Intelligent systems are revolutionizing a variety of industries, including transportation and logistics, security, and manufacturing. They help improve energy efficiency, quality, and flexibility of these systems. Intelligent systems are complex and use a wide range of technologies – artificial intelligence, cybersecurity, natural language processing, deep learning, embedded CPUs, distributed storage, wireless networking and graphical signaling.
“From a computer science perspective, that’s what’s so fascinating to me about this technology. It really incorporates everything we do as computer scientists,” said Dr. Ray Klump, Professor and Chair of Computer Science at Lewis University. “Intelligent systems has everything, which makes it such a rich subject to study.”
Intelligent Systems and Real-World Applications
Intelligent systems are a computer-based approach to decision making. Notably, they are used in autonomous transportation systems and interact with the world in a way that helps humans get from point A to point B safely.
Volvo Autonomous Cars
“Even some not-so-highly-priced cars can now sense that there is an impending collision about to happen or there’s somebody in your blind spot. The cars’ cameras use computer vision by taking in the scene,” says Dr. Klump. “And as it processes all these images of its environment, the system pieces them together to detect whether a collision is about to occur.”
Another application of intelligent systems is making technology more energy efficient. For example, machine learning can take advantage of energy usage data, the weather and room occupancy to more efficiently heat and cool homes. Overall, these systems minimize wasted energy, while keeping homes more comfortable.
Today's electrical grid has thousands of smart devices routing electricity to your home. By measuring voltages and currents, these systems identify problematic conditions and collaborate with nearby intelligent systems to determine the best course of action to take to keep the lights on.
The Smart Grid
Artificial Intelligence and Machine Learning
Intelligent systems use artificial intelligence and machine learning. This helps machines to “learn” in much the same way humans do. This is now possible because of ubiquitous data in the modern world, including the ability to store it and communicate it at high speeds.
“AI systems have been around for 60 to 70 years already, which is pretty amazing, and for much of its history it was something that only science fiction writers and their fans would talk about,” Dr. Klump said. However, only recently have major breakthroughs occurred. “The ready availability of data, and lots of it, has really helped AI finally achieved some of the outcomes that early AI proponents and dreamers thought were possible.”
With machine learning, computers take in data and train themselves based on that data. They run tests to ensure they are interpreting the data correctly. They then pass it through classification algorithms to figure out what in the current situation is familiar and what is less well known. After the computer’s algorithms have been trained to make the right decisions, they can use this decision-making ability to perform tasks.
Cybersecurity is a necessary component of intelligent systems as well. If a machine is fed data that trains a computer to make the wrong decisions, it could endanger lives. This means security is interwoven at every step of the creation of intelligent systems and applications. It is critical to their operation.
The Field of Computer Science
As a dynamic and exciting aspect of computer science, intelligent systems utilizes all the tools and skills available to computer scientists. They can help make our world a safer, more efficient and eco-friendly place, from home thermostats to trans-Pacific shipping routes.