Edge AI combines two emergent technologies: edge computing and artificial intelligence (AI). Whereas edge computing stems from the same general premise, in that data is generated, collected, stored, processed, and managed from a local location rather than a remote data center, edge AI further evolves the concept to the device level, using machine learning (ML) that mimics human reasoning to reach points of user interaction, such as a computer, edge server, or Internet of Things (IoT) device. In general, these devices don’t require an Internet connection to operate and can make decisions independently
The global market for Edge Al Software is projected to grow from USD 1.1 billion in 2023 to USD 4.1 billion by 2028, at a CAGR of 30.5% during the forecast period. Edge AI software is revolutionizing industries worldwide, driven by its ability to process data in real-time, minimize latency, and bolster security. This exponential growth can be attributed to several factors, including the proliferation of IoT devices generating massive amounts of data that require real-time processing. Edge AI software effectively addresses this need by analyzing data on the edge, eliminating the need for cloud transmission. Additionally, edge AI software reduces latency by processing data closer to the source, ensuring real-time responses critical for applications such as autonomous vehicles and smart cities. Furthermore, it enhances security by isolating data on the edge, making it more resistant to unauthorized access.
Edge AI software is being adopted in the healthcare and life sciences vertical to enable smart medical facilities with digital diagnosis and remote patient monitoring. The adoption of Edge AI in healthcare is critical for both patients and healthcare providers, as it can automate tasks, enable autonomous monitoring of hospital rooms and patients, and monitor vital signs. Edge AI computing usage cases can greatly extend the range of health services, and large chip manufacturers have been investing heavily in Edge AI. Edge AI is utilized for in-hospital patient monitoring, fall detection, radiology, and anomaly and injury detection. Real-time insights and alerts can be given to operators as suspicious activity or objects are detected.
