Ecological Game Field — main installation view
Project 05
#Plant-Machine-Coexistence #Object-Oriented-Design #AI-Mediated
Material Sunflower seedlings, glass round-bottom flasks, full-spectrum LED, EMG sensors, temperature/humidity sensors, AI vision, Arduino, automated drip irrigation, thermal printer Plant-Machine Collaborative Installation

Ecological Game Field

Plant-Machine Collaborative Installation · 2025 · Object-Oriented Design Practice
Ecological Game Field — concept rendering

Re-imagining the Plant–Machine Relationship

Ecological Game Field is an interactive installation built on the principle of plant-machine collaboration. Within the system, plants are given the ability to express their own needs — they send "ecological proposals" through the machine.

An AI vision system continuously monitors plant growth indicators via high-precision cameras, transforming biological states into data. When the AI detects an imbalance, a resource allocation mechanism is triggered: light, nutrients, and water are redistributed in a decentralised network, allowing plants to build cooperative relationships within competition.

The machine here is neither tool nor servant. It is a translator and mediator — responding to plant needs while regulating overall ecological balance.

Installation — blue light atmosphere Installation — full system
Installation — flask detail
— System in Motion · Animations —

The Machine Breathes

The installation is rarely still. Light shifts. Fluid moves. Resource flows are choreographed by the AI in real time. These short loops capture the system at different moments of negotiation.

System animation 1 ▸ GIF
System animation 2 ▸ GIF
System animation 3 ▸ GIF
System animation 4 ▸ GIF

Object-Oriented Design

This work embodies the core principle of object-oriented design: it breaks from human-centric thinking and treats plants and machines as agents with their own intentionality, rather than as passive objects.

The plants are no longer decoration or utility — they become participants whose growth itself constitutes a form of expression. The machine is no longer pure execution of human will — it has limited but real autonomous judgement, acting as an intermediary.

Close detail — purple light layer

Time Mapping

Plants grow on a slow, cyclical timescale — fundamentally different from human perception or technological time. To bridge this gap, the system uses a multi-layered time-mapping mechanism.

Cameras continuously capture micro-changes in plant form. AI converts these changes into data streams, triggering immediate responses from the lighting and nutrient systems. The plant's slow growth becomes legible at the human scale — without being forced to abandon its own rhythm.

Installation — viewing angle Installation — lit setup
— Preliminary Light Experiments —

How Light Steers Growth

Before building the installation, we ran a series of experiments to understand how plants respond to controlled light. Two-week-old sunflower seedlings were placed under fixed unilateral light sources to measure their phototropic response.

Within 24 hours, stems bent visibly toward the light — average angles of 1°–2°. After 72 hours, the angle had increased to 4°–8°, with leaves rotating to maximize photosynthetic surface area. When the light source was alternated, plants adapted dynamically, but rotations more frequent than once every 6 hours caused growth disorder.

These data established the safe parameters for AI-driven light modulation — fast enough to engage in negotiation, slow enough not to stress the plant.

Light experiment — seedling array Light experiment — angle measurement
— Prototype Structure —

Built Around the Plant

The installation uses transparent materials and a metal frame so that plant growth — including the root system inside round-bottom flasks — remains fully visible. The aesthetic is laboratory-like, deliberately emphasising the experimental and the scientific.

Modular components include: a full-spectrum LED system, plant carriers (round-bottom flasks), nutrient nozzles, transparent water tubing, cameras, a cross-shaped support structure, and a thermal printer that prints the AI's real-time descriptions of plant states.

Structural diagram — overall system
Structural detail 1 Structural detail 2
— Three-Layer Decision Logic —

A Tripartite Decision Mechanism

The collaborative decision system has three layers — sensing, AI arbitration, and execution-feedback. Resources are allocated through a "voting" mechanism: every plant has a voice, but final decisions consider collective wellbeing.

/ Layer 01
Signal Sensing
EMG sensors capture plant electrical signals; environmental sensors track temperature and humidity. The sensing layer turns biology into a continuous information stream.
/ Layer 02
AI Arbitration
Every 3 hours, the AI analyses plant signals, environmental data, and growth state. When indicators fall below threshold, the AI rebalances — not by overriding plants, but by interpreting their proposals.
/ Layer 03
Execution & Feedback
Decisions become physical action: light fields shift; nutrients flow; positions adjust. The intervention is recorded; the cycle continues.
System logic — overall decision flow
System logic — AI arbitration detail
— Building the Field —

In the Studio

The construction process involved iterative testing of every component — from the geometry of the flask supports, to the precise angle of the LED arrays, to the calibration of the AI vision system.

Working — calibration Working — installation Working — detail check Working — final assembly
— Close-up —
Close-up — system detail composite
Detail — flask with mechanism Detail — light reflection
Detail — full setup

A Field of Multi-Species Negotiation

When AI describes a plant, the description is not a copy of reality — it is a glimpse of how technical media perceives non-human life. When that description is printed onto paper, the plant gains another mode of being: an organic body, then digital information, then a physical text.

The plant is no longer a passive object of observation. Through its symbiosis with the machine, it becomes a subject in artistic practice — its growth, its form, its responses all become driving forces of the system. Ecological Game Field proposes a vision of post-human aesthetics where multi-species negotiation, rather than human dominion, is the foundation of art.

"If one day the machine no longer describes, and the plant no longer greens, has the work itself lost its life?"

Video

Video preview — Ecological Game Field
▸ Watch on YouTube 2025 · Documentation
System3-layer plant-machine collaboration
AIComputer vision + decision algorithm
Year2025
StatusResearch Practice
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