# Plant Bioelectric Early Warning Systems: A Five-Year Investigation into Human-Plant Electromagnetic Communication

arXiv: https://arxiv.org/abs/2506.04132 · HTML: https://mlsanity.com/paper/2506.04132/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Builds on 2 of its 15 references that are in the map.
- First posted on arXiv 4 Jun 2025.

## Builds on (most cited first, 2 of 2)

- [Recognizing Individuals and Their Emotions Using Plants as Bio-Sensors through Electro-static Discharge](https://mlsanity.com/paper/2005.04591/) (2020)
- [Eurythmic Dancing with Plants -- Measuring Plant Response to Human Body Movement in an Anthroposophic Environment](https://mlsanity.com/paper/2012.12978/) (2020)

## Abstract (arXiv)

We present a comprehensive investigation into plant bioelectric responses to human presence and emotional states, building on five years of systematic research. Using custom-built plant sensors and machine learning classification, we demonstrate that plants generate distinct bioelectric signals correlating with human proximity, emotional states, and physiological conditions. A deep learning model based on ResNet50 architecture achieved 97% accuracy in classifying human emotional states through plant voltage spectrograms, while control models with shuffled labels achieved only 30% accuracy. This study synthesizes findings from multiple experiments spanning 2020-2025, including individual recognition (66% accuracy), eurythmic gesture detection, stress prediction, and responses to human voice and movement. We propose that these phenomena represent evolved anti-herbivory early warning systems, where plants detect approaching animals through bioelectric field changes before physical contact. Our results challenge conventional understanding of plant sensory capabilities and suggest practical applications in agriculture, healthcare, and human-plant interaction research.