In a sector like machine vision, wherein the latest technologies are being introduced drastically, several trends concerning technology are evolving constantly. Here is an attempt to summarize some of them.
Fremont, CA: The machine vision sector has been continually undergoing changes which are quite interesting to carefully follow and analyze. These emerging technology trends have been considerably reshaping the industry. For instance, uncertainty with respect to economic conditions is expected to influence the industry. However, the impact fails to be damaging though significant. Further, hardware platforms are expected to gain significance, while conventional applications are likely to remain stable. Besides these, the industry will be experiencing several changes in accordance with some other critical trends.
As per recent researches, the machine vision solutions industry is expected to grow from being priced at 11.94 billion dollars in 2018 to 17.38 billion USD by 2023. The expected CAGR rate of growth is 7.8 percent.
Increasing Prominence of Embedded Vision
Embedded Vision is likely to remain a significant trend for the contemporary machine vision sector. The prominence of this technology is due to the applications it supports in numerous markets. Autonomous driving, consumer electronics, agriculture, distribution, and broader surveillance have been some of them.
Processing power has enhanced tremendously, and memory has turned very inexpensive. Today’s technical users possess the requisite knowledge to choose. As an example, by using a small camera, it is now possible to leverage data from the cloud from different sources. When these factors are combined with machine learning to form a single package, embedded vision is achieved.
Conventional machine vision might not be capable of competing with the contemporary embedded vision in several use cases. However, the traditional machine vision is experiencing a revolution on its own.
Completely mechanized systems which comprise of machine vision include several sensors along with motion components which permit us to accumulate data for better insights into the operational efficiency of equipment within the systems.
System integrators would continue to play the most vital role in the development of embedded vision systems. Presently, embedded vision continues to take smart cameras towards their original purpose of getting image processing video analytics in a tiny enclosure and also as near to the image sensors as possible.
The toughest challenge concerning embedded vision from a machine vision viewpoint is to design a system that is attractive to consumers with respect to both cost and function. Being capable of putting the entire range of functionalities, which consumers of machine vision landscape have historically known, into a tiny form factor with low power and low-cost device remains a tough challenge.
Embedded vision has been the most trending topic in the machine vision sector in the recent past. Several exciting possibilities of embedded vision systems continue to exist in all aspects of daily life and the commercial industry. However, it has unique importance in the machine vision space.
The U.S. economy, although, gives an impression of being robust, is expecting an impending slowdown. It is a common belief among people, and the recent stock market trends have been indicative of the same. The stock exchange sector points at a possible recession ahead, not only in the U.S. economy but also the worldwide economy.
A few of the causative factors have been recent trends such as the deteriorating effect of the fiscal stimulus, increasing the complexity of financial concerns, enhancing volatility along with trade uncertainty.
Investors who could drive strategic business decisions are turning apprehensive about the future as they must remain risk-averse. The widespread speculation regarding the likely economic slowdown has been evident in the purchase decisions and patterns made by customers.
Economic fears have impelled professionals involved in machine vision to predict stable yet less significant growth, especially in comparison with the past two years.
The year 2018 gave an excellent start to the machine vision sector in several parts of the United States. However, neighboring industries, including robotics, have experienced a decline this year. There are rumors surrounding the industry that a similar turn down may take place in the machine vision space as well.
Perhaps, the biggest economic fear is in the form of tensions with respect to tariffs and trades, which made several enterprises to move cautiously into the current year. The biggest world economies, which also are the biggest markets for machine vision-related products are currently experiencing trade issues.
Industry experts are of the opinion that despite the possibility of a potential slowdown, machine vision is strong enough to overcome its implications.
Point cloud can be termed as the set of data points within a 3D space. A better way to describe it will be, all points located on the surface of the object encompass 3D coordinates, the X, Y, and Z, which are referred to as point cloud.
Point cloud, as one of the robust 3D machine vision powered technologies, is capable of providing an exact depiction of where an object is likely to be in the given space. It is due to this reason that Point cloud has multiple applications which involve object movement tracking or object identification.
A few of these applications include scanning of construction sites, mapping utility infrastructure, and scanning construction sites, besides many others. These applications have several uses even with respect to tackling real-world concerns, including repairs, urban planning, natural disaster management, and so on.
This is an emerging trend in the machine vision industry for the current year. The next-gen modular hyperspectral systems for imaging are capable of providing analysis of chemical material properties with respect to industrial environments. It is easy to visualize a material’s molecular structure with different colors in the consequential images. As a result, the chemical composition can be analyzed quickly with standard machine vision software.
This imaging technology is finding increased applicability in detecting plastic in meat and also in identifying various recyclable materials besides many others. What makes this technology a hot trend for the year 2019 are factors including better algorithms, on camera calibration, and the emergence of faster procedures.