SILDSO: Dynamic Switching Optimization Scheme for Solar Insecticidal Lamp Based on Multi-Pest Phototactic Rhythm

Area of Science:

• Agricultural Science
• Entomology
• Smart Agriculture Technology

Background:

• Grain crops are vital for China's food security, necessitating effective pest control.
• Traditional solar insecticidal lamps have limitations in energy efficiency and adaptability to multiple pests.
• Nocturnal phototactic pests like Cnaphalocrocis medinalis and Chilo suppressalis threaten rice yields.

Purpose of the Study:

• To develop an intelligent switching control optimization scheme for solar insecticidal lamps.
• To enhance pest control effectiveness and energy efficiency by integrating multi-pest phototactic rhythms.
• To improve the adaptability of IoT-based solar insecticidal lamps in complex agricultural environments.

Main Methods:

• Developed a multi-period intelligent switching control scheme based on multi-pest phototactic rhythms.
• Integrated pest behavioral rhythms, energy consumption, and residual energy levels for dynamic optimization.
• Employed rhythm modeling and dynamic adjustment mechanisms for precise control.

Main Results:

• The dynamic switching control scheme improved the average insecticidal rate by 17.7%.
• Effective insecticidal energy efficiency increased by approximately 66.1%.
• Energy utilization rate was enhanced by about 38.5% compared to traditional methods.

Conclusions:

• The proposed intelligent control scheme significantly boosts pest control precision and energy efficiency.
• This technology promotes sustainable smart agriculture through optimized networked solar insecticidal lamps.
• Provides a practical reference for intelligent pest management in diverse agricultural settings.