RaspberryPi_for_Edge_Intelligence_i.pptx

Raspeberry pi introduction shetd

1. Raspberry Pi for Edge Intelligence

2. Overview Raspberry Pi acts as a mini-computer at the network edge. It performs local data processing and supports AI/ML workloads.

3. Role in Edge Computing Serves as a bridge between IoT devices and the cloud. Enables real-time analytics and decision-making close to the data source.

4. Machine Learning on Raspberry Pi Supports lightweight AI frameworks like TensorFlow Lite and Edge Impulse. Executes tasks such as image recognition and predictive maintenance.

5. Benefits of Edge Intelligence Reduces latency and network traffic. Improves responsiveness for time-sensitive applications. Supports offline functionality even with limited connectivity.

6. Use Cases Smart agriculture: automated irrigation based on local sensor data. Industrial IoT: detecting equipment anomalies in real-time.