In the past few years, computer vision has made a lot of progress, changing the way people process, analyze, and understand visual data. Computer vision is a subset of artificial intelligence (AI), which computers the ability to interpret and understand visual information from the world around them. With the rise of powerful computing systems and improved algorithms, computer vision has witnessed significant progress in recent years.
According to a report by MarketsandMarkets, the computer vision market is expected to grow from USD 10.9 billion in 2019 to USD 17.4 billion by 2024, at a CAGR of 7.8%. The report attributes this growth to the increasing demand for computer vision systems in various applications such as healthcare, automotive, and security.
Federal agencies have also recognized the potential of computer vision and have been utilizing it to improve their operations. For instance, Homeland Security has employed AI and computer vision through the Metamaterial Electronically Scanning Array (MESA) radar system, which was created by the radar technology firm Echo dyne. This system is utilized by the Customs and Border Protection Agency (CBP) to identify and signal objects of interest using AI-powered software. This, in turn, enhances situational awareness along the borders of the United States.
Now, federal agencies can not only process and analyze images but also get useful information from them. Besides defense, computer vision can be used to do many different things, like find faces in a crowd or signs of fraud.
But what if it was told that image processing is only the tip of the iceberg? This article will look at how federal agencies use AI to take computer vision to the next level, thus opening up a world of possibilities. It goes deeper into the world of computer vision and finds out how this cutting-edge technology can be used in many different ways.
With the help of AI, computer vision systems can find and identify objects much more accurately. Computer vision systems can learn to find patterns and details that a human eye might not be able to see by using algorithms for machine learning. For example, AI-powered computer vision can make it easier for customs agents to find illegal drugs or weapons in shipments. This improves border security. With AI's ability to look at a lot of visual data, it can spot small details that humans might miss. This improves the accuracy and reliability of the results.
AI can also speed up and improve the way computer vision systems work. AI algorithms can handle huge amounts of data in real-time because they can automate the process of analyzing visual data. This can help federal agencies process and look at a lot of visual data much faster than if they had to do it by hand. AI-powered computer vision can, for example, help police find and follow suspects quickly in crowded places.
Because AI algorithms can learn from a lot of data, they can be changed and scaled to fit different use cases and environments. This means that federal agencies can use computer vision systems for a wide range of tasks, like keeping the public safe and keeping an eye on the environment. For example, AI-powered computer vision can help environmental agencies keep an eye on wildlife populations or track the spread of invasive species, which is good for conservation. Because AI-powered computer vision systems can be customized, they can help the government solve complicated problems on a larger scale and with more accuracy.
Traffic management is a natural place for smart vision systems to be put to use. One of these uses is putting in place GRIDSMART's single fisheye camera, which gives a full view of intersections, including the middle where cars, people, and bikes cross. The system uses both traditional computer vision and deep neural networks to find and track all moving objects in the scene and use AI to figure out what they are. The platform gives traffic managers real-time data on traffic volumes, turns, and average speeds that can be used for analysis and to set the timing of lights at intersections. There are already 10,000 places in the United States where GRIDSMART cameras are in use.
Oil and gas, telecommunications, and power companies use Levatas to get smart cameras for drones and fixed locations. It is currently working with Florida's largest public utility to automate safety checks that otherwise take a lot of time. Drones can be set up to find leaks and other problems in hard-to-reach places, and a stationary smart camera can watch over gauges. This technology can help workers do their jobs better and keep them safer.
Fortem Technologies made the SkyDome platform to provide autonomous 3D airspace monitoring. It uses AI-assisted radar to watch for airborne obstacles when a city wants to send a drone over the horizon to check out an accident or crime scene. The system tells the operator that there is an open flight path, and the FAA gives a waiver. Fortem is working with the transport departments of 14 states right now.
Hayden AI makes a smart camera that can be put on city buses, police cars, and other vehicles. The onboard device can tell if a car is parked in a bus lane and can also tag and report cars that are parked at bus stops. The system also remembers past information to make 3D maps, which can help find a car parked in front of a fire hydrant. The camera is a 21-teraflop device that gathers evidence in 10-second packages that are sent to the cloud. Hayden AI has municipal clients in New York, California, and Washington State, and its cameras will soon be on city vehicles in Washington, D.C.
Deep learning was used by Smart Vision Works and the state of Michigan to find and get rid of invasive carp in the state's waterways. The company taught its AI system to tell the difference between carp and six or seven other species, with the end goal of making a fence-and-camera-equipped trap net. As the fish went by, they were named and put through different exit doors.
AI and computer vision can be used to improve border security by finding and identifying things like illegal drugs or weapons that could be used to harm security. Customs officials, for example, can use AI-powered systems to look through cargo containers and find any strange items. Face recognition technology can also be used at border checkpoints to make sure that travelers are who they say they are.
AI and computer vision can also be used to help people deal with disasters. For example, drones with computer vision technology can look for survivors in areas hit by disasters, and AI algorithms can help find places that need help immediately. Computer vision can also track how well recovery efforts are going and determine how much damage was done by natural disasters.
Tracking how diseases spread is an important way for public health workers to keep an eye on the spread of infectious diseases and stop them. It means collecting and analyzing information about outbreaks, like the number of cases, their location and other important details. This information is used to figure out where the outbreak started and who is at risk, as well as to make plans to stop it from spreading further.
During the COVID-19 pandemic, for example, many countries used Bluetooth or GPS to track the movements of people who might have been exposed to the virus. The name of these apps was "contact tracing." People who were close to an infected person could find out through these apps and be encouraged to get tested and stay away from other people. By quickly finding and isolating people who had the virus, health officials were able to slow its spread and stop new outbreaks.
Several federal agencies are already using AI-powered computer vision to improve their operations. Here are some examples:
Computer vision is an important tool for federal agencies because it lets them automate tasks and get useful information from visual data. But there are a few problems that make it hard for these agencies to use computer vision well.
The availability of high-quality and large amounts of data is one of the most important problems in computer vision. The amount and quality of data used to train computer vision systems is a big part of how well they work. There may not be many relevant and varied datasets that federal agencies can use to train their computer vision models.
Computer vision systems also have to deal with the problem of bias and fairness. These systems can repeat and amplify the biases in the training data that come from society. When it comes to making important decisions, federal agencies need to make sure that their computer vision systems are fair and unbiased.
AI has the potential to automate many routine tasks, giving federal workers more time to work on the important ones. AI can, for example, be used to look at a lot of data and find patterns and trends that would be hard for humans to find on their own.
AI can help federal agencies make better decisions by analyzing data and giving insights that humans might not be able to see. AI can be used, for example, to predict future trends or outcomes based on data from the past. This helps agencies make better decisions.
AI can help federal agencies get the most out of their resources by finding places where they aren't being used well or where they can be used more efficiently. AI can be used, for example, to look at how energy is used in federal buildings and find ways to use less energy and save money.
AI can help federal agencies help people better by automating processes, speeding up response times, and making the whole customer experience better. AI-powered chatbots, for example, can be used to answer people's questions right away, cutting down on wait times and making people happier.
The way we process and analyze visual data has changed because of computer vision, and advances in AI have made it possible for federal agencies to take this technology to the next level. Computer vision can now recognize objects, faces, and even emotions in real-time thanks to machine learning algorithms and deep neural networks. This makes it easier than ever for police and border guards to do their jobs.
Computer vision can help federal agencies reach their mission goals by doing things like recognizing license plates, keeping an eye on roads and surveillance, securing the border, keeping the law in place, and using virtual assistants. There's no doubt about the benefits: better accuracy, faster responses, and a better understanding of what's going on.
But some problems need to be solved with ethics and privacy. As technologies advance, it's important to think about how to use them responsibly.
Cogent Infotech helps clients deal with these complicated issues and use computer vision to its fullest potential responsibly and ethically. Those interested in learning more about how computer vision, visit our website or get in touch for a consultation