Developing an Intelligent Farm System to Automate Real-time Detection of Fungal Diseases in Mushrooms
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Abstract
Mushrooms are economically valuable crops of high nutritional value. However, during cultivation they are continually threatened by fungal diseases, even in controlled-condition farm ecosystems. Fungal diseases significantly affect mushroom growth and can rapidly contaminate an entire crop. Farmer inspections can be hazardous to farmer health. This paper contributes an automated fungal disease detection system for the Sajor-caju mushrooms together with an intelligent farm system for precise cultivation environment control. The objective was to create and test a detection system that could detect fungal diseases rapidly, reduce farmer exposure to fungal spores, and alert farmers when fungal disease was detected. The system is composed of three parts: (i) a high-precision environment control system, (ii) an innovative imaging robot system, and (iii) a real-time fungal disease prognosis system using deep learning, with an alarm system. The trial results show that the real-time disease prognosis system has 94.35% precision (89.47% F1-score, n=13,500), and its twice daily inspections detect and report fungal disease typically within 6 to 12 h. The innovative farm’s overall capability for mushroom cultivation (environment control) is regarded as excellent and has precise control (99.6% capability, over 3-months). The innovative imaging robot’s overall operational trial performance is effective (at 99.7%). Moreover, the system effectively notifies farmers via smartphone when a fungal disease is detected.
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