A Quantum-Enhanced Multi-Agent Approach for Efficient Energy Management in Smart Greenhouse CPS
Abstract
This paper presents a distributed multi-agent cyber-physical system (CPS) framework integratingquantum-inspired particle swarm optimization (QPSO) for autonomous en- ergy management insmart greenhouses. The system employs 50 cooperative agents organized in a nine-layer hierarchicalarchitecture (physical sensing, security, computa- tion, decision-making, control, communication,resilience, maintenance, and application layers). The quantum-inspired PSO incorporatessuperposition principles enabling par- allel exploration of solution spaces and adaptive parametercontrol (w = 0.9 → 0.4, c1 = c2 = 2.0). Through six-month validation on a 1000 m2 commercialtomato facil- ity (180 experimental days, 4,320 hourly measurements), we achieved 23.4% energyreduction (175.8±12.4 to 135.1±8.7 kWh/day, p<0.001) while enhancing crop yield to 34.2±1.6 kg/m2(3.3% improvement). The system achieves 42±8 ms agent response time, 99.2% availability, and95.4% faster fault recovery (8.3±2.1 vs 180±45 seconds) compared to centralized baseline. Statisticalvalidation uses paired t-tests with 95% confidence intervals across 30 daily measurements.Comparative analysis shows superior performance over model predictive control (15-20% energyreduction), genetic algorithms (15-18%), and IoT-based systems (10-15%). This research advancesintelligent agricul- tural systems through distributed artificial intelligence and cyber-physicalintegration.References
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DOI:
https://doi.org/10.31449/inf.v50i14.11990Keywords:
cyber-physical systems, multi-agent systems, quantum-inspired optimization, smart agriculture, energy efficiency, particle swarm optimization, IoT, autonomous controlDownloads
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