The problem Vwatch solves

Vwatch!
Now that the covid pandemic which rocked the world is coming to an end, things are returning to normalcy with the working sector being reopened again. However, home theft and robbery has been surging up to new records as the older generations as well as young kids being home alone,are getting more and more vulnerable.To solve this rising problem and provide a sense of safety to the vulnerable demographic..We,have developed a mobile application called Vwatch!

Working of Application:
Whenever a person arrives at the front door,the cctv camera installed detects their face.An old mobile is attached to the doorframe inside the house which takes the data from the cctv and using face detection tech,identifies whether the person is an insider or a stranger and notifies thorugh the app.

If its an acquaintance, then the app displays the name of the person and thus, guarantees that its a person the user is acquainted with. The user has an option to accept or deny the notification.If accepted,then the user can open the door and a notification is sent to the caretaker of the house with the details of the person.If its a stranger, then the user can simply deny the request.

Key Features of Application:
1)Safeguards the older demographic as well the young agegroup
Senior citizens , experience mental problems and are vulnerable to thefts.Vwatch would greatly benefit them to provide them safety in their own residence.Younger children generally arenaive and quite impulsive and hence, prone to crimes such as kidnapping,thus this app would be a relief to parents!

2)Promotes reusability of older smartphones,thus conserving resources
An older android compatible smartphone can be fixed on the doorframe and be used to run the application.

3)Has colourful and easy to use interface, thus enriching user experience to the fullest:
Has minimalistic buttons and bright colors used to appeal to the users which appeal to the targeted demographic and vastly enhances the user experience.

Challenges we ran into

Challenges faced :

1. Face Detection : The model we developed was relatively weak and had very little existing features.The model we customised to our needs and updated was upto the mark, more efficient and could detect faces will more accuracy and precision.
2. Apk file loading :
   We couldnt convert python file into apk file using buildozer and specs file.Loading and debugging was taking a significant amount of time.We solved this problem by changing the name of the main build directory as main.py and solved the issue
   3)Ui Difficulty.
   Ui was intensive to make, and we faced a lot of difficulties due to us being first years and having a lack of eloquent skills.
   We had to research up the kivy documentation and find appropriate keywords and functions which managed functionalities well and we could write readable code in a short amount of time
   4)Our Mistakes:
   Specifications were not made crystal clear from the very beginning of the project, which led to difficulties and an ample amount of time wastage in the later parts of the project which decreased our efficiency.
   We underestimated the deployment of the project in our apk file which further more led to a lack of time as well as energy wastage.