Believe it or not, we're not breaking new ground talking about Human-Machine Systems (HMS). The current status is that we tinker with human-machine interactions in our everyday lives. It all technically started during the Industrial Revolution when people began to build tools that changed the interaction between humans and machines. Yet, the most major turning point was in the 1940s, when they made the first computers and software applications. Yes, when computers were as large as rooms or small houses.
That paved the way for more advanced technology in the industry and a new era in HMS. It became interesting when intelligent systems based on Machine Learning (ML) and Artificial Intelligence (AI) emerged. The field of HMS has a major impact on Product Development, helping provide more value and better User Experience (UX). Let's look closer at HMS and how they've influenced software products.
What are Human-Machine Systems?
The application of HMI involves designing top-notch systems that can combine and leverage the cognitive and physical abilities of users and machine capabilities to work as a single entity. The main goal is to improve productivity and performance to build better products and drive growth. Besides simplifying the process of bringing great products to life faster, HMS also aims to eliminate human mistakes. To err is human; unfortunately, errors can cost large business resources. HMS can significantly minimize the number of mistakes we make. As you can imagine, HMS extends to almost every sector. The most common application fields are Fintech, Healthcare, Aerospace, Automation, Robotics, Accounting, Transportation, and Software Development.
Design factors of an effective HMS involve human individual operator factors, like general emotional abilities, human behavior, and cognitive abilities. Physical ergonomics is also a crucial element in systems. One of the most important aspects of an HMS is the platform, allowing seamless interactions. That's why they often call these platforms Human-Machine Interface (HMI). The last piece of the puzzle is what the machine aims to achieve. That leads us to the main types of HMSs.
What are the Main Types of Human-Machine Systems?
We'd get endless categories considering all the industries that benefit from HMS. Thus, we've only picked the main four categories or types.
Think of Manual Systems as the simplest version of HMS that has been around the longest. The main characteristic of a Manual system is that the user performs most of the work with minimal assistance from the machine. While the margin of error is large and efficiency is small compared to the other types of HMS, Manual Systems gives a high control over actual performance. Real-life examples include tools used in construction or manufacturing. A practical example of IT in the IT industry would be manually tracking software licenses using physical documentation or a spreadsheet.
Here, things finally start to get interesting. Machines come much more into play in Mechanical Systems. Yet, they still require some level of human intervention to work properly. Mechanical Systems enhance human speed, strength, or reasoning to help us complete concurrent tasks faster and more easily. Think of cars, keyboards, printers, or other computing equipment, such as server racks or cooling systems.
Automated Systems fall into the more modern category, aiming to minimize user input as much as possible. When set up correctly, Automated Systems can normally work independently without supervision. Automation implies a high investment cost at the beginning, but it largely increases efficiency and productivity. A perfect example is Automated Teller Machines (ATMs) in banking or robots in manufacturing plants. Automated Systems can automate complex tasks like monitoring, processing models, writing documentation, and deployment in Software Development.
Here, we have the most advanced type of system. Cyber-physical systems bridge the gap between the digital and physical worlds, allowing for real-time monitoring and analysis. They involve feedback loops where networks affect processes and vice versa. These systems commonly use sensors to collect data from the "real world" and computational algorithms to make decisions based on that data. The best example is the Internet of Things (IoT) devices, including Smart Cities, navigational systems, advanced driver assistance systems, and air traffic management systems.
How Do Human-Machine Systems Work?
The first step to understanding how Human Machine Interface Systems work is learning their components. The simplest model of a HMS includes a human user (or human operator agent), a machine, a system environment, inputs, outputs, interfaces, feedback, and mechanisms. The system normally receives inputs from the user and executes an action or output based on that input. That creates a feedback loop, allowing users to adjust their inputs based on results. Advanced systems may include some autonomy, enabling them to make decisions and act independently. It's important to note that the user has complete control over the machine. That means users can override the machine's actions when needed.
On the other hand, developing a Human-Machine Interface involves a deep understanding of User Experience (UX) design. That often extends to human interaction, cognitive sciences, behavior, mental models, cognitive ergonomics, human systems, and affective sciences. This way, developers can build stellar systems with intuitive User Interfaces (UI) to interact with machines. Numerous examples of advances in sensing technology include keyboards, dashboard displays, touch screens, and gesture-based interface machines. Developing advanced systems requires high-level programming languages like Rust, Java, C#, and C/C++. If the system requirements include AI or ML solutions, Python could also be a great choice.
Why are Human-Machine Systems so Important?
Almost every sector has used HMS to increase productivity, efficiency, and organizational interactions. Systems that allow users to leverage the power of machines help avoid repetitive tasks, giving us more time to focus on decision-making and creative problem-solving. The ability of HMS has allowed us to unlock levels of innovation and progress.
The synergy and collaboration of users and machines have constantly redefined the boundaries of what we can achieve. That all translates into more growth and better graphical User Interfaces for users and developers. We owe systems the most of the digital tools we take for granted. Devices that allow us to live way more comfortably and, in some cases, even save lives. That's how important Human-Machine Systems and Machine System Modeling are for us.
Human-machine models play a major role in Software Reliability models, Zero-Parameter models, and the Engineering Design process. That involves UI/UX Design, Front-End and Back-End Development, DevOps, and Product Management. Digital products, physical equipment, companion technologies, aesthetic applications, and task analysis tools built with Human-Machine Systems help us provide better quality products and reduce the likelihood of errors in complex environments.
They allow developers and digital agencies to promote adaptive performance with more value, boosting satisfaction, engagement, and task analysis while creating accessible User Interfaces. As mentioned, they also help human users work and live way more comfortably. For all these reasons, at Capicua, we acknowledge the importance of HMS for achieving technological improvements and boosting User Satisfaction.