How AI-ML is changing the business landscape across the industries

How AI-ML is changing the business landscape across the industries

You must have witnessed the implication of computer vision and machine learning in various industries. Detecting, monitoring, and analyzing the data is quite a laborious task but with the help of computer vision today everything is possible. So, let’s try and understand the various roles of computer vision and AI - ML in business or numerous industries.

In today’s world, advancements in computer vision and machine learning have expanded their operation in businesses. Today AI and machine learning can be found in various industries. From Robotics technology to autonomous vehicles, there is a list of technologies that are the aftermath of computer vision and machine learning.

Let’s have a look at the numerous roles of computer vision and ml in Businesses today:

Helping in the creation of a safe workplace

Before granting someone entry to a public space, computer vision systems can determine whether they are wearing a mask and can also take their temperature. Before you enter a store, a people-counting device can let you know how busy it is. It can also assist businesses to determine when they have achieved a safe occupancy that allows for enough physical distance.

Before giving access to the job site, computer vision is also used to check if the person is wearing the proper protective gear, such as safety glasses and protective clothing. Everyone in the space can be informed and reminded of the essential safety precautions using computer vision. computer vision can also help in identifying people using image classification.

computer vision in retail store
Source: Analytics Insight

Usage of drone imagery for insurance claims

Insurance firms are collecting high-definition images of a home's roof and general footprint using drones and computer vision. Insurance firms may quickly quote and settle claims based on the information and other information about a home. Only in cases when the computer vision program is unable to resolve an insurance claim, then it must be dispatched to the adjusters. By doing this, insurance firms can drive down the value of claim revisions on straightforward cases while still giving the adjuster time to handle more challenging cases.

Inspections of highly damaged areas, hazardous places, and difficult-to-access properties can all be risk reduced with the use of drones for insurance inspections.

Remotely operated vehicles' improved data collecting results in significantly quicker claims processing, greater efficiency, and larger revenues.

drone footage based AI in insurance
Source: Nearmap

Locating defects in Rail tracks

Over 140,000 kilometers of railroad rails exist. The sector spent $260,000 on average per mile in 2018 for maintenance, finance, and upcoming requirements. Running the railway network efficiently depends on spotting maintenance concerns before they cause a disturbance on part of the 140,000 km. How can the probable flaws in the 140,000 miles of roadway be investigated and analyzed?

To visually monitor every square inch of the railway track and the track bed, the solution is to place camera systems on railway cars that are already traveling along the rails. As a result, the train infrastructure can be continuously monitored while being used.

High-speed, high-resolution images of the railways and the track base are taken using computer vision. Defects in these photos can be rated after further analysis. Later, one can go over and prioritize the most crucial initiatives.

computer vision in rail track defect
Source: Global railway review

Immunity Cell Measurement in Cancer Patients

There has been numerous research about the near-human accuracy rates that AI and computer vision can achieve when reading X-rays and MRIs. Anomalies in photos can now be "seen" by computer vision that the naked eye cannot. Therefore, even though a machine and an algorithm's average accuracy might not be higher than that of people, their field of vision is considerably broader and deeper. We will now see more than ever by utilizing computer vision to supplement the skills of medical professionals. The evolution of life has a long history. Let's just assume that every wave of technological advancement was created to address an issue or necessity from the past.

Since everyone had a computer system and desired to "digitize" their processes, desktop applications were created. This resulted in significant data duplication, consistency issues, and security issues.

deep learning in immune sysytem
Source: healthcareitnews

Restructuring the Beauty Industry

Beauty enthusiasts may quickly experiment with new makeup thanks to AI. Computer vision technology is used in augmented reality to add in-the-moment visualizations to the face. Recognizing facial traits, analyzing the data, and drawing conclusions about appearance are all made possible with the aid of computer vision.

For testing reasons, the capacity of AI-oriented computer vision to accurately assess a human face is tremendously useful, and it might even assist end users in selecting the tools and methods that would be best for them.

AI has the potential to revolutionize the creation of new formulations. Data has long been utilized to improve formulae and develop better goods. Before being sold, a perfume is typically physically examined, evaluated, and compared. Currently, data can be utilized to optimize particular fragrance ratios to produce the upcoming hit.

computer vision in beauty industry
Source: Robotics & automation news

Computer vision are now an integral part of every industry. From healthcare to beauty to even retail sectors, the world is transitioning from manual to automation with the help of Computer Vision and Machine Learning. Surely, in the upcoming years, AI will expand its implications and will bring out various new techniques that can help in achieving greater efficiency and productivity in different fields.

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