A Biomimetic Way for Coral-Reef-Inspired Swarm Intelligence for Carbon-Neutral Wastewater Treatment
This addresses carbon-neutral wastewater treatment for environmental applications, but it appears incremental as it builds on swarm intelligence concepts.
The paper tackles the challenge of energy-neutral wastewater treatment by introducing a coral-reef-inspired Swarm Interaction Network, achieving 96.7% removal efficiency, 0.31 kWh m^{-3} energy consumption, and 14.2 g m^{-3} CO2 emissions.
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.