additionally, artificial intelligence (AI) programs can monitor edge systems to detect and respond to security threats. 

At the same time, edge computing systems may keep data safer by reducing the distance it has to travel for processing. With more data being kept close to its source, hackers are less likely to see cloud-based servers as good targets to attack. 

 

What’s Next

Edge computing with IoT is a powerful combination of technologies that is poised to push convenience, efficiency, and safety across industries. Watch for more and better autonomous machines, including vehicles and drones, and a higher level of AI and machine learning applications. 

Another likely outcome includes more secure electric and telecommunications grids, which will become increasingly protected by the ability to quickly transmit information about breakdowns and interference. We may also see an increase in convenience features, such as facial recognition to get on a plane. 

No doubt, as the technology matures, current issues will be resolved, and users will develop many more novel uses. 

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