diff --git a/README.md b/README.md
index 7d280b57..beed655c 100644
--- a/README.md
+++ b/README.md
@@ -217,19 +217,23 @@ len(dataset)
## 🎬 tutorials
-
-
-Speed Estimation & Vehicle Tracking | Computer Vision | Open Source
-
Created: 11 Jan 2024 | Updated: 11 Jan 2024
-
Learn how to track and estimate the speed of vehicles using YOLO, ByteTrack, and Roboflow Inference. This comprehensive tutorial covers object detection, multi-object tracking, filtering detections, perspective transformation, speed estimation, visualization improvements, and more.
+Want to learn how to use Supervision? Explore our [how-to guides](https://supervision.roboflow.com/develop/how_to/detect_and_annotate/), [end-to-end examples](https://github.com/roboflow/supervision/tree/develop/examples), and [cookbooks](https://supervision.roboflow.com/develop/cookbooks/)!
-
-Traffic Analysis with YOLOv8 and ByteTrack - Vehicle Detection and Tracking
-
Created: 6 Sep 2023 | Updated: 6 Sep 2023
-
In this video, we explore real-time traffic analysis using YOLOv8 and ByteTrack to detect and track vehicles on aerial images. Harnessing the power of Python and Supervision, we delve deep into assigning cars to specific entry zones and understanding their direction of movement. By visualizing their paths, we gain insights into traffic flow across bustling roundabouts...
+
+Dwell Time Analysis with Computer Vision | Real-Time Stream Processing
+Created: 5 Apr 2024
+
Learn how to use computer vision to analyze wait times and optimize processes. This tutorial covers object detection, tracking, and calculating time spent in designated zones. Use these techniques to improve customer experience in retail, traffic management, or other scenarios.
+
+
+
+
+
+Speed Estimation & Vehicle Tracking | Computer Vision | Open Source
+
Created: 11 Jan 2024
+
Learn how to track and estimate the speed of vehicles using YOLO, ByteTrack, and Roboflow Inference. This comprehensive tutorial covers object detection, multi-object tracking, filtering detections, perspective transformation, speed estimation, visualization improvements, and more.
## 💜 built with supervision