Vattenjagen

#8 — Rian Design Museum, 2025

Vattenjagen #8 is a mechatronic speculative design installation enabling dialog with a Lake in Sweden, Lake Bolmen. The installation consists of a sculptural prototype, The Liminal Contact Device (LCD), and accompanying elements designed to articulate the future context the prototype enables. The piece aims to explore communication between human and more-than-human entities by writing, or drawing, in the sand along the shoreline and through the LCD. The message is read by the device’s wave and a response appears and represented by an audio response and a generated image. The fleeting response dissolves back into the device’s shoreline interface as if the water itself is thinking about its connection to it’s dialog partner(s). The message exchange is repeatable where those in conversation likely realize that they do not necessarily understand one another fully. Instead the aim is to inspire an understanding that they could learn how to hear or listen. That, in fact, the Lake-Human dialog, configures a reality where one must meet in the middle of each other’s experiences. Moreover, that we have been communicating to our Lake friends and that we can in fact learn to understand the communication messages towards us. This work continues Studio Alight's investigation into liminal spaces: thresholds where human perception meets machine vision, where language meets landscape, where the seen meets the sensed. The lake in Vattenjagen #8 becomes a mirror and a messenger.

Location: Rian Design Museum, Falkenberg

Year: 2025

Medium: Mechatronic installation, projection mapping, computer vision

Exhibition: Part of ongoing Vattenjagen series

Vattenjagen

#8 — Technical Documentation

System Architecture

STEREO CAMERA ARRAY → YOLO OBJECT DETECTION → IMAGE CLASSIFICATION ↓ ↓ ↓ SAND TRACKING HUMAN DETECTION CONTENT SELECT ↓ ↓ ↓ TRIGGER SIGNAL → PROJECTION MAPPING → LAKE SURFACE OUTPUT

Hardware

• Camera Array: One 4K camera with IR illumination for low-light conditions

• Processing Unit: NVIDIA Jetson AGX Orin for edge computing. Runs YOLOv5 for real-time human detection at 30fps.

• Projection System: 12,000 lumen laser projector. Calibrated to water surface geometry.

Software Stack

• Object Detection: YOLOv5 trained on COCO dataset, fine-tuned for shoreline human silhouettes

• Classification: ImageNet-based classifier (ResNet50) for style and content matching

• Projection Mapping: OpenCV calibration with water surface distortion compensation

Data Flow

1. Stereo cameras capture shoreline at 30fps 2. YOLO detects human presence and tracks motion path 3. Writing gesture triggers: motion stops + sand contact detected 4. System captures written character/image from bounding box 5. Character classified (letter? symbol? abstract shape?) 6. Content database queried for semantic match 7. Selected image warped for water surface projection 8. Laser projector outputs for 3-5 seconds 9. Fade to black, system resets

References

Based on prior work: [Self] Confidence (2019) — neural network classification research

GitHub: github.com/studioalight/vattenjagen

Paper: "Mechatronic Dialogues: Water as Interface" (in review)