Over the past few years the need to drive faster, smarter and agile applications have been a hot topic for both D2C & B2B companies across different industries. While cloud computing has been a central part of Artificial Intelligence for the past few years in delivering this experience, there are challenges that trades-off some of the key components that have become quintessential in today’s market needs. Some of them include faster responses, utmost security, operational costs, etc.
Check out our article – ‘How Edge AI is addressing the key challenges of Cloud Computing’
In the near future, the ability to deliver customer experience will be driven by how well companies can build applications and devices that are fast, secure and cost-effective. This race to deliver the edge has already led a lot of companies to reinvent and innovate their products. Hence the birth of Edge AI.
Edge AI is a system that uses Machine Learning algorithms to process data generated by a hardware device at the local level. This enables the device to process data and make decisions in real time, in a matter of milliseconds without even having an internet connection.
So in a nutshell, Edge AI takes the data and processing to the closest point of interaction with the user, whether it is a computer, an IoT device or an Edge server to deliver faster and swifter responses by cutting down the time involved in processing the data in the cloud and again sending the response back to the device.
Interesting Read – ‘Edge AI – Harness the true potential of Artificial Intelligence (AI)’
How Edge AI is bringing agility to applications across industries?
With the availability of the internet globally, various companies from different industries are looking to increase automation that can improve their processes, efficiency and security.
Today, almost all businesses and devices have functions that can benefit from Edge AI. It can be a retail store, factory, hospital or devices all around us, like traffic lights, autonomous machines and phones, Edge AI can transform the experience and deliver better outcomes.
A good example of how effective Edge AI is smart speakers. We can look at how Google Home or Alexa works. They are built to store words and answers locally. Even without being connected to the internet, they can provide answers to questions asked by users from the data stored in the device itself thereby completing the whole function locally.
While the advancements in technology, consumer demand and the competition to drive innovation favour Edge AI, it is still an evolving technology. In this article, we will discuss the top 6 implementations of Edge AI across different industries in the real world today.
Edge AI Applications For Different Industries
Edge AI is set to be the cornerstone across various Industries to deliver better outcomes and agility. Some of them include –
1) Shopping Experience In Retail
A positive, well-crafted customer experience is very important for businesses today to stay ahead of the competition. This not only enables them to sell smarter, better and faster but also provides a way to better retention and loyalty. This can be achieved through having a deeper understanding of usage patterns, interactions and interests which are enabled by Analytics.
With the help of Edge AI, businesses can achieve:
- Ergonomic movement patterns by designing the store to improve the efficacy of the shopping experience within the store
- Customer interactions and sentiment by face recognition to understand the overall experience
- Improve employee efficiency by tracking the movement and engagement with customers using Computer Vision
- Customers’ feedback for different products using video analytics
2) Artificial Intelligence In Smart Factories
Manufacturers and factories today back on precision manufacturing to keep their products accurate, protected and secure. Safer and efficient operations on a daily basis are the answers to achieving a holistic outcome for smart factories. This can be enabled only when there is a real-time view across the floor, resources and operations.
With the help of Edge AI, factories and manufacturers can achieve:
- Ergonomic workflow through video analytics on the shop floor to determine resource lag times and imperfections
- Inspect the factory floor for real-time monitoring and automatic detection of accidents and mishappenings
- Quality Control of the products on the assembly line using computer vision and detection models
3) Smart Roads
Smart roads are a hot topic in the transportation industry. Many countries and governments are vested in building roads that are smart and connected. The array of applications when roads, vehicles, and buildings all start interacting with one another is endless. This enables a safer, more efficient road system for drivers that can be beneficial in minimizing accidents, improving security and controlling traffic.
With the help of Edge AI, smart road builders can achieve:
- Safer roads for drivers by using computer vision to detect reckless drivers on the road and taking corrective actions to tackle them
- Real-time traffic monitoring using computer vision and object detection to monitor blockages, traffic jams, etc.
- Faster response times using AI models that can detect and take remediation using Edge AI enabled cameras
4) Enabling Smart Hospitals
Operational excellence and care for patients have been a deal-breaker for many hospitals while operating with limited health professionals. The use of technology to drive better, more comprehensive healthcare has always been a part of better healthcare management in both developed and developing countries.
With the help of Edge AI, hospitals and healthcare institutions can achieve:
- Improved security of the data by locally hosting medical data while being connected to the internet
- Improve the efficiency of healthcare professionals using video analytics to determine movement patterns in the shift times
- Remote patient monitoring using computer vision to determine emergency responses even when the doctors or nurses are not around
- High precision thermal screening of patients using Edge AI enabled cameras
With 5G underway in many countries, Edge AI is the answer for many telecommunication companies to bring a whole new experience to their applications in consumer market, manufacturing and transportation offerings.
With the help of Edge AI, telecommunication companies can achieve:
- Faster flow of data by locally storing the key information and computing at the edge without relying on the cloud for every process
- Software-defined networks that can be used to automate self-checkout functions in stores and outlets
- Inventory management using video analytics in factories, stores and warehouses
6) Autonomous Vehicles
Self-driving cars are a testament to Edge AI applications. With the electric vehicles (EV) revolution happening across the world, the automotive industry is now overlooking more sophisticated and smart car applications. Edge AI can be used effectively to drive the ADAS & self-driving functions in the car which can be a revolutionary change in the industry for years to come.
With the help of Edge AI, automobile manufacturing companies can achieve:
- Faster data processing in smart cars to provide feedback to drivers instantaneously
- Self-driving and navigating features using the video analytics, radars and AI
- ADAS features using computer vision and real-time remediation to detect accidents ahead of time and respond immediately
Applications of Edge AI with time will be limitless and this change is not just necessary, but essential to tackle the challenges of cloud computing. With the advantages that Edge AI can bring in, we are only a couple of years behind in seeing it implemented across all major sectors.
The global Edge AI market is expected to grow at a compound annual growth rate of 19.27% to reach a market size of US$1,954.244 million in 2026 from US$569.194 million in 2019. ( Source: Research&Markets ).
Edge AI is not just a topic of discussion anymore but is a necessity. Many companies and organizations are already in the race to adopt Edge AI.
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