In the past few years, low-cost computing, reliable sensors, and good connectivity have contributed to the commercial application of iot. With the Internet of Things, people can connect sensor objects to the Internet, exchange data and monitor their interactions. And according to recent surveys, businesses around the world are rapidly adopting iot solutions.
But given the explosion in the number of iot devices and resulting data, it is feasible for companies to send all this information to the cloud, but better alternatives are needed. Edge computing is well positioned to fill this gap and cope with this massive data onslaught. By analyzing data at source, edge computing can reduce stress on data centers, reduce network latency, and ensure that enterprises work more efficiently.
What is Internet of Things?
The Internet of Things 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 full range from ordinary objects to complex tools.
Iot devices are equipped with sensors that make them "smart." These sensors collect information and generate a lot of data. Iot gateways act as routers to send data to the cloud via multiple data protocols such as HTTP and Message Queue Telemetry Transfer (MQTT). Once the data reaches the cloud, analytics tools process it and extract important information. This information is then sent back to the end user through the API.
What is Edge computing?
In fact, the growing popularity of the Internet of Things is a powerful driver of edge computing. As more and more iot devices become connected, they will generate huge amounts of data. But sending all that data to the cloud for processing can backfire.
First, the cost of sending each piece of data to the cloud can be prohibitive. Second, sending so much data to the cloud causes latency and bandwidth issues.
Edge computing pushes data processing closer to the origin (sensor devices) rather than sending it to a centralized cloud platform located thousands of miles away. This is especially necessary where data is time sensitive and split-second decisions must be made. Edge devices perform advanced analysis of the information available at the edge of the network and provide much-needed predictions and solutions to the enterprise in real time.
How is the Internet of Things similar to edge computing?
The Internet of Things and edge computing have some similarities. Essentially, both technologies aim to capture data in a distributed computing environment. These two techniques:
Use sensors to capture data.
Mass production of data.
Both are innovative technologies that revolutionize the way data is used.
The Difference between the Internet of Things and Edge Computing?
While there are similarities between the Internet of Things and edge computing, they are not the same. Here are the differences between the two technologies:
In edge computing, data processing is done locally, while in iot devices, data is sent to the cloud for data analysis. This is one of the most striking differences between the Internet of Things and edge devices.
Iot devices must support the Internet in order to function properly. In edge devices, this feature is optional.
Each iot device can only perform specific functions, while a single edge device can handle multiple functions.
Iot devices have few data processing requirements, so they are best suited for simple tasks. By contrast, edge devices run complex operating systems; As a result, they can support a range of data processing capabilities.
Edge?? Devices can handle a large number of iot devices.
Internet of Things use cases
Automotive iot - Automotive iot involves equipping vehicles with sensors, tools, and Internet access so that they can perform predictive maintenance and ensure safety in real time. With the Internet of Things, owners can monitor the health of their vehicles and receive updates about their care and maintenance.
Smart Home -- Smart home is one of the most popular iot applications. In a smart home, a user's everyday devices are connected to a smart home system and can be monitored and operated even from a distance.
Smart cities - Smart cities rely on a vast iot ecosystem equipped with apps and sensors to collect data. Analyzing data from the source will help cities improve services and work more efficiently.
Industrial Internet of Things - The Industrial Internet of Things includes equipment used in factories and other industrial sectors. These devices are connected to an internal monitoring system that monitors key performance indicators (KPIs) and ensures that things are running smoothly.
Use cases in edge computing
Manufacturing - Edge computing enables manufacturers to gather real-time information about the manufacturing process and make faster decisions. By deploying sensors throughout the plant, manufacturers can gain insight into machine health to identify production issues before errors occur.
Self-driving cars - Self-driving cars are one of the best examples of edge computing. Vehicle data must be analyzed in real time while driving; Otherwise it is useless. Edge devices study data in real time and communicate immediate results to aid vehicle navigation.
Healthcare - Edge computing is having a transformative impact on the healthcare industry. With just-in-time data processing, hospitals are able to provide better patient care even beyond their walls. For example, wearable medical devices enable remote monitoring of patients with chronic conditions and notify caregivers of reading problems or abnormal patient behavior.
Other uses include using augmented and virtual reality to train staff, remotely manage the movement of medical devices and enable robot-assisted surgery.
The future of the Internet of Things and the edge
More and more enterprises are using edge computing and the Internet of Things to increase efficiency and unlock business value. Here are some of the iot and edge computing trends that will dominate in 2022.
Be ready for even greater growth
In 2021, the edge computing market size was US $36.5 billion. It is projected to grow to $87.3 billion by 2026. The huge increase in volume can be attributed to the high growth rate achieved by enterprises through the use of iot and edge devices.
The success of an iot device depends on how fast it connects to a cloud platform or other device. Because 5G is billed as much faster than 4G, companies are expected to use its speed to develop new use cases. In addition, consumers can benefit from 5G because these networks can handle many devices without failure.
Pay more attention to safety
Edge computing centers are also prone to security breaches. Distributed Denial of service (DDoS) attacks, software injection, and routing attacks are some of the ways edge devices can be compromised. As edge computing begins to handle more confidential information, they must adopt the Secure Access Service Edge (SASE) framework. The model includes zero-trust Network Access (ZTNA), Firewall as a Service (FWaaS), and Cloud Access Security Proxy (CASB) to ensure secure access regardless of location.
Stakeholders will adopt AI
As the amount of data generated by iot devices snowballs, gaining actionable insights from it is critical. Artificial intelligence helps the network think intelligently. As a result, devices can learn from past activities and predict future actions without human intervention.