diff --git a/src/exercises/type_hints.py b/src/exercises/type_hints.py
new file mode 100644
index 0000000..f704701
--- /dev/null
+++ b/src/exercises/type_hints.py
@@ -0,0 +1,11 @@
+def load_scores(data: list[tuple[str, int | str]]) -> dict[str, int]:
+    result: dict[str, int] = {}
+
+    for name, points in data:
+        result[name] = int(points)
+
+    return result
+
+
+if __name__ == "__main__":
+    print(load_scores([("Housi", 40), ("Theodolf", 45), ("Mehmet", 15)]))
diff --git a/src/lap_detection/api.py b/src/lap_detection/api.py
new file mode 100644
index 0000000..8013300
--- /dev/null
+++ b/src/lap_detection/api.py
@@ -0,0 +1,35 @@
+from dataclasses import field, dataclass
+from typing import List
+
+
+@dataclass
+class Coordinate:
+    lon: float
+    lat: float
+
+
+@dataclass
+class Geometry:
+    coordinates: list[list[float]]
+    type: str
+
+
+@dataclass
+class Feature:
+    type: str
+    properties: dict
+    geometry: Geometry
+
+
+@dataclass
+class Collection:
+    type: str
+    features: list[Feature]
+
+
+@dataclass
+class Lap:
+    start_index: int
+    end_index: int
+    distance_m: float
+    coords: List[Coordinate] = field(default_factory=list)
diff --git a/src/lap_detection/data/usecase1-luetzelsee.png b/src/lap_detection/data/usecase1-luetzelsee.png
new file mode 100644
index 0000000..b431cd1
Binary files /dev/null and b/src/lap_detection/data/usecase1-luetzelsee.png differ
diff --git a/src/lap_detection/data/usecase1.json b/src/lap_detection/data/usecase1.json
new file mode 100644
index 0000000..df6f7e0
--- /dev/null
+++ b/src/lap_detection/data/usecase1.json
@@ -0,0 +1,254 @@
+{
+  "type": "FeatureCollection",
+  "features": [
+    {
+      "type": "Feature",
+      "properties": {},
+      "geometry": {
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diff --git a/src/lap_detection/data/usecase2-la_stadion.png b/src/lap_detection/data/usecase2-la_stadion.png
new file mode 100644
index 0000000..e8a2aaa
Binary files /dev/null and b/src/lap_detection/data/usecase2-la_stadion.png differ
diff --git a/src/lap_detection/data/usecase2.json b/src/lap_detection/data/usecase2.json
new file mode 100644
index 0000000..b14ca3c
--- /dev/null
+++ b/src/lap_detection/data/usecase2.json
@@ -0,0 +1,230 @@
+{
+  "type": "FeatureCollection",
+  "features": [
+    {
+      "type": "Feature",
+      "properties": {},
+      "geometry": {
+        "coordinates": [
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diff --git a/src/lap_detection/data/usecase3.json b/src/lap_detection/data/usecase3.json
new file mode 100644
index 0000000..3fe2b7d
--- /dev/null
+++ b/src/lap_detection/data/usecase3.json
@@ -0,0 +1,146 @@
+{
+  "type": "FeatureCollection",
+  "features": [
+    {
+      "type": "Feature",
+      "properties": {},
+      "geometry": {
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diff --git a/src/lap_detection/data/usecase3_davos_gelaende.png b/src/lap_detection/data/usecase3_davos_gelaende.png
new file mode 100644
index 0000000..91fe690
Binary files /dev/null and b/src/lap_detection/data/usecase3_davos_gelaende.png differ
diff --git a/src/lap_detection/data/usecase4-aarau_stadtkurs.png b/src/lap_detection/data/usecase4-aarau_stadtkurs.png
new file mode 100644
index 0000000..379c259
Binary files /dev/null and b/src/lap_detection/data/usecase4-aarau_stadtkurs.png differ
diff --git a/src/lap_detection/data/usecase4.json b/src/lap_detection/data/usecase4.json
new file mode 100644
index 0000000..66a662b
--- /dev/null
+++ b/src/lap_detection/data/usecase4.json
@@ -0,0 +1,150 @@
+{
+  "type": "FeatureCollection",
+  "features": [
