Michael Kim
Software Engineer
Michael makes fast, responsive, and dynamic web interfaces. He currently lives in DC Metro area and is #readytowork!
Check out some of his skills and projects here.
Michael makes fast, responsive, and dynamic web interfaces. He currently lives in DC Metro area and is #readytowork!
Check out some of his skills and projects here.
The License Plate Database ("LPDB") is a full stack web application that can recognize license plates from a live video stream and store them in a database. Commissioned by a local car wash business, LPDB tracks their customers' visits, giving the business capacity to enact customer loyalty programs (i.e. every 10th car wash free) as well as gain business analytics.
I have worked in collaboration with another engineer in this project using git / github. Docker was utilized for maintaining consistent development environment. I contributed to the front-end by designing a responsive UI using React. In the back-end, I utilized Express.js to define routes that run CRUD services to a SQLite database.
License recognition is implemented using the deep learning based automatic license recognition engine Ultimate ALPR.
A demo version is linked below for browsing. The license recognition feature is not available in the demo version, which controls the inserting of new data. But the rest of the CRUD functions are available for testing. Future updates may include a way to insert video files with license plates to allow end-to-end testing.
This ROI (Return on Investment) calculator assists customers estimate their ROI based on several interactive variables. Upon receiving a request from the sales team that such tool would be useful, I considered the business logic and ideal technology / stack to solve the problem and delivered this app.
The final product has an easy-to-use UI with dozens of data nodes properly managed using React.
