# Enhancing Smart Agriculture by Implementing Digital Twins: A Comprehensive Review
## 4 Reviewing DT Applications in Agriculture and Farming Domain
### The Second Categorization of Researched Literature, Related to Specific Technical Research Aspects
\begin{table}
\begin{tabular}{c c c c c c c c} \hline \hline
**Citation** & **Case** & **Type of** & **DT** & **Target** & **Sensors** & **IoT/Platforms** & **Deployments/ Technologies- Protocols** \\ \hline
[45] & - & Review & - & Authenticity and traceability of food supply in the agricultural production process & Data acquisition— temperature, conditions, RFID & Satellites Robotics & Technology \\ \hline
[45] & - & Review & - & Authenticity and traceability of food supply in the agricultural production process & Data acquisition— temperature, humidity, soil conditions, RFID & - & Assisted with AI, ML, and deep-learning techniques \\ \hline
[86] & - & Review & Future & Remote detection and monitoring of vegetation and crop stress in agriculture & LiDAR-light detection and ranging—stereo-photogrammetry & & & \\
[87] & - & Review & Future & Remote detection and monitoring of vegetation and crop stress in agriculture & multi-spectral imagery. Passive microwave remote sensing. Active microwave remote sensing & - & - \\
[86] & - & Review & Future & - & - & - \\
[86] & - & Article & Future study & Remote detection and monitoring of vegetation and crop stress in agriculture & - & - \\
[86] & - & Review & Future & - & - & - \\
[87] & - & Review & & - & - & - \\
[87] & - & Assessment & \(\surd\) & Monitor, control, coordinate, and execute farm operations at agricultural sites & IoT sensor nodes & IoT sensor nodes & IoT sensor nodes & IoT sensor nodes & \\ \hline
[88] & - & Conference paper & \(\surd\) & Predictive control, for improving soil quality & Predictive control, for optimization, or co2 concentration, air velocity, and light level & & & \\ \hline
[88] & - & Conference paper & \(\surd\) & \(\surd\) & \(\begin{array}{c}\text{Predictive}\\ \text{control, for}\\ \text{improving}\\ \text{soil quality}\end{array}\) & \(\begin{array}{c}\text{Predictive}\\ \text{control, for}\\ \text{improving}\\ \text{soil quality}\end{array}\) & \(\begin{array}{c}\text{Predictive}\\ \text{control, for}\\ \text{(RH), CO}_{2}\end{array}\) & IoT, SWAMP & \(\begin{array}{c}\text{Programmable}\\ \text{logic controllers}\\ \text{(PLCs) in the}\\ \text{in}\\ \text{irrigation system,}\\ \text{equipment}\\ \text{and machines}\end{array}\) \\ \hline \hline \end{tabular}
\end{table} 
Table 3: _Cont._(LiDAR) sensors and multispectral cameras following an Arduino single-board microcontrollers programmable platform or single-board computer Raspberry Pi-3 enhance IoT sensor nodes to acquire and transmit farm data to IoT gateways or edge devices, thus cultivating DT requirements for vertical farms, for the greenhouse production process and finally models in sustainable agriculture. Remote detection and monitoring of vegetation and crop stress in agriculture seem feasible based on [86] utilizing LiDAR--stereo-photogrammetry technology, using multi-spectral imagery, passive microwave remote sensing, RFID schemes [9; 45], active microwave remote sensing (RADAR) and sensors onboard UAVs and satellites [45; 76; 88]. Location determination in farming via geospatial position (GPS) plays a significant role in the remote detection and monitoring of vegetation and crop conditions in agriculture [88]. IoT deployments in smart farming are based on serial hardware communication protocols such as I2C serial bus [28] and UART that uses asynchronous serial communication with configurable speed and pulse width modulation (PWM) for driving actuators [77; 81], in correlation with programmable logic controllers (PLC) for data recording [29], monitoring, and optimization aided occasionally by fuzzy interference systems (FIS) [73]. The decision-making and actions once undertaken by the farmers now have given way to data-driven agricultural decision-making, i.e., assisting them to undertake informed decisions related to planting, fertilization, pest control, harvesting, and overall farm management.