From the 1 of 6 linked papers with an AI index.
6 papers
Bimodal Synchronization Performance: Why Noise and Sparse Connectivity Can Improve Collective Timing
Till Aust, Tianfu Zhang, Andreagiovanni Reina +1
The paper studies a discrete-time firefly-inspired pulse‑coupled oscillator model and shows that collective synchrony appears only near a critical balance of quorum threshold and p…
Early Detection of Water Stress by Plant Electrophysiology: Machine Learning for Irrigation Management
Eduard Buss, Till Aust, Heiko Hamann
Purpose: Fast detection of plant stress is key to plant phenotyping, precision agriculture, and automated crop management. In particular, efficient irrigation management requires e…
Embedded Deep Learning for Bio-hybrid Plant Sensors to Detect Increased Heat and Ozone Levels
Till Aust, Christoph Karl Heck, Eduard Buss +1
We present a bio-hybrid environmental sensor system that integrates natural plants and embedded deep learning for real-time, on-device detection of temperature and ozone level chan…
When Plants Respond: Electrophysiology and Machine Learning for Green Monitoring Systems
Eduard Buss, Till Aust, Heiko Hamann
Living plants, while contributing to ecological balance and climate regulation, also function as natural sensors capable of transmitting information about their internal physiologi…
Classifying Subjective Time Perception in a Multi-robot Control Scenario Using Eye-tracking Information
Till Aust, Julian Kaduk, Heiko Hamann
As automation and mobile robotics reshape work environments, rising expectations for productivity increase cognitive demands on human operators, leading to potential stress and cog…
Automated Phytosensing: Ozone Exposure Classification Based on Plant Electrical Signals
Till Aust, Eduard Buss, Felix Mohr +1
In our project WatchPlant, we propose to use a decentralized network of living plants as air-quality sensors by measuring their electrophysiology to infer the environmental state,…