A Biomimetic Way for Coral-Reef-Inspired Swarm Intelligence for Carbon-Neutral Wastewater Treatment

TL;DR

This paper presents a coral-reef-inspired swarm intelligence system for energy-efficient wastewater treatment, achieving high removal efficiency and low energy consumption while demonstrating robustness and potential for diverse field scenarios.

Contribution

Introduces a novel biomimetic swarm interaction network inspired by coral reefs for scalable, energy-neutral wastewater treatment with multi-task carbon awareness.

Findings

Achieves 96.7% removal efficiency

Consumes 0.31 kWh/m^3 energy

Reduces CO2 emissions by 14.2 g/m^3

Abstract

With increasing wastewater rates, achieving energy-neutral purification is challenging. We introduce a coral-reef-inspired Swarm Interaction Network for carbon-neutral wastewater treatment, combining morphogenetic abstraction with multi-task carbon awareness. Scalability stems from linear token complexity, mitigating the energy-removal problem. Compared with seven baselines, our approach achieves 96.7\% removal efficiency, 0.31~kWh~m$^{-3}$ energy consumption, and 14.2~g~m$^{-3}$ CO$_2$ emissions. Variance analysis demonstrates robustness under sensor drift. Field scenarios--insular lagoons, brewery spikes, and desert greenhouses--show potential diesel savings of up to 22\%. However, data-science staffing remains an impediment. Future work will integrate AutoML wrappers within the project scope, although governance restrictions pose interpretability challenges that require further visual analytics.