Design and deployment of wireless sensor networks for aquaculture monitoring and control based on virtual instruments

Aquaculture is moving toward an intensive controlled environment production with a significant increase in production, but at a cost of increased risk of catastrophic loss due to equipment or management failures. In addition, managers of intensive production facilities need accurate, real-time information on system status and performance in order to maximize their potential. This work has developed and deployed low cost short-range modules of wireless sensor network based on ZigBee standard and virtual instruments technology in order to monitor and control an aquaculture system in real time. The system consists of smart sensor nodes, coordinator/gateway node and personal computer (PC). The smart sensor nodes monitor environmental parameters such as dissolved oxygen, water temperature, pH and water level using relevant sensors, transmit this information to the coordinator/gateway node through ZigBee network and receive control signals for actuator control. The coordinator/gateway node receives data acquired and sends command to PC in order to achieve human-computer visualization interface. The graphical user interface (GUI) was designed by LabWindows/CVI software platform so that users can observe, investigate and analyze the related scientific and accuracy of parameters in aquaculture environment. We have implemented our method for two sensor network nodes deployed in fish ponds and monitored the results for six months indicating that the power management and networking solutions adopted to work in practice, lead to maximize monitoring, control as well as the recording of the aquaculture system. It effectively reduces the probability of high risk of fish mortality through enabling constant monitoring of the critical parameters in the aquaculture environment. This situation in effect increases economic benefit for aquaculture, consumer confidence and safety while reducing labor cost and energy consumption. (C) 2014 Elsevier B.V. All rights reserved.