WIRELESS SENSOR NETWORKS TO SUPPORT AN INNOVATIVE REMOTE TECHNICAL SERVICE FOR TILAPIA INTENSIVE FARMS IN CENTRAL GULF OF MEXICO.

Aquaculture in Mexico is moving from open systems to intensive land-based production systems. At a national scale tilapia demand is increasing due to recognition of nutritional value and current demand is not fully met with national production.

Intensive production systems, despite their scale, are vulnerable to operational human mistakes (mechanical, electric and biologic) which result in loss or even bankruptcy and are preventable. To prevent these events important investments are required in training, monitoring and safety equipment. It is common for tilapia producers to underestimate these risks and avoid making these