A Framework for Digital Crop Growing Modeling based on Agricultural Internet of Things

The extensive deployment of Internet of Things (IoT) devices in Controlled Environment Agriculture (CEA) improves the networking and intelligence level of factory agriculture and indoor agriculture. The Digital Crop Growing Model (DCGM) is the foundation for realizing smart agricultural production. Most modeling processes of the known Crop Growing Models (CGMs) use a single environmental factor and the data collection method can cause damage to crops. Temperature and photosynthetically active radiation (PAR) are the key factors in crop growth, but the existing research has not considered the coupling of multiple environmental factors. To address this issue, a DCGM with IoT non-destructive testing technology is proposed and the prototype of real-time online modeling IoT system of vegetable seedlings is designed. The experimental data show that the crop growing prediction accuracy of the proposed modeling method is above up to 98%.