One of the biggest challenges for non-AI experts is the terminology. Artificial intelligence, machine learning (ML), and computer vision (CV) are frequently discussed, but people outside of data science fields often do not know what they mean. Fortunately, it is not that complex: Artificial Intelligence, Machine Learning, and Computer Vision all generally refer to the same thing, just with more specificity. For example, if you are running a computer vision algorithm to identify solar panel defects, you are engaging in AI, ML, and CV. In contrast, if you are translating words from English to Spanish using an algorithm, that is more likely to be AI or ML, not CV. Most AI inspection projects in the solar panel industry are typically CV initiatives.

For example, if you are running a computer vision algorithm to identify solar panel defects, you are engaging in AI, ML, and CV. In contrast, if you are translating words from English to Spanish using an algorithm, that is more likely to be AI or ML, not CV. Most AI inspection projects in the solar panel industry are typically computer vision (CV) initiatives. This means that an algorithm uses images to identify solar panel defects. The use of AI and CV in solar panel inspection is relatively novel.

There are a few different ways that solar farms can deploy AI-powered inspection. The most common way is through the use of an Unmanned Aerial Vehicle (UAV) or drone. UAVs provide a non-contact way for solar farm operators to perform quality control of their solar panels using aerial imagery. Images collected by a UAV over a solar farm can be processed by an algorithm either in the cloud or on-device. The results of the AI algorithm will tell the quality controller which PV panels have visible signs of defective equipment. To speed up the inspection process and improve accuracy, solar farm operators are turning to AI-powered inspection. This involves the use of deep learning algorithms that can automatically detect solar panel defects from images. Deep learning algorithms are a type of machine learning algorithm that uses a neural network to learn how to solve a task. Neural networks are composed of interconnected layers that can learn how to recognize solar panel defects from images.

One of the biggest challenges for non-AI experts is the terminology. Artificial intelligence (AI), machine learning (ML), and computer vision (CV) are frequently discussed, but people outside of data science fields often do not know what they mean. Fortunately, it is not that complex: Artificial Intelligence, Machine Learning, and Computer Vision all generally refer to the same thing, just with more specificity. For example, if you are running a computer vision algorithm to identify solar panel defects, you are engaging in AI, ML, and CV. In contrast, if you are translating words from English to Spanish using an algorithm, that is more likely to be AI or ML, not CV.