Category: Know How

Machine learning defined more precisely

Machine learning is an area of artificial intelligence that enables computers to learn from data and continuously improve themselves instead of being explicitly programmed. Algorithms are trained to recognize patterns and correlations in large data sets and to make the best decisions and predictions based on these analyses. This leads to automated knowledge generation, the identification of correlations and the application of these findings to unknown data sets for the optimization of processes and the prediction of future developments.

How does machine learning work?

To make machine learning effective, training by a human is required. There are various learning models that use different algorithmic techniques. A model is selected depending on the desired result and type of data, whereby a distinction is made between supervised, unsupervised, partially supervised or reinforcement learning. Within these models, specific algorithmic techniques can be applied according to the intended result. The algorithms are used individually or in combination to ensure accuracy in the processing of complex and unpredictable data. This development process is iterative and is often repeated several times until the desired quality level is achieved. Once the learning process is complete, the trained model evaluates unknown data in order to make improved decisions. The main goal is for the computer to learn autonomously and adapt its actions without human intervention.

Types of machine learning algorithms

Supervised learning uses known data, recognizes patterns and learns from a training data set. It aims to accurately predict a target variable, such as when forecasting electricity consumption or assessing the risk of investments.

Unsupervised learning visualizes large amounts of data, performs cluster analyses and independently detects hidden patterns or groups. It is not suitable for precise predictions, but requires an assessment based on more flexible factors, suitable for the desired business application.

Semi-supervised learning combines supervised and unsupervised learning, uses sample data with target variables and unknown data. It is used in areas such as image or object recognition, where a small amount of data with target variables and a larger amount of data without target variables are used.

Reinforcement learning interacts with the environment and learns a strategy for solving a problem through a cost function or reward system. In contrast to other methods, it does not require sample data, but develops an optimal action strategy in simulation steps.

Areas of application for machine learning

The areas of application of machine learning can be assigned to the individual learning methods. Unsupervised learning is therefore ideal for dimension reduction (recognizing structures, compressing information, big data visualization, etc.) and cluster analysis in the form of market and customer segmentation or recommendation systems. Supervised learning is used for classifications such as text and object recognition or forecasts (demand, weather, sales, customer values, etc.). Reinforcement learning is ideal for autonomous driving, game AI, traffic control, robotics and also for personalization and advertising.

Machine learning and spo-comm Mini-PCs

Of course, our spo-comm product portfolio also includes mini PCs that are suitable for machine learning. We are talking about our mini PCs that are equipped with a dedicated graphics card. The KUMO VI and the QUADRO P1000 are therefore suitable for machine learning, as is our new addition, the NOVA R680E. Even our new 19″ rack PC, the NINETEEN Q670E, can be used in machine learning, provided it is equipped with a suitable graphics card.

If you have any questions about our spo-comm Mini-PCs, please do not hesitate to contact us!

What is a watchdog function?

It is an essential monitoring function that continuously monitors the operation of a system to ensure that it is running properly. If the system fails or hangs due to an error or a software or hardware problem, the device will be restarted or put into a safe state. The name “Watchdog” says it all: like a watchdog, it monitors the entire operation of the system and reacts immediately if something goes wrong.

How a watchdog works

A watchdog controller continuously monitors the system’s activities. The process works as follows:

1. Regular check: The system is checked at regular intervals to ensure that it is running properly. This can be done by receiving a “heartbeat signal” – a regular signal from the operating system or software that informs the watchdog that everything is OK.
2. Error detection: If this signal is not received within a certain time frame or an error is detected, the controller interprets this as a problem.
3. Response: The watchdog responds to this error message by restarting the system or taking another predefined action, such as activating a safe system state.

This little companion is particularly useful in areas where a system failure could have serious consequences, such as in industrial plants, medical devices or automation technology.

Why is the watchdog function important for Mini PCs?

Mini PCs – including our spo-comm computers – are particularly in demand in areas such as industrial automation, IoT (Internet of Things), machine control and media technology. These applications not only require high computing power, but also exceptionally high availability. This is where the watchdog function comes into play. It ensures that the Mini PC can be operated reliably without failures, which is crucial for the smooth running of processes.

In many cases, a system failure can lead to costly downtime or, in the worst case, cause security breaches. Especially in automated systems or in environments where people depend on the functionality of devices, the watchdog function can save lives and protect companies from major damage.

Watchdog in practice: Applications

• Industrial automation: In production lines or automated production lines in which machines and devices run around the clock, it ensures that all systems remain stable and react immediately in the event of a system error.
• IoT devices: Many IoT applications, whether in vehicles or smart cities, require constant monitoring. It ensures that these devices continue to work reliably even after a malfunction.
• Medical devices: It is also of great importance in medical devices where failures could have serious consequences. For example, the failure of a mini PC in a medical device can be rectified quickly and safely.
• Digital signage: In areas such as digital advertising or information transmission, the watchdog ensures that content is displayed on screens without interruption.

Advantages of the little helper

• Increased system stability: Continuous monitoring means that errors are detected at an early stage and the system can be restored quickly.
• Automatic troubleshooting: The watchdog function automatically takes care of troubleshooting without the user having to intervene.
• Reliability in critical applications: In many areas, such as industrial automation or healthcare, downtimes are unacceptable. The watchdog ensures that these are minimized.
• Lower maintenance costs: As the watchdog detects and rectifies errors at an early stage, less manual intervention is required. This saves time and costs for maintenance work.

An indispensable security feature for mini PCs

The watchdog function ensures reliable Mini PCs and ensures that they run stably even in demanding applications. It continuously monitors the system and ensures that errors are rectified quickly before they lead to major problems. For companies that use mini PCs in safety-critical or high-availability applications, the integration of a watchdog is therefore a valuable investment.

Curious about robust, flexible and durable Mini-PCs? Contact us and discover the variety of spo-comm Mini-PCs.