Throughout history, the biggest breakthroughs in technology have been a consequence of personalizing it to the consumer. AI is the next emerging technology, therefore a logical progression would be to tailor machine-learnt services to the user. In this same vein, we have developed proof of concept for a tool that could potentially map an owner to an object. Not only could this be used in our daily lives, but we also thought of the impact that this tool could have on visually or physically impaired individuals that would benefit from an intelligent robot using our tool.
What it does
The software analyzes a photo of an object and identifies its owner. For the proof of concept, water bottles have been used as sample objects and 3 members have been used as test owners. Ideally, users would be able to add ownership to any object.
How we built it
Challenges we ran into
In order to optimize the Custom Vision API’s precision and accuracy, we must train it by feeding it large volumes of data, which is not easily achievable under our given time constraints, and figuring out how to transition between the API and the web app implementation. In addition, the sparse documentation for the custom vision API and blob service did cause us some minor setbacks.
Accomplishments that we're proud of
Figuring out how to use the tools at our disposal in under 24 hours.
What we learned
How to use MS’s Azure Custom Vision API, the Angular Framework, RESTful services and as well as the Azure toolkit.
What's next for AIdentify
With the proper tools, we plan to upgrade this software such that we can also input videos, whose frames will be extracted and analyze by the same logic as regular photos. As mentioned earlier, we look forward to a future where we would be able to implement our AIdentify Robot. Through this opportunity we were given a chance to implement our ideas and build a good basis for forthcoming iterations. Thank you :)