A Guide to Understanding Edge Computing, IoT Devices, and Sensors
As enterprises continue to innovate, the need for faster and more efficient data processing is growing. Edge computing, Internet of Things (IoT) devices, and sensors are all technologies that help meet this need, and organizations worldwide have successfully leveraged them to achieve positive outcomes. However, they also introduce new security concerns that must be addressed to protect sensitive information.
In this blog, I’ll be walking you through how edge computing and IoT can maximize accuracy and user experience. I’ll be explaining the differences between edge devices, devices using IoT technology, and the types of IoT sensors available that can scale production, quality, and decision-making. Let’s get right into it.
What Is Edge Computing?
Edge computing is a process that takes place near a data source of a literal, physical location to gather reliable data for better, more enhanced user experiences while identifying industry trends, and ultimately offering better services and products.
On a grassroots level, edge computing helps in utilizing and distributing data that is collected from a pool of resources like IoT sensors. This makes it incredibly easy for business owners to scale from the ground up and digitally transform their business.
While devices with IoT technology send data to a centralized center or cloud, edge computing processes and analyze data at a closer point where it was created. So, with edge computing, data isn’t sent over a cloud, network, or data center – edge computing offers a more thorough, comprehensive analysis of the data collected, which helps business owners enable faster solutions and improve customer experiences.
Differences between Edge and IoT Devices
Edge devices are pieces of hardware that are often located in remote locations of a network to collect and process data. With adequate memory, processing power, and resources, these devices can also execute solutions in real time as a result of information that was derived from previously collected data.
Devices with IoT technology on the other hand are physical objects that are connected to the internet. They can detect changes in infrastructure and transverse data from a vast variety of networks and connected devices. IoT solutions and edge computing can both offer a breakthrough to streamline industrial automation.
What Is an IoT Sensor and How Does It Work?
IoT is growing to become the foundation for industrial automation, thanks to IoT sensors. This includes providing devices the ability to share and collect data. Let’s dive deeper into the types of IoT sensors available that can bridge the digital and physical world by collecting intricate data to measure pressure, temperature, and changes in motion.
1. Temperature Sensors
Temperature sensors are tools utilized in diverse industries like healthcare, agriculture, and manufacturing to measure the amount of heat produced from a specific object or area. These IoT sensors function by detecting temperature changes and converting them into useful data.
2. Proximity Sensors
Proximity sensors are quite common in retail sectors, as well as industrial sectors. They detect the presence or absence of objects near the sensor without physical contact. These sensors often emit a beam of infrared radiation. These IoT sensors are used for monitoring and controlling the manufacturing process in warehouses.
3. Pressure Sensors
These sensors are capable of detecting alterations in the gas or liquid. Whenever the pressure range exceeds a predetermined threshold, the pressure sensors issue an alert regarding the detected issue. These sensors are also utilized for leak testing, water systems, vehicles, and aircraft, pressure sensors are an incredibly versatile tool.
Now that we have a thorough idea of what IoT sensors are and how they can help, let’s understand what IoT sensor inference is and how it’s of paramount importance with IoT technology.
What is IoT Sensor Inference?
IoT inference is the process where machine learning models analyze the data that is collected by IoT sensors. Inference itself is the stage where machine learning models are used to make predictions or decisions after analyzing temperature, proximity, pressure, and other measurable characteristics.
Fortinet believes that this also tremendously helps in identifying user-market trends. Ultimately, making it possible for manufacturers and business owners to automate production – making it a strong IoT solution in industrial industries, specifically.
Examples of IoT inference include predicting equipment failure in industrial settings, detecting anomalies in environmental data, or recognizing objects in security footage. Inference is a critical component of many IoT applications, and it enables them to provide real-time insights and automated decision-making.
The Problem with Unpatched IoT Devices
IoT has helped in streamlining operations, management, and quality control, but there are certain risks to be aware of. Even a small vulnerability such as an unpatched sensor on a device can compromise the sensitive data of the business.
In the manufacturing industry, implementing IoT can make devices vulnerable to attacks, as they typically employ node software and Linux-based gateways, which can be highly attractive to malicious actors.
Now that we’ve identified how vulnerable connected devices can be, it is critical for protecting your organization and business from cyber threats. Automated live patching is a solution that greatly benefits manufacturers, business owners, and warehouse employees.
How Automated Live Patching Can Optimize the Efficiency in IoT Environments
Since edge computing and IoT devices can offer problem-solving IoT solutions in real time, their efficiency can’t afford to take the brunt of unpatched vulnerabilities. IoT technology in itself is known to reduce latency and bandwidth, so enabling automated patching will be incredibly useful and productive.
With Tuxcare’s KernelCare Enterprise for IoT, enterprises can take advantage of efficient IoT sensors without having to stop production for individual devices. Then, it can apply the most recent patches.
Avoid waiting for vulnerability patches and dread the downtime that results from having to reset your servers. The KernelCare Enterprise for IoT sends fixes to a Linux kernel while the device is in use.
TuxCare can assist in improving the security of your IoT devices so you don’t bear the brunt of unpatched vulnerabilities and malicious threats. Speak with a TuxCare expert about how you can keep your IoT devices safe.