Artificial Intelligence and Computer Vision – A Match Made in Heaven?
After becoming independent in 1957, Malaysia continued as an agricultural country but quickly grew into a manufacturing nation in a relatively short time. Literally from nowhere, the manufacturing sector now commands more than 38% of the nation’s GDP overtaking the agriculture sector which commands just slightly above 7%. In addition to the multinational manufacturers who are mainly in the electrical and electronics sectors, there are also other smaller producers who produce for the rest of the world. Nevertheless in order to compete, they cannot just rely on manual labour whether local or foreign, to produce high volume and high quality goods at a competitive price. With intense competition, even the old way of making many products to satisfy the global appetite for good products from both the brick-and-mortar shops to your huge online shops is no longer adequate.
Manual operations in the manufacturing process can come in various forms, ranging from the very simple but monotonous and repetitive to the highly complex or sophisticated. In the quality department many of the local manufacturers have chosen to use human labour to ensure their quality is maintained. For many of these highly repetitive but relatively simple tasks, the human operators need to be properly trained for an appropriate length of time before they can perform effectively. Other than the intelligence of these operators, their ability to detect deviations from the desired patterns are also utilised. And this is where artificial intelligence and computer vision can help.
The term artificial intelligence was first coined at the Dartmouth Summer Research Project on Artificial Intelligence by John McCarthy in 1956. While there are many definitions, Ray Kurzweil, an American inventor and futurist defines it as machines that perform functions that require intelligence when performed by humans. On the other hand, computer vision deals with how computers can gain high-level understanding from digital images or videos. From the perspective of engineering, it seeks to understand and automate tasks that the human visual system can do. This paper shows how artificial intelligence combined with computer vision can be used to improve productivity and effectiveness in three different areas.