Phytomorphic Computing: A Bio-Inspired Framework for Sustainable Data Processing Using Plant Growth Patterns

Posted: May 26, 2024

• Dr. Elara Vance
• Prof. Kenji Tanaka
• Dr. Isabella Rossi

Abstract

This paper introduces phytomorphic computing, a novel computational paradigm inspired by plant growth mechanisms and resource distribution patterns in botanical systems. Unlike traditional computing models that prioritize speed and efficiency, phytomorphic computing emphasizes sustainability, resilience, and adaptive resource allocation. We developed a computational framework that mimics plant vascular systems, root network development, and photosynthetic processes to create energy-aware data processing algorithms. Our methodology translates botanical principles into computational operations, including phyllotactic data structures, auxin-inspired load balancing, and stomatal-like access control. Experimental results demonstrate that phytomorphic algorithms reduce energy consumption by 42% compared to conventional approaches while maintaining 89% of performance efficiency in distributed computing environments. The framework shows particular promise for edge computing and IoT applications where energy constraints and environmental adaptability are critical. This research establishes a foundation for biologically-inspired sustainable computing that diverges fundamentally from animal-inspired neural approaches.