Our website supports creating a 2D grid of videos we call wall, where each video in it is a tile. Before saving a wall, we must validate it.

The client sends a list of tiles, where each tile encodes its 2D coordinate(s) (x,y) inside the wall as integers. The wall can only include 1x1 fixed sized tiles, the coordinates pair identifies the starting corners of the tile in this case. An example follows (the notation is intended to be language agnostic, it is incidentally the same as python):

[[0,0],[0,1],[1,0],[1,1]]

Which means:
- the wall has 4 tiles;
- the first tile goes from (0,0) to (1,1);
- the second tile goes from (0,1) to (1,2);
- the third tile goes from (1,0) to (2,1);
- the fourth tile goes from (1,1) to (2,2);

Task

Write a function that validates a wall with only 1x1 tiles. You can assume all coordinates are >= 0.

A wall is valid if:
1. It has at least one tile;
2. The tiles form a square or rectangle starting at [0,0] with no holes;
3. The tiles don't overlap;

The function returns true if the wall is valid, false otherwise.

Note: you can model the wall and tiles as you wish.

Example of a valid wall: [[0,0],[0,1],[1,0],[1,1]]

Example of a valid wall: [[1,1],[0,1],[0,0],[1,0]]

Example of a valid wall: [[0,0],[0,1]]

Example of an invalid wall (containing holes): [[0,0],[1,1]]

Example of an invalid wall (containing holes): [[0,0],[0,1],[1,0]]

Example of an invalid wall (overlapping tiles): [[0,0],[0,1],[0,1],[1,1]]

Design a system for processing and displaying AI detection events from cameras for a Full Stack Role.

Context: Our cameras run some fancy AI detection algorithm which produces outputs with the following fields:

Field Name    Field type    Description
Camera hash    string    Unique hash of the camera
Detection type    enum    Person,car,bicycle
startX    float    Bounding box coordinate
startY    float    Bounding box coordinate
endX    float    Bounding box coordinate
endY    float    Bounding box coordinate
timestamp    int/string (you choose)    Time of this event

These events are then batched (e.g. every second) and pushed out.

You can assume we already store the camera information and they are available in your backend. Last seen time is periodically updated. It is not related to the pushed events:

Field Name    Field type    Description
Camera hash    string    Unique hash of the camera
Camera name    string    Chosen by the user
Last seen time    time    When the camera was last seen

System components (this is the stuff you should design):

Backend

Design a backend architecture to process the data coming from the cameras. Detections should be stored persistently. You should consider the following:

• Communication protocol(s)
• Persistence
• Redundance
• Scaling

Frontend Pages

Design the following 2 user pages:
Landing page
This page lists all the cameras in the system. For each camera we want to show whether it is online or not (online is last_seen_time < 30 s from now). Cameras can change over time (some might be removed/added). The user can click on a camera to be taken to the daily activity page.
Camera Daily activity page
This page gives information about detection events for a single camera and a single day of choice. A user should be able to answer the following questions:

1. When was a person/car/bike event last/first detected?
2. How are detections distributed per detection type through the day?
3. Were there at least 4 people around at a given time?

Think about how to best display this information.