+    {
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+}
diff --git a/src/lap_detection/lap_detector.py b/src/lap_detection/lap_detector.py
new file mode 100644
index 0000000..3487408
--- /dev/null
+++ b/src/lap_detection/lap_detector.py
@@ -0,0 +1,53 @@
+from haversine import haversine, Unit
+
+from lap_detection.api import Coordinate
+
+
+def dist(a: Coordinate, b: Coordinate):
+    return haversine((a.lat, a.lon), (b.lat, b.lon), Unit.METERS)
+
+
+def count_laps(coords: list[Coordinate], start_coord: Coordinate, radius: int) -> int:
+    """Count the number of laps completed
+    by tracking the number of times that the starting coordinate was passed by the given coordinate list
+    Args:
+        coords (list[Coordinate]): the list of coordinates
+        start_coord (Coordinate): the coordinate to compare to
+        radius (int): the radius around the starting coordinate
+    Returns:
+        int: the number of laps completed
+    """
+    if not coords:
+        return 0
+
+    laps = 0
+
+    distance_since_last = 0
+
+    # Do we start inside or outside the start/finish area?
+    d_to_first = dist(coords[0], start_coord)
+    inside = d_to_first < radius
+
+    for i in range(1, len(coords)):
+        prev = coords[i - 1]
+        curr = coords[i]
+
+        # Don't compare the starting coordinate with itself
+        if curr == start_coord:
+            continue
+
+        d = dist(prev, curr)
+        distance_since_last += d
+
+        # Did we enter the start/finish area?
+        d_to_start = dist(curr, start_coord)
+        now_inside = d_to_start < radius
+        if not inside and now_inside:
+            # Ignore possible gps stutters with minimum lap distance threshold
+            if distance_since_last > 100:
+                laps += 1
+                distance_since_last = 0
+
+        inside = now_inside
+
+    return laps
diff --git a/src/lap_detection/main.py b/src/lap_detection/main.py
new file mode 100644
index 0000000..e33527d
--- /dev/null
+++ b/src/lap_detection/main.py
@@ -0,0 +1,131 @@
+# TASK: Rundenzählung Stoppuhr
+
+# Hintergrund:  Sportuhren zeichnen oft mittels GPS alle x Sekunden die Koordination (lat/lon) des jeweiligen Standorts auf.
+#               Ein automatischer Modus detektiert, wenn der User eine Runde (Lap) gelaufen/gefahren ist und nimmt
+#               automatisch die Zwischenzeit.
+#
+# Aufgabe:      Unsere Aufgabe ist es nun diese Rundendetektion selbst in Python zu schreiben. Der Programmierer bekommt
+#               eine .json-File mit Koordinaten. Diese sind immer als Liste [lon, lat], also z.B. [[8.5417, 47.3769],
+#               [8.5434, 47.3772], [8.5446, 47.3783], ...]. Unser Programm soll als Antwort einen Integer mit der
+#               ermittelten Anzahl Runden zurückgeben, also z.B. 2.
+#
+#               - Die Aufgabe ist bewusst so offen gestellt, damit eure Kreativität nicht eingeschränkt ist. Ihr könnt den
+#                 Schwierigkeitsgrad selbst steuern, wie stark ihr ins Detail wollt, was ihr berücksichtigen wollt und was
+#                 nicht etc. Es geht damit auch nicht so sehr um die technischen Details, sondern darum, denn Code mithilfe
+#                 von Hints und Docstrings möglichst aussagekräftig und selbsterklärend zu machen. Nutzt auch 2-3 Tests mit
+#                 Pytest, um eueren Code 'sicherer' zu machen und zu validieren.
+#
+# Denkanstösse: - Was macht eine Runde aus?
+#               - Wie entscheide ich, was eine Runde ist (geometrisch, Randbedingungen) -> 'Kochrezept' machen
+#               - Wo schränke ich mich ein, wo mache ich Annahmen, ...
+#
+# Ziel:         - Ein anderer User/Programmierer kann eure Funktionen und die darin hints/docstrings/tests lesen und
+#                 versteht was in eurem Code passiert, ohne den eigentlichen Code anschauen zu müssen.
+#               - Es muss keine Perfektion angestrebt werden, es geht um die praktische Umsetzung der Theorie in einer
+#                 Praxisanwendung! Macht Annahmen/Vereinfachungen!
+#               - Diejenigen, welche das Beispiel abgeben wollen, machen am besten einen
+#                    - neuen Branch (Aufgabe Rundenzählung)
+#                    - main-Funktion mit der Hauptfunktion, allfällige Helferfunktionen in einem separaten Modul
+#                    - test-Ordner mit 2-3 Pytests
+#                    - ein kurzer Readme mit Erklärung der Funktionsweise eures Rundenzählers und allfällige
+#                      Einschränkungen/Annahmen
+#                    - alle Funktionen mit sauberen Typehints und docstrings (Validation falls nötig)
+#                    -> commit und PR
+#
+# Hilfsmittel:   - für benötigte geometrische Berechnungen dürfen auch KI-Hilfsmittel (Prompt Engineering) genutzt werden!
+#                - Bitte nützt aber die KI nicht, um das ganze Programm zu erstellen, dokumentieren und testen :-)
+#
+# Hints:         - für eine allfällige Distanz zwischen 2 Punkten -> haversine
+#
+# Usecases:      - Im Ordner 'data' befinden sich 4 usecases mit Koordinaten.
+#                - Lösungen für die usecases:
+#                   - usecase1: 3
+#                   - usecase2: 3 (3 3/4)
+#                   - usecase3: 0
+#                   - usecase4: 2
+#                - Schreibt aber auch noch 1-2 eigene Testcases für allfällige wichtige Hilfsfunktionen.
+
+
+from pathlib import Path
+import json
+
+from dacite import from_dict
+
+from lap_detection.api import Collection, Coordinate
+from lap_detection.lap_detector import count_laps, dist
+
+
+def _check_path(path: str) -> Path:
+    """Checks the existence of the provided path
+    Args:
+        path (str): The path
+    Returns:
+        a Path object
+    Raises:
+        ValueError: If the path is not present
+    """
+    path = Path(path)
+    if not path.exists():
+        raise FileNotFoundError(f"{path} does not exist")
+    return path
+
+
+def _read_file(path: Path) -> Collection:
+    """Reads the provided file
+    Args:
+        path (str): The path of the file
+    Returns:
+        an object of type Collection
+    """
+    with path.open("r", encoding="utf-8") as f:
+        loaded_file = json.load(f)
+        collection = from_dict(data_class=Collection, data=loaded_file)
+        return collection
+
+
+def _build_coordinates(collection: Collection) -> list[Coordinate]:
+    """Build a list of Coordinate objects from a Collection
+    Args:
+        collection (Collection): the feature collection
+    Returns:
+        a list of Coordinate objects
+    """
+    return [
+        Coordinate(coordinate[0], coordinate[1])
+        for coordinate in collection.features[0].geometry.coordinates
+    ]
+
+
+def get_coordinates(path: str) -> list[Coordinate]:
+    """Validate the path, read the file and extract the coordinates
+    Args:
+        path (str): The path of the file
+    Returns:
+        a list of Coordinate objects
+    """
+    validated_path = _check_path(path)
+    data = _read_file(validated_path)
+    coordinates = _build_coordinates(data)
+
+    return coordinates
+
+
+def main(path: str) -> None:
+    coords = get_coordinates(path=path)
+
+    # detect laps -> business logic (build functions)
+
+    # Set the radius of the start/finish area based of the minimum distance of two following points
+    radius = min([dist(coords[i - 1], coords[i]) for i in range(len(coords))])
+
+    # Count laps from each coordinate
+    # The maximum indicates that the starting point is in a high traffic area
+    n_rounds = max([count_laps(coords, start, radius) for start in coords])
+    print(f"Anzahl Runden: {n_rounds}")
+
+
+if __name__ == "__main__":
+    main("data/usecase1.json")
+    main("data/usecase2.json")
+    main("data/usecase3.json")
+    main("data/usecase4.json")
diff --git a/tests/lap_detection/test_main.py b/tests/lap_detection/test_main.py
new file mode 100644
index 0000000..c6dd668
--- /dev/null
+++ b/tests/lap_detection/test_main.py
@@ -0,0 +1,57 @@
+import pytest
+
+from lap_detection.api import Collection, Feature, Geometry, Coordinate
+import lap_detection.main as main
+
+
+# arrange
+@pytest.fixture
+def sample_collection():
+    return Collection(
+        "FeatureCollection",
+        [
+            Feature(
+                "Feature",
+                {},
+                Geometry([[123.456, 654.321], [987.654, 101.010]], "LineString"),
+            )
+        ],
+    )
+
+
+# arrange
+@pytest.mark.parametrize(
+    "path,expected_laps",
+    [
+        ("src/lap_detection/data/usecase1.json", 3),
+        ("src/lap_detection/data/usecase2.json", 3),
+        ("src/lap_detection/data/usecase3.json", 0),
+        ("src/lap_detection/data/usecase4.json", 2),
+    ],
+)
+def test_main(path, expected_laps, capsys):
+    # act
+    main.main(path)
+
+    # assert
+    captured = capsys.readouterr()
+    assert captured.out.strip() == f"Anzahl Runden: {expected_laps}"
+
+
+def test_check_invalid_path():
+    # assert
+    with pytest.raises(FileNotFoundError, match="invalid_path.json does not exist"):
+        # act
+        main._check_path("invalid_path.json")
+
+
+def test_build_coordinates(sample_collection):
+    # act
+    coordinates = main._build_coordinates(sample_collection)
+
+    # assert
+    assert isinstance(coordinates, list)
+    assert len(coordinates) == 2
+    assert isinstance(coordinates[1], Coordinate)
+    assert coordinates[1].lon == 987.654
+    assert coordinates[1].lat == 101.010
diff --git a/tests/test_lap_detector.py b/tests/test_lap_detector.py
new file mode 100644
index 0000000..d5e62b6
--- /dev/null
+++ b/tests/test_lap_detector.py
@@ -0,0 +1,54 @@
+from lap_detection.api import Coordinate
+from lap_detection.lap_detector import count_laps
+
+
+def test_no_laps():
+    # arrange
+    start = Coordinate(lat=47.0, lon=8.0)
+    coords = [
+        Coordinate(lat=47.0001, lon=8.0001),
+        Coordinate(lat=47.0002, lon=8.0002),
+        Coordinate(lat=47.0003, lon=8.0003),
+    ]
+
+    # act
+    result = count_laps(coords, start, radius=20)
+
+    # assert
+    assert result == 0
+
+
+def test_single_lap():
+    # arrange
+    start = Coordinate(lat=47.0, lon=8.0)
+    coords = [
+        Coordinate(lat=47.0030, lon=8.0000),  # far from start
+        Coordinate(lat=47.0020, lon=8.0010),
+        Coordinate(lat=47.0010, lon=8.0020),
+        Coordinate(lat=47.0001, lon=8.0001),  # back near start -> lap counted
+        Coordinate(lat=47.0030, lon=8.0000),  # far again -> no second lap
+    ]
+
+    # act
+    result = count_laps(coords, start, radius=20)
+
+    # assert
+    assert result == 1
+
+
+def test_two_laps():
+    # arrange
+    start = Coordinate(lat=47.0, lon=8.0)
+    coords = [
+        Coordinate(lat=47.0030, lon=8.0000),  # far from start
+        Coordinate(lat=47.0001, lon=8.0001),  # back near start -> lap 1
+        Coordinate(lat=47.0002, lon=8.0002),  # still near start -> don't count twice
+        Coordinate(lat=47.0030, lon=8.0000),  # far again
+        Coordinate(lat=47.0001, lon=8.0001),  # back near start -> lap 2
+    ]
+
+    # act
+    result = count_laps(coords, start, radius=20)
+
+    # assert
+    assert result == 2