Computer vision and Edge AI are witnessing a booming high-pitch in AI-based applications and services. To highlight even better, we see commercial potential in the use of artificial intelligence techniques; the utilization of data\ information must always take into account concerns including data security, privacy, and potential issues of bias. 

Here are some of the factors that drive computer vision movement from the realms of academia to commercial deployments include: 

1. Advancement in DL and ML frameworks 

2. Availability to load a large volume of data 

3. Cost and energy-efficient hardware 

4. The proliferation of cloud (the rapid growth of Edge technology replaced the cloud) 

Additionally, below are few main reasons why computer vision has become deployable in the Edge includes 

• Bandwidth: For better data management 

• Latency: The edge device processes data quickly and reliably for use-cases that require real-time decision making. 

• Economics: relatively cheaper compared to cloud 

• Reliability: Getting inference done within the device without the need for the cloud. 

• Privacy: lower security and privacy threats.

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