Artificial intelligence (AI) might feel far away, but many of us experience AI every single day in applications like speech to text virtual assistance or fingerprint recognition on smartphones. AI capabilities in IoT applications help to identify patterns and detect variations in IoT edge devices carrying sensors for environmental parameters like temperature or pressure.
Traditionally, simple embedded edge devices collect this data from sensors in the application environment and stream the data to AI systems built on cloud infrastructures to perform analytics and draw inferences. Yet, as the need for real-time decision making in IoT implementations grows, so do connectivity or processing needs—and it is not always possible to stream all data to the cloud for AI processing. This paper from Avnet will discuss how deploying AI at the edge can improve the efficiency and cost-effectiveness of IoT implementations.
What You Will Learn
- Exploring AI in an IoT Solution
- How to Deploy Edge AI
- The Benefits of the Ege