What it takes to increase your revenue by up to 30% and boost ROI with computer vision.

As more companies hear about the use cases of AI success, enterprises are continually finding new and innovative ways to achieve enormous competitive advantages with AI. This trend is happening across all business verticals, including data analytics, workflow efficiency, customer relationship management, and marketing.

With the latest advancements in computer vision technology, AI is bringing new ROI opportunities to an even more comprehensive range of industries and use cases.

An increasing need for automation and optimization of workflows across various sectors, including healthcare, automotive, retail, BFSI, manufacturing, restaurants, construction, automotive transportation, and others, is expected to drive the adoption of computer vision technology. Implementing technologies such as edge computing, artificial intelligence (AI), the Internet of Things (IoT), and automation machine learning, among others, is also expected to drive the deployment of computer vision technology over the coming years.

Here is an in-depth examination of computer vision and the ROI opportunities in different industries, specifically retail, manufacturing, restaurants, healthcare, construction, transportation, oil, and gas. Also, it will provide some examples of how business is applying computer vision in their industries to save on operational cost, boost customer satisfaction levels, keep workers safe, and achieve better healthcare outcomes.

What is Computer Vision?

Computer vision is a field of artificial intelligence that trains computers to interpret and understand the visual world. The systems learn to see and perform visual tasks that are used to require human sight. When we, as humans, look at images, we can tell what’s in the pictures. When a computer looks at these images, it only sees pixels, each with a different number value that identifies the shade of color. In this respect, the field of computer vision involves teaching a computer to derive meaningful information from those pixels; something humans do naturally.

Using digital images from cameras or videos with deep learning models, machines can accurately identify and classify objects and then react to what it sees. These visual AI systems can perform various tasks that require visual analysis, monitoring, interpretation, and expert-level decision-making. Businesses are deploying this technology to accomplish several studies that used to require human laborers. Moreover, these computer systems can perform their tasks at lower costs with incredible speeds and much higher accuracy. ?

How Does Computer Vision Work?

The latest computer vision technologies offer unparalleled speed, accuracy, and flexibility to apply to various use cases. They are based in the cloud or on-prem. Both systems can rapidly ingest visual information, train AI and machine learning models, and test their success. Computer vision works in three basic steps.?An image with a frame grabber, even large sets, can be acquired in real-time through video, photos, or 3D technology for analysis.?Processing the images?deep learning models automate much of this process, but the models are often trained by being fed thousands of labeled photos or pre-identified images. If you have quality images from the camera being used, you don’t need as much data; this is called DATA CENTRIC.?Understanding the pictures?is the final interpretative step, where an object is identified or classified.

Today’s AI systems can go a step further and take actions based on an understanding of images. Computer vision tools are used in different ways:

• Image Segmentation?partitions an image into multiple regions or pieces to be examined separately.
• Object Detection?identifies a specific object in an image. Advanced object detection recognizes many things in a single vision: a football field, an offensive player, a defensive player, a ball, and so on. These models use an X and Y coordinate to create a bounding box and identify everything inside the box.
• Deep Sort?tracks are based on distance, velocity, and what that object looks like. Deep sort allows us to add a feature by in-depth computing features for every bounding box and using similarity between deep elements to factor into tracking.
• Facial Recognition?is an advanced type of object detection that not only recognizes a human face in an image but identifies a specific individual and emotion.
• Edge Detection?is a technique used to identify an object outside the edge or landscape to determine better what is in the image.
• Pattern Detection?recognizes images' repeated shapes, colors, and other visual indicators.
• Image Classification?groups image into different categories.
• Feature Matching?is a type of pattern detection that matches similarities in images to help classify them.
• Pose Position?technique that predicts and tracks the location of a person’s objects.
• Action Recognition?Video Classification?produces a relevant label to the video given its frames.
• Measuring?a part or getting distance, speeds, etc.
• Re-identification?retrieves an object of interest across multiple non-overlapping cameras.
• Geospatial Analytics leverages geographic information, spatial data, location data, and, increasingly, high-resolution imagery.

The General ROI Benefits of Computer Vision for Workers and Organizations Risk

Regarding general ROI benefits, the possibilities for implementing computer vision are endless and span from operations to consumer experiences. Computer vision can eliminate errors, inefficiencies, and other negative consequences from repetitive, visual job responsibilities. Adding these additional tools assist human labor in completing these activities and save time and money.

Computer vision offers the following advantages compared to human workers doing similar tasks.

• Speeds up workflows and performs more tasks within the same period.
• Achieves greater consistency and efficiency in visual inspections, resulting in fewer inspection errors.
• Relieves organizations of labor burdens, allowing employees to achieve more in less time.
• Automates repetitive, visually demanding tasks.
• Facilitates rapid scaling of visual task performance without hiring and training additional employees.
• Augments the ability of human workers to perform their tasks more successfully, efficiently, and productively.
• Dramatically reduces labor costs as it performs the same tasks for less money.
• Reduces the risk of injury and sickness by more efficiently identifying risks such as traffic flow inefficiencies that cause onsite collisions, slip-and-fall dangers that cause workplace injuries, office space density, and construction job site dangers.

Additional ROI benefits of computer vision are that AI systems do not suffer from boredom and burnout. By comparison, the longer human workers focus on mundane tasks, the more distracted and error-prone they become. Research demonstrates that work-related boredom results in the following harmful adverse for workers and the businesses that employ them:

• Less effort from employees
• Reduced performance.
• Greater chances of errors and mistakes
• Increased job dissatisfaction
• Rise in absenteeism
• More instances of employee turnover
• Increases in counterproductive work behavior.
• Greater chances of work injuries

In summary, computer vision technology allows organizations to perform visual tasks requiring analysis, monitoring, and inspection with or without human labor. This offers considerable ROI benefits by saving money on operational costs, boosting the quality and success of task performance, and reducing safety risks.

Before starting your following proof of concept, “POC,” select the correct types of hardware; otherwise, your POC may not be what you want. Testing on videos from YouTube doesn’t give you what you are seeing in an environment where you may not have control over lighting, etc. When using a prebuilt AI model, research what data was used along with the camera angles, etc. If you need help, reach out.

By Tim Goebel

1. Introduction to computer vision Technology

• What is Computer Vision?
• How Does Computer Vision Work?
• General ROI Benefits of Computer Vision for Workers and Organizations.

2. The ROI of Computer Vision in Specific Industries Future Articles coming soon

• Manufacturing Industry
• Construction Industry
• Retail Industry
• Fast Food Industry
• Healthcare Industry
• Transportation Industry
• Oil and Gas Industry

3. Final Thoughts on ROI For Computer Vision