This content originally appeared on DEV Community and was authored by Nikola Perišić
Edge computing is a distributed computing model that brings computation and data storage closer to the sources of data.
Now let’s explore it through an example 🙂
Smart cameras & face recognition – The superheroes of security
Let’s talk about one of the coolest real-life uses of edge computing – smart cameras!
In the past, security systems sent every second of footage to a central server far away for analysis. But now with edge computing, smart cameras can process video locally, right where the action is happening. 
Why does that matter?
This means these cameras can instantly detect movement
, recognize faces
, and even raise alarms
all in real-time without needing to send every single frame to the cloud.
Real-life example
Imagine a smart camera at your building’s entrance 
.
Someone unauthorized tries to sneak in. The camera sees their face, recognizes they shouldn’t be there, and BAM 
– sends an alert immediately!
No need to waste bandwidth sending hours of footage – it only uploads the important moments! Pretty awesome, right? 
Tools That Power This Magic
Raspberry Pi: This small tool is perfect for running AI applications in smart cameras!
NVIDIA Jetson Nano: Need more power? This beast is for processing video right on the device, giving you smooth, powerful video analytics and AI without needing a big fancy server.
Key Takeaways:
- Edge computing allows devices to process data locally instead of relying on cloud servers
- Smart cameras use edge computing to recognize faces, detect motion and raise alarms in real time thanks to edge computing
- Raspberry Pi and NVIDIA Jetson Nano are two great tools to power these smart devices
Thank you for reading! Do you know some other real-life examples? Write it down below 
This content originally appeared on DEV Community and was authored by Nikola Perišić