AI is a prominent fixture in Hollywood films as producers attempt to make movies futuristic. But AI is not a thing of the future as we already use it. It is, in fact, making considerable contributions across multiple industries, including engineering. In this post, we’ll look at the different engineering applications of artificial intelligence.

AI in Engineering: Applications

Many scientists are fascinated with the idea of developing a machine that can mimic the human brain. Artificial neural networks, brain-computer interfaces, and transhumanism all try to replicate the human brain’s complexity. But many do realize that it’s not that simple.

However, we can’t discount the fact that while we are still far from bringing this complexity to a machine, AI is significantly making our lives easier. In fact, it has already become a vital part of engineering.

Let’s take a closer look at some engineering applications of artificial intelligence.

Application 1: Advanced Robots

The growth of AI allowed developers to create machines that can carry out complex manufacturing tasks. The goal is to develop systems that can learn and improve without the need for human intervention. As manufacturing needs continue to expand, we foresee a more significant demand for advanced robots that can replace humans in an assembly line.

An example is the use of advanced robots in the automobile manufacturing sector. AI systems have evolved from doing simple tasks to performing precise and complex processes that mimic the intricate functions that were initially reserved for human workers.

Application 2: Big Data

All industries now rely heavily on data. Information has become a hot commodity that many organizations who want to beat the competition invest in. But no data would be useful without AI systems that allow users to collect, analyze, and give it context. AI, through machine learning (ML), can provide organizations with algorithms capable of detecting mistakes and formulating solutions to improve their operations.

Engineers can use big data and AI to facilitate large-scale urban projects. The technology can help them identify where people are and what public infrastructure projects they can carry out to address general issues. Engineers can also use big data to analyze how their projects are performing and if these can be replicated in other areas.

Application 3: Internet of Things

The Internet of Things (IoT) has exploded in the past decade, as many organizations continuously work to get everyone connected. Smart devices have become prevalent, allowing people to remain in touch wherever they may be. Connectivity has benefited the engineering industry as well, as IoT devices make it possible for specialists to monitor projects remotely.

For instance, an engineer can use IoT sensors to monitor how well a system he/she designed measures soil consolidation, degradation, and environmental impact for the client. By enabling ML on IoT devices, it is then possible to achieve “connected intelligence” that would allow engineers to do predictive, prescriptive, and adaptive analyses for their projects.

Application 4: Image Processing

While the image processing component of AI may not have that much of an impact on engineering, it can potentially change practices to a high degree. Through image processing algorithms, engineers can readily identify structural deformities and other potential issues that may not be readily identifiable with the naked eye. These engineering applications of artificial intelligence are crucial to ensure the safety of workers on a project.

When combined with other data from sensors, image processing can give contextual information that would aid engineers in decision-making. For instance, a construction site’s structural integrity can be assessed with the help of AI before construction begins.

Application 5: Natural Language Processing

Another AI concept that can help engineers is natural language processing (NLP), which allows machines and humans to communicate. Imagine an engineer talking to a tool to get the latter’s input on how to reinforce an assembly line process in real-time. While this is still a concept, it can be an area worth looking into.

The engineering applications of artificial intelligence featured in this post show us that evolution is not something to be scared of. Technology, when used appropriately, can bring about positive outcomes.