## 6 Conclusions  
Smart farming involves the integration of advanced technologies into existing farming practices to increase production efficiency and quality of agricultural products. The evolution of IoT and UAVs has enabled the vision of sustainable smart farming, where these smart technologies have proven to increase the quality of crop yield and reduce the environmental footprint from the agricultural sector. This paper shows a low-cost platform for comprehensive environmental parameter monitoring using flying IoT. The proposal is based on experimental work to fulfill the requirements of automated and real-time monitoring of the environmental parameters using both under- and aboveground sensors. These IoT sensors devices on a farm collect vast amounts of environmental data, where it is sent to ground gateways every 1 h, after which the obtained data are collected and transmitted by a drone to the cloud for storage and analysis every 12 h. This platform is deployed and tested in a real scenario on a farm in Medenine, Tunisia, in the period of March 2020 to March 2021, covering open-field and greenhouse cultivation. This low-cost platform can help farmers, governmental, or manufacturers to predict environmental conditions data over the geographically large farm field, which leads to enhancement of crop produc  
\begin{table}
\begin{tabular}{p{12.3 pt} p{12.3 pt} p{12.3 pt} p{12.3 pt} p{12.3 pt} p{12.3 pt} p{12.3 pt} p{12.3 pt}} \hline \hline
**Ref. ** & **Major Advantages** & **Validation** & **Decision Support System** & **Critical Challenges** \\ \hline \multirow{10}{*}{[30]} & \multirow{4}{*}{\(\blacksquare\)} & \multirow{4}{*}{Agrize system features a mesh-like configuration of in-field nodes that act both as the sensor for soil moisture, temperature, and humidity and actuator on a valve that regulates drip irrigation.} & \multirow{4}{*}{\(\blacksquare\)} & \multirow{4}{*}{Experimental} & \multirow{4}{*}{\(\blacksquare\)} & \multirow{4}{*}{Regulates drip irrigation.} & \multirow{4}{*}{\(\blacksquare\)} & High power consumption in the case of the sensor nodes far from Sink \\  & & & & & & & \\ \hline \multirow{10}{*}{[31]} & \multirow{4}{*}{A system that will recommend whether water is needed or not by predicting the rainfall using Genetic Algorithm.} & \multirow{4}{*}{\(\blacksquare\)} & \multirow{4}{*}{Simulation} & \multirow{4}{*}{\(\blacksquare\)} & Plant watering is performed by quadrotor UAV. Activation a pump for water spraying.} & \multirow{4}{*}{\(\blacksquare\)} & Gateway consumes more power because it is always awake. \\ \cline{1-1} \cline{5-5}  & & & & & & & \\ \cline{  
tivity and farm management in a cost-effective, and timely manner. Obtained practical results indicate that automated and human-made sets of actions have been applied and/or suggested that are smart actions for precision agriculture, which, in turn, dramatically boost crop productivity and help in saving natural resources. Examples of these actions are the following:  
* Farmers are advised to consider various strategies such as spraying chemicals on plants during some seasons;
* Various plantings and quarterly grains are suggested;
* Estimate the amount of water needed to bring the soil to field capacity;
* Farmers are advised to consider greenhouses to protect plants from high light intensity during summer;
* Adjust water irrigation using automated dripping and sprinkling based on environmental parameters;
* Using solar panels for powering the weather station leads to energy efficiency. From a practical point of view, the deployed nodes, which are fed by a solar panel-recharged battery, have correctly transmitted data for 12 months, with underground and aboveground sensors and despite bad weather conditions. Indeed, even though some samples were lost during several rainy days, once their batteries were recharged by solar light during the following sunny days, nodes restarted to transmit properly.