diff --git a/hackathon/config.py b/hackathon/config.py
new file mode 100644
index 0000000..49e31fa
--- /dev/null
+++ b/hackathon/config.py
@@ -0,0 +1,4 @@
+SERVER_IP = ""
+SERVER_PORT = 6666
+FRAME_RATE = 20
+UPDATE_RATE = 2
\ No newline at end of file
diff --git a/hackathon/server.py b/hackathon/server.py
new file mode 100644
index 0000000..1aceca5
--- /dev/null
+++ b/hackathon/server.py
@@ -0,0 +1,89 @@
+import cv2 as cv
+from facenet_pytorch import MTCNN
+from hsemotion.facial_emotions import HSEmotionRecognizer
+from threading import Thread
+from queue import Queue
+import time
+from config import SERVER_IP, SERVER_PORT, FRAME_RATE, UPDATE_RATE
+from communication import create_server_socket, send_image_and_emotions
+from vision import (
+    check_cuda_available,
+    check_camera_available,
+    detect_faces,
+    adjust_bounding_boxes,
+    predict_emotions_from_faces,
+)
+from cli import print_connect, print_disconnect, print_emotions
+
+
+def update_values(queue: Queue):
+    capture = cv.VideoCapture(0)
+    check_camera_available(capture)
+    device = check_cuda_available()
+    mtcnn = MTCNN(keep_all=False, post_process=False, min_face_size=40, device=device)
+    emotion_recognizer = HSEmotionRecognizer(
+        model_name="enet_b0_8_best_afew", device=device
+    )
+    previous_time = 0
+    try:
+        while True:
+            time_elapsed = time.time() - previous_time
+            if time_elapsed > 1/FRAME_RATE:
+                previous_time = time.time()
+                _, frame_bgr = capture.read()
+                frame = cv.cvtColor(frame_bgr, cv.COLOR_BGR2RGB)
+                bounding_boxes = detect_faces(mtcnn, frame)
+                bounding_boxes = adjust_bounding_boxes(
+                    bounding_boxes, frame.shape[0], frame.shape[1]
+                )
+                emotions = predict_emotions_from_faces(
+                    emotion_recognizer, frame, bounding_boxes
+                )
+                #print_emotions(emotions)
+                if queue.full():
+                    with queue.mutex:
+                        queue.queue.clear()
+                        queue.put((frame_bgr, emotions))
+                else:
+                    queue.put((frame_bgr, emotions))
+    finally:
+        capture.close()
+
+
+def update_to_clients(queue: Queue):
+    server_socket = create_server_socket(SERVER_IP, SERVER_PORT)
+    
+    try:
+        server_socket.listen(5)
+        while True:
+            client, address = server_socket.accept()
+            thread = Thread(
+                target=update_to_client, args=(client, address, queue)
+            )
+            thread.start()
+    finally:
+        server_socket.close()
+
+
+def update_to_client(client, address, queue):
+    
+    try:
+        previous_time = 0
+        print_connect(address)
+        while True:
+            time_elapsed = time.time() - previous_time
+            if time_elapsed > 1/UPDATE_RATE:
+                time_elapsed = time.time()
+                (frame_bgr, emotions) = queue.get()
+                send_image_and_emotions(client, address, frame_bgr, emotions)
+    except BrokenPipeError:
+        print_disconnect(address)
+        client.close()
+
+
+if __name__ == "__main__":
+    data_queue = Queue()
+    update_values_thread = Thread(target=update_values, args=(data_queue,))
+    update_to_clients_thread = Thread(target=update_to_clients, args=(data_queue,))
+    update_values_thread.start()
+    update_to_clients_thread.start()