Since the project aimed at setting up an environment where a deep-learning algorithm can detect household waste items in real time, I deployed YOLO on multiple EC2 instances for different purposes: database, scheduling, and web hosting. I ran two different testing sessions with 30 different users who interacted with the web application and simultaneously sent images to the cloud. While the users uploaded images onto the web application, I checked how quickly YOLO could process these images and return predictive results. I found out that the speed was acceptable, and the inference (processing) was quick. The key takeaways that I offered are: • Deploying YOLO on multiple EC2 instances can work well for different tasks like storing data, scheduling, and hosting a web application. • With proper setup and testing, users will have good experiences with data science applications since cloud-based systems can give good performance and low latency. • Moreover, the setting-up time is not lengthy, and that helps start-up companies to quickly launch data-products live.
