AI technology has changed the trajectory of the evolution of technology. A growing number of organizations are using tools like ChatGPT to streamline their research and development processes. There are currently around 100 million ChatGPT users and that figure is likely to grow as more startups discover the benefits it offers.
Software developers are among the professionals that rely most heavily on ChatGPT. A growing number of them are starting to use it to develop embedded systems.
What Is Embedded Software?
We will discuss some of the advantages of using AI for embedded software development shortly. However, first, it is important to understand the concept of embedded software.
Embedded software is computer code specifically written to operate a device or system (other than a computer). It’s designed to be used on something like an electronic circuit board, microprocessor, or other dedicated hardware.
Unlike general-purpose software (like Windows or Android), or software products or apps, embedded software is built for particular functions and is tailored to their target systems. It’s the “brain” of its device; without embedded software, the device would be practically useless.
When the first embedded system was created more than 50 years ago, it was revolutionary. It allowed us to make technology smaller and more efficient than ever before. Without embedded software development, we wouldn’t have the connected world we have today. It’s around us at every turn, including Internet of Things (IoT) devices, smartphones, and just about every other piece of technology you can think of. It plays a huge role in the progression of AI technology.
However, building embedded software isn’t simple by any means. It requires a deep understanding of hardware and software engineering and the ability to develop code tailored for specific applications. Several steps are involved in embedded software development. In this article, we’ll explore their ins and outs.
What Are Some of the Benefits of Using AI for Embedded Software Development?
Earlier this year, embedded software consultant Jacob Beningo wrote an insightful article on the future of embedded AI software. Beningo mentioned a number of ways that AI technology is changing the state of embedded systems. Advances in AI systems such as ChatGPT are further accelerating these changes.
Here are three of the biggest ways that ChatGPT and other AI platforms are transforming the state of embedded systems:
- Using AI pair programming to accelerate software development
- Using machine learning models to debug code more quickly
- Leveraging AI systems to help developers find solutions more quickly
There is no denying the fact that AI is rapidly changing the future of embedded software development. More developers are likely to take advantage of it due to easier access to tools like ChatGPT.
Examples of the Benefits of Using AI to Develop Embedded Software
There are a number of huge reasons to consider leveraging AI technology to create embedded software. After all, the range of options is nearly limitless.
Perhaps the easiest-to-understand example of an embedded system is the calculator. It uses a microcontroller to interpret keystrokes and provide the correct output. Another basic example is the TV remote, which uses an embedded system to control the TV.
AI technology isn’t necessary to develop these types of simple embedded systems. However, there are a lot of more complex embedded software applications that rely more heavily on AI.
The code is written in such a way that it can recognize the different buttons and associate pressing them with a specified on-screen reaction. Simpler embedded systems like the above are often called firmware. These days, embedded software development typically refers to more complex systems, such as, but not limited to:
- Automotive systems, including dashboard displays and engine control systems
- Connected cars and semi-autonomous vehicles
- Medical equipment like pacemakers or MRI machines
- Smart home appliances like voice assistants, security cameras, and connected thermostats
- Aerospace systems, including navigation systems and autopilot capabilities
- Fitness trackers that collect data about your heartbeat and bodily functions
The ubiquity of embedded software in modern life is hard to overestimate. By 2029, it will be a $24.83 billion industry.
There are many reasons that AI can help with the development of these systems. One of the biggest advantages is that AI can help create low code software. AI has also improved the quality of DevOps tools that make software development easier.
The defining characteristic of embedded software is its reliance on hardware and software components. It also has an operating system which controls the entire system.
The most significant element of the hardware within embedded software is the user interface; the set of actions, features, and buttons that control the device. This includes buttons, touchscreens, and voice recognition systems. The user interface is connected to the processor, which contains a set of instructions for executing code. It also has memory (RAM or ROM), which stores bits of information while the code is being executed.
It also has a power supply (either a battery or plug-in power) and a clock system, which controls the speed of the code execution. For example, a smart lighting system might have a timer that turns off a light after it senses a lack of movement for five minutes. Modern embedded systems usually have a communication port as well. USB ports are the most common, allowing users to update the software or data exchange.
Embedded software can be written in any language, although C/C++ are the most common. C and C++ are great languages for developing data and AI applications, so it makes sense that they are great for developing embedded systems.
The code is often compiled for a specific processor or microcontroller architecture so that it runs efficiently and accurately on its target system.
The software is also tailored to its environment. For example, a pacemaker would need completely different code than a washing machine. It must be written in such a way that it can handle real-world situations and data accurately. This requires extensive testing before the software can be deployed.
An embedded operating system is the “glue” that holds all of these components together. It provides an interface between the hardware resources and software applications. There are two main types:
- Real-time OS (RTOS): designed for systems with strict timing requirements, such as automotive or aerospace applications
- Non-real-time OS (nRTOS): designed for systems with less-stringent timing requirements, such as smartphones and connected home appliances
The choice of an embedded operating system will depend on the application’s needs. For example, a safety-critical system (like a car) should use an RTOS, while a home appliance can get away with an nRTOS.
Software engineers building embedded systems need a variety of tools, from development environments and compilers to debugging tools and documentation.
A development environment (or IDE) is the main tool for writing code for embedded systems. It includes features like syntax highlighting, code completion, and integrated debugging. Popular options include Atmel Studio, Eclipse, Visual Studio Code, and Keil MDK.
A compiler is a program that translates the source code written in an IDE into machine-readable instructions. It converts the code from one language (like C++) to another (like assembly). Popular compilers include GCC, Clang, and LLVM. An assembler, on the other hand, translates assembly code into machine instructions. This is needed for the processor to understand and execute the code.
Debugging tools are essential for debugging embedded systems. They allow software engineers to detect errors in their code, identify possible solutions, and test them out before deployment. Popular debuggers include RealView Debugger and GDB. Simulators are also useful for testing the system in a safe environment.
A linker combines the code pieces written in the IDE and compiles them into a single file. It also adds any libraries or external functions that the code needs to run.
An emulator mimics the behavior of a real device, allowing software engineers to test their code without having access to the actual hardware. It can also be used for debugging, user experience testing, and simulating new features before releasing them.
Developers must keep track of changes they make, so documentation is essential for embedded software development. Changelogs, test reports, technical specifications, design documents, and user manuals are all key pieces of documentation.
AI Technology Has Significantly Improved Embedded Software Development
Embedded software development isn’t without its challenges — mostly connected to safety, stability, and security. Still, it’s at the core of every modern devices, from connected cars to medical equipment. And AI technology is making it better than ever!
With the right AI tools, hardware components, and software development processes in place, embedded developers can create highly effective applications that revolutionize how we live and work.