AI solutions have already been implemented across industries, helping to increase efficiency, reduce costs, improve safety, and more. New advancements in edge AI processing are now enabling companies to take AI applications to the next level with multiple large, complex deep neural networks (DNNs). Analog compute-in-memory is a revolutionary new approach that is bringing incredible performance, power, and cost advantages to the edge AI industry. Here are predictions for three key markets that will be reshaped by this new approach to edge AI processing.
Markets to Be Affected by Edge AI
#1: Video Security
AI is starting to completely transform the market for video security, which includes measures to deny unauthorized access and protect personnel/property. In the retail space, edge AI applications can use computer vision to protect people’s safety and assist with loss prevention in more efficient and cost-effective ways. For example, security cameras can monitor a store and use algorithms designed to detect shoplifting in real-time, while also sending notifications to law enforcement when necessary. Security cameras with AI capabilities can also provide businesses with an accurate count of how many customers are present at any given time and where customers are located; this can help businesses better understand customers’ shopping habits, in addition to helping stores to limit the number of people in a space to ensure public safety.
There is also significant demand to implement more edge AI applications in high-traffic public spaces. Security cameras with AI processing can help to monitor for a wide variety of threats – this could be an unattended item left in an airport, someone getting too close to the tracks in a train station, or a physical altercation happening in a public square. Similarly, edge AI applications can be used to monitor traffic which can help cities better understand traffic flow and utilize the best routes in emergencies.
One of the biggest advantages of edge AI processing is not only its speed – which is able to process information instantly – but that edge AI applications can also help protect people’s privacy. Edge AI security applications can be configured to only send the metadata of security incidents to the command center, helping to alleviate privacy concerns about people being monitored.
#2: Industrial Automation
Edge AI applications are helping to improve factories through increasing quality, improving workplace safety, and increasing overall efficiency. Robots with computer vision can inspect products on the assembly line in real-time for quality control, instantly detecting if there is a defect so damaged goods don’t get shipped out. These types of computer vision applications can also help to decrease waste and catch issues before they become bigger problems.
There is also a growing demand for robots to work alongside humans. These robots will require advanced edge AI processing to autonomously navigate and ensure they don’t get in the way of their human counterparts. The advantage of these highly intelligent robots is that they can do dangerous and strenuous tasks, improving workplace safety, while also being extremely efficient to boost a factory’s overall productivity.
Autonomous robots can also gather real-time data about a facility. The robots can be programmed to identify when levels of different products are running low so they can be restocked, or if machines in a facility are damaged.
Drones are another key market that will be transformed by image recognition, object detection, tracking, and other useful capabilities enabled by edge AI processing. Drones equipped with predictive maintenance algorithms can help inspect infrastructure to determine where and when repairs need to be done and help catch issues before there is a system failure.
Drones can also be used in environmental applications, such as inspecting coastlines for erosion or monitoring for forest fires. Additionally, drones help farmers monitor their fields to look for crop damage, monitor livestock, and provide real-time insights on crop growth, irrigation, and more. These capabilities can enable the agriculture industry to improve efficiency, increase yields and reduce costs.
Another interesting use case is how drones can leverage object recognition and tracking to help locate people during recovery efforts after natural disasters.
Looking Forward with Edge AI
These three markets do not even begin to scratch the surface of the edge AI revolution. Edge AI is becoming increasingly popular for consumer electronics, healthcare, transportation, and AR/VR applications. Simply take a look at all the buzz around the metaverse. Thanks to advancements like analog compute-in-memory, edge AI applications can help companies significantly boost efficiency, increase capabilities, reduce deployment time, and much more with real-time analytics, all in a cost-efficient manner.