Applications of Edge AI in this Era

Edge computing has been a popular idea since phones and even portable calculators became a thing. This technological advancement brought us into direct contact with computers and computers were no longer as large and clumsy as they used to be in the early 20th century. They became easier to use. At the time this technology was a marvel. However, as we continued to evolve, this once adequate technology became grossly inadequate as the need for real-time computing arose and AI stood at the forefront in bringing this innovation. There onwards the applications of edge AI widened.

Edge AI comes to be when edge computing meets AI. It is a transformative merge of both worlds. AI’s technology is one no one deserves to be left out of. To carry everyone along, edge AI came to being, and as predicted, it has greatly increased how we use and interact with AI. With edge AI, artificial intelligence algorithms can now fit into our pockets. Developers can fix broken codes on their train rides or while getting coffee.

The applications of edge AI are numerous as it cuts across various industries. The most important thing to look forward to in this article is to learn how you can use edge AI to improve your day-to-day. The uses of edge AI are not far-fetched. Later in this article, you will also see that with edge AI, it’s all about getting real-time results, predicting weather patterns, and traffic, and optimizing your day for a seamless and stress-free flow.
Let’s dive into the details.

What is edge AI?

Edge AI is the technology where artificial intelligence algorithms are fitted into smart, portable devices at the edge of the network. Traditional AI relies heavily on a centralized cloud server. Contrary to traditional AI, edge AI is optimized for processing data directly on the edge device, like your mobile device.

By doing so, it puts AI directly into the hands of users where their data is safer. However, data privacy is not the only beneficial aspect of edge AI. It is also highly beneficial for applications that require real-time decision-making and problem-solving.
There are a lot of benefits to edge AI, and most of them are covered in this ARTICLE.

Real-world applications of edge AI

Edge AI runs artificial intelligence algorithms directly on edge devices such as smartphones or Internet of Things (IoT) sensors. There is no cloud reliance on edge AI and this mediates the problem of data privacy. With these benefits, many sectors have seen its immense importance and adopted it. Here are some of the applications of edge AI in our world today.

Applications of Edge AI

Powering smart cities and transportation

Urban areas are known for their dense population. The dense population is reflected in the traffic congestion during rush hour, and sometimes all the time. Eventually, the situation gets out of hand so much that individuals cannot control this problem by themselves. This is where edge AI steps in.

Edge AI helps to create a system where there is real-time monitoring and control of traffic even with the density of the population. Incorporating edge AI, traffic movement can be optimized better. Imagine a situation where there is a potential for traffic congestion, edge AI can work on traffic lights to work based on the situation of traffic to reduce decongestion and make commute times more reliable. With edge AI you know how much time you need, to get to where you are going.

Manufacturing

Edge AI is ensuring that manufacturers produce the best products that are up to standard and safe for human use. It does this by monitoring the efficacy of a product and predicting potential failures in that product even before they occur. This way, manufacturers know the strengths and weaknesses of their products and improve on these weaknesses to make their products more suitable to use.

Also, edge AI models can detect errors or anomalies in products and alert the maintenance teams to take proactive action. These systems analyze physical flaws such as scratches or dents during inspection. In helping manufacturers achieve a higher level of accuracy, and competence than their competitors they put together a good client base of satisfied clients.

Healthcare

Wearables that measure our calorie levels, blood pressure, and heart rate all in real time are some examples of the applications of edge AI in our world today. Edge AI is not just in our wearables. In the hospital system, portable devices equipped with edge AI can scan images and make medical analyses of X-rays, MRIs, CTs scans to enable the physician to make diagnoses faster. Everyone hates the long waiting times at hospitals and if we are being honest, hospitals are not that pleasant to be at. With this revolution, patient waiting time at the hospital is reduced by a significant percentage.

In addition, edge AI helps foster scientific advancements in medicine. Even now, tools like Openfabric genome generator are making a remarkable drift in the way patients’ symptoms are analyzed. It gives the physicians the ability to analyze the patient’s problems from the foundation – the gene.

Challenges in the application of edge AI

Although edge AI is a transformative innovation in technology and AI, there are still some bottlenecks often encountered. Unless these challenges are fully addressed, the application of edge AI will always fall short of some of our expectations.

• Limited resources
  Running edge AI is not an easy task. It is not just physical, it also requires a lot of resources to put it all together. The hardware and software components of this AI model are expensive and may not be affordable for some startups. These components are necessary for the development and deployment of edge AI.
• Lack of power
  Edge AI runs on a lot of power. Power for edge AI is often supplied by batteries. Most of the time, these batteries wear down after a while. To fix this, energy-efficient algorithms and dynamic power management are needed. However, even with these energy-efficient mediums, performance must remain top-notch.
• Data privacy concerns
  Edge AI processes tons of sensitive data. As such, comprehensive security measures should be in place to protect users’ data, earn their trust, and prevent data breaches.

Conclusion

Edge AI brings us a new and fresh perspective on how we view AI and use it. It puts the power of computation supported by vast amounts of data in our hands, pushing the boundary of innovation. However, we believe that this is not the end but just the beginning as we hope to see more edge AI everywhere we go.

No more cloud AI. We now have direct access to AI with real-time decisions just a grasp away.

That is not all about AI. Visit our WEBSITE today to know more!