# Multiparametric Monitoring in Equatorial Tomato Greenhouses (II): Energy Consumption Dynamics
## 2 Related Work  
WSN is a modern technology that has been widely used in a variety of applications, such as greenhouse parameter control in precision agriculture [16; 17], quality water monitoring systems [18; 19], military applications [20], intelligent street lighting systems [21], air pollution monitoring systems [22], urban traffic characterization [23], oil industry [24], or health status monitoring [25], among many others. Today, WSNs offer some advantages over traditional wireless communication systems, such as low cost, ease of installation, real time, reliability, and connectivity [26]. Although the choice of WSN technology is attractive, there are still some limitations present, such as energy consumption, low battery life, redundant data acquisition, or low duty cycle.  
One of the today problems in the development of WSN systems comes from the high energy consumption of the sensor nodes, due to its direct impact on the WSN useful life [27]. According to the literature [28; 29], the relevant factors for energy consumption are inside the sensing module (active sensors, sampling rate, and sensor type), inside the processing module (active state, clock frequency, and microcontroller), and inside the communication module (bandwidth, radio, distance, duty cycle, and topology). The heaviest energy consumer is the communication module used for the transmission and reception of data among sensor nodes, and the most energy-demanding elements are at the radio subsystems. Batteries are usually constrained to be small and they are in trouble when required to support long-distance communications due to transmitted power constraints [7].  
Table 1 shows a compilation of research works on the evaluation of WSNs topologies, transmission reliability, energy-consumption optimization techniques, and energy modeling of sensor nodes. In summary, it can be seen that the research is often limited with respect to the analysis of the energy consumption dynamics of the sensor nodes, with the simultaneous consideration of different communication technologies and topologies, in addition to the incidence of the data transmission speed. However, and to our best knowledge, a detailed analysis on the consumption dynamics in terms of detailed statistical descriptions of the consumption time series evolution is missing in the literature.  
\begin{table}
\begin{tabular}{p{113.8 pt} p{113.8 pt}} \hline \hline
**Work** & **Technical Contribution** \\ \hline [PERSON] et al. (2008) [30] & An electronic system to visualize node current consumption usage, and charge extracted from the battery during node operating states. \\ \hline [PERSON] et al. (2009) [31] & A short overview of the energy conservation techniques and algorithms for calculating energy-efficient topologies for WSNs. \\ \hline [PERSON] et al. (2010) [32] & A technique for WSN with mobile sensor nodes reducing 50\% in the energy consumption. \\ \hline [PERSON] et al. (2010) [33] & A full experimental characterization of current consumption in ZigBee sensor nodes. \\ \hline [PERSON] et al. (2011) [34] & A review of energy consumption balancing (ECB) issues in WSNs. \\ \hline [PERSON] et al. (2011) [35] & Energy mathematica model for each part of the wireless sensor node, which is adaptable to any sensor node. \\ \hline [PERSON] et al. (2011) [36] & A performance evaluation of a WSN. \\ \hline [PERSON] et al. (2011) [37] & A review of different techniques to reduce the consumption of the sensor nodes. \\ \hline [PERSON] et al. (2012) [38] & An overview of WSNs and a scenario based comparison for energy efficiency between different topologies. \\ \hline [PERSON] et al. (2012) [39] & A methodology to evaluate the dependability of WSNs in typical industrial environments. \\ \hline \hline \end{tabular}
\end{table}
Table 1: State of the art of relevant works in WSN literature related with energy aspects.