Imagine the following sample data:

[
  {
    "_id": 1,
    "category": "FIRE",
    "time": "2024-05-11T07:11:00Z"
  },
  {
    "_id": 2,
    "category": "FIRE",
    "time": "2024-05-11T08:11:00Z"
  },
  {
    "_id": 3,
    "category": "FIRE",
    "time": "2024-05-11T09:11:00Z"
  },
  {
    "_id": 4,
    "category": "POLICE",
    "time": "2024-05-11T07:22:00Z"
  },
  {
    "_id": 5,
    "category": "POLICE",
    "time": "2024-05-11T08:22:00Z"
  },
  {
    "_id": 6,
    "category": "POLICE",
    "time": "2024-05-11T09:22:00Z"
  },
  {
    "_id": 7,
    "category": "AMBULANCE",
    "time": "2024-05-11T07:33:00Z"
  },
  {
    "_id": 8,
    "category": "AMBULANCE",
    "time": "2024-05-11T08:33:00Z"
  },
  {
    "_id": 9,
    "category": "AMBULANCE",
    "time": "2024-05-11T09:33:00Z"
  }
]

For each combination in a set of categories (e.g. ["FIRE", "AMBULANCE"]) and timestamps (e.g. ["2024-05-11T08:15:00Z", "2024-05-11T09:00:00Z"]), I’d like to get the latest entry on or before each timestamp for each category:

[
  {
    "category": "FIRE",
    "time": "2024-05-11T08:15:00Z",
    "last_entry_on_or_before": {
      "_id": 2,
      "category": "FIRE",
      "time": "2024-05-11T08:11:00Z"
    }
  },
  {
    "category": "FIRE",
    "time": "2024-05-11T09:00:00Z",
    "last_entry_on_or_before": {
      "_id": 2,
      "category": "FIRE",
      "time": "2024-05-11T08:11:00Z"
    }
  },
  {
    "category": "AMBULANCE",
    "time": "2024-05-11T08:15:00Z",
    "last_entry_on_or_before": {
      "_id": 7,
      "category": "AMBULANCE",
      "time": "2024-05-11T07:33:00Z"
    }
  },
  {
    "category": "AMBULANCE",
    "time": "2024-05-11T09:00:00Z",
    "last_entry_on_or_before": {
      "_id": 8,
      "category": "AMBULANCE",
      "time": "2024-05-11T08:33:00Z"
    }
  }
]

Is this possible to do in a single efficient aggregation pipeline? I have a compound index on [category, time].