• Mobile app should be scalable
• Multi Language support required
• It was a bit of a challenge to ensure the new environment meets all of the compliance criteria and still remain cost effective

• Achieving similar results from one camera while the same results in an actual game are received using hawk-eye technique that uses six cameras.  Achieving accurate results from the app each time was dependent on the background noise and the position of the camera and device quality.
  • We informed user if the camera quality and device was not compatible for 240FPS and slow-mo recording was not available we did not allow them to download the app. A list of supported devices was also released on the Machineroad’s site. 
• Ability to process videos recorded in different environments under different lighting conditions and pitches
  • We did Machine learning for which we trained the model in different conditions like day and night, Outdoors and indoor etc. But it was difficult for the app to pick a new location and pitch automatically if it was different from the models on which it was trained. 
• User needs to align the pitch with the camera and orientation of the camera should also be accurate else the results gets impacted.
  • Help screens were implemented to inform user on the orientation and Video tutorials were released by the client as well so users can understand how to get the best results from the app. 

• Logging in to have the same user access the store front and mobile to have one seamless experience on any device
  • We used Auth0 and Shopify APIs to authenticate the same user if it exists already on Shopify web app
• Initially we hardcoded the logic for categories on the mobile side but that would mean frequent code update and if the client needs to change something on the product or category had to come back to the development team 
  • Integrated with the shopify store to ensure that categories and product information is read from the backend and not hard coding any logic on the app side 
• Mobile App should behave same as the Shopify store front and there were some data validation logic like Coupon code, Pin code validation etc which were not working as expected
  • We integrated the same logic using APIs for all data validation hence the app behaved exactly like the web store front.  

• Getting the huge amount of data to incorporate and add to the online database, we took an online database migration tool and added AI ML logic to ensure the right data is sent to the right data view.

• Teacher training on how to mark the attendance as there were more than 200+ teachers who were onboarding around 50+ class schedules for 500+ students.