# State-of-the-Art Internet of Things in Protected Agriculture
## 4 IoT Applications in Protected Agriculture  
### Plant Management  
Compared with open-field agriculture, protected agriculture provides a relatively suitable and controllable environment for crop growth by greenhouse technology, which to some extent is free from the constraints of the natural environment and promoted the intensive and efficient use of agricultural resources. However, spatial and temporal variability of crops' growth environmental parameters in the protected agriculture are strong and affect each other [76; 77], which made it difficult to adapt to the growth of different types of plants in different growth stages by traditional cultivation and environmental regulation. Therefore, it needs higher accuracy in the aspect of monitoring and control. Many works have attempted to design and test types of monitoring and control systems to adjust greenhouse environmental parameters such as air temperature and humidity, light intensity and CO\({}_{2}\) concentration based on IoT and their results have proven it is technically and economically feasible [78]. At the low level of IoT development, the environmental data were simply processed and usually presented in sheet and plot form [79; 80]. Later, some studies collected huge amounts of data to set up various models based on plant growth or greenhouse climate [81; 82; 83], which contributedto predicting the crop yield and environment parameter changes to help farmers better manage greenhouse. [PERSON] et al. developed a low-cost smart greenhouse remote monitor system based on IoT. The system used STM32F103 single chip machine and sensors to collect environmental information and transferred the data to cloud by LPWAN. Security link was established with TLS, which reduced system costs while ensuring the security of data transmission. At the same time, they adopted a time series database to store data so that tremendous storage space can be saved [84]. [PERSON] et al. have reported a greenhouse temperature intelligent control system based on NB-IoT. The relative error of greenhouse environmental information collection was below 1%, the average control accuracy was 3.57% (\(\pm\)1.0 \({}^{\circ}\)C), the transmission distance was not limited and the automatic regulation of crop growth temperature was realized [85]. Nowaday, with the development of cloud computing, ML, etc., IoT solution can easily achieve smart data processing and analyzing at low cost and in a convenient way [86; 87]. At the same time, greenhouse technology has also undergone several generations of upgrades and has now evolved into highly mechanized and automated plant factories. [PERSON] et al. have implemented a closed-loop control system in a salad-cultivating plant factory based on the kinetic model. Both digital simulation and real-time results demonstrated the system can work stably under the internal variations and external disturbances [88]. [PERSON] et al. developed a smart farming IoT platform based on edge and cloud computing, which was designed for soilless culture greenhouses at low cost. The platform was composed of local, edge and cloud parts: the local part dealt with data gathering and automatic control though Cyber-Physical Systems, the edge part took main management tasks and could improve the stability of this systems, the cloud part was in charge of data analytics. Compared with a regular open control, the platform saved more than 30% water [89]. [PERSON] et al. have designed an online irrigation system for hydroponic greenhouse crops and their results indicated it increased water and fertilizer use efficiency by 100% [90]. [PERSON] et al. implemented a IoT-based system in an orchid greenhouse to monitor the environmental factors and the growth status of phalaenopsis. They developed an image processing algorithm to estimate the leaf area of phalaenopsis and identified the relationship between growth of plant leaves and environmental factors.