## 2 Related Work
For water monitoring, they employed sensors to achieve data on conductivity, temperature, dissolved oxygen, and air saturation. The user interface allowed monitoring of the parameters from a graph and a log. Furthermore, the system was able to alarm users when the fish disease was propagated to provide treatment. [PERSON] et al. presented in [20] a water quality monitoring system for fish farms. The system was composed of SUNSET (Software Defined Communication Stack) for networking purposes and Hydrolab Series 5 probes for data acquisition. The measured parameters were temperature, pH, luminescent Dissolved Oxygen (LDO), salinity, Oxidation Reduction Potential (ORP) and specific conductance (SpCond). Moreover, energy consumption was reduced employing new sleep and wake-up mechanisms. Another water monitoring system was presented by [PERSON] et al. in [21]. Their system employed ZigBee and GPRS modules with a STM32F103 chip. They also employed a Pt1000 temperature sensor and a YCS-2000 dissolved oxygen sensor as well as other sensors to measure pH and ammonia. The obtained information could be monitored with a computer program developed with Labview. This program allowed monitoring of each parameter in a separate graph as well as numerically. Results showed a packet loss rate of 0.43%. [PERSON] et al. proposed in [22] an aquiculture environment monitoring system that employed RF (Radio Frequency) and GSM (Global System for Mobile communications) to measure temperature and dissolved oxygen. Two algorithms were designed to determine the performance of the monitoring center and the different substations. Substations performed a 24-h uninterrupted data acquisition and forwarded the information in real-time. The techniques employed to monitor fish behavior usually utilize optic and acoustic techniques. [PERSON] et al. implemented in [23] a fish behavior monitoring system that was able to monitor 9 fish tanks at the same time employing computer-vision. They evaluated stock density as a stress factor. Their system was able to be controlled remotely and provided real-time images of the fish. The obtained results showed a significant statistical difference in treatment comparison only for the experiment performed with the undamaged mesh. A survey of other existing vision-based systems for fish behavior monitoring was presented by [PERSON] et al. in [24]. They defined the two major areas of applications for optical sensors as pre-harvesting and during cultivation, and post-harvesting situations. They also performed a discussion on fish monitoring technologies such as machine vision, hyperspectral imaging, thermal imaging, and x-rays. They summarized the applications of optical sensors for fish monitoring into five types being fish sorting, fish quality, physical attributes, chemical attributes, and food security. A monitoring behavior system based on a flat passive integrated transponder antenna array was presented by [PERSON] et al. in [25]. They employed their system to record the movements of salmon shoals. Several experiments were performed employing different quantities of salmons for each test. The obtained results showed a success rate higher than 99%. Moreover, fish presented no unusual behavior to the antenna array. [PERSON] et al. employed acoustics for monitoring fish behavior, growth, and density, as described in [26]. Their experiments were performed over sardines, rockfish and sea bass deployed in tanks. They employed the scattering cross section to determine the behavior of the fish and to trig an alarm when anomalies were detected. They were able to monitor the growth-rate of the fish as well employing a first-order polynomial equation and a second-order polynomial equation. An imaging sonar referred as DIDSON (Dual-frequency Identification Sonar) was utilized by [PERSON] et al. in [27] to monitor swimming pattern and the length of Chinese sturgeons. Experiments were performed with over 2500 targets. Authors were able to find a relation between swimming pattern and body length from the obtained data.