# Multiparametric Monitoring in Equatorial Tomato Greenhouses (II): Energy Consumption Dynamics
## 5 Discussion and Conclusions  
In this paper, we addressed the detailed study of the dynamics of energy consumption time processes in three types of WSNs, namely, ZigBee with star topology, ZigBee with mesh topology (DigiMesh), and WiFi with access point topology, at different transmission rates, for the monitoring of tomato greenhouses in Ecuador. The electrical current measurements of the nodes were acquired at a fast sampling rate, using high resolution multimeters that were connected to the data storage station through a local area network. The experiments were conducted with all the network elements being active, distributed in line of sight, and at the same distance. For the three networks, the test was repeated several times for each transmission rate, and without charging the battery between runs to analyze the impact of battery discharge over the reliability of the acquired consumption data. The consumption dynamics was scrutinized by using stochastic process analysis techniques, such as time series, _pdf_, histograms, and autocorrelation estimation, complemented with bootstrap resampling and CIs, and the results of all the realizations were simultaneously represented by the M-mode. The power consumption of the WSNs nodes was evaluated considering the type of sensors, the network topology, the transmission speed, and the data transmission duration. According to the type of sensor, we conclude that the nodes with the CO\({}_{2}\), wind speed, and wind direction sensors were the ones with the highest consumption, independently of the network communication technology. Regarding the network topology, we verify that the consumption is associated with the role of each node. The consumption of the sensor nodes was lower in the ZigBee and WiFi networks (star topology), where each node only communicates with its coordinator, in contrast to the DigiMesh network (mesh topology), where the links are redundant and the nodes communicate simultaneously with more than one network element. In the case of the coordinator nodes, we concluded that the consumption values were lower for the DigiMesh network, closely followed by the ZigBee network. The consumption of the WiFi coordinator node (MeshliumTM wireless router) was considerably greater than other networks, because the design of this device does not prioritize the issue of energy optimization. Based on these results, we conclude that, in terms of energy saving, the ZigBee network, with star topology and maximum transmission rate, was the most efficient option, and therefore the recommended one for greenhouse monitoring. The WiFi network can be considered as an appropriate second option, since the Coordinator Node is a device whose supply system is the commercial electrical network, and not a battery. Therefore, its high consumption is not a limitation, and the average consumption of the sensor nodes was very close to the measured ones in the ZigBee network. The DigiMesh network would be recommendable for applications where the redundancy of communication links is prioritized instead of energy saving. A further objective of the present research was the characterization of energy consumption of WSNs nodes in terms of seasonality to identify the feasibility of its behavior prediction over time. Unlike the previous analysis, the seasonality was not significantly dependent on the type of sensors used in each node or the network topology, as the outcomes differed between networks, even for cases where sensor nodes measured the same variables. The results of the DigiMesh network were quite similar for the three speeds, i.e., the energy consumption processes were seasonal for the sensor nodes that measure solar and ultraviolet radiation, non-seasonal for the coordinating node, and weakly correlated for the CO\({}_{2}\) sensor node. For the WiFi network at the different transmission rates, the consumption process of the coordinator node was seasonal, while for all the sensor nodes it was non-seasonal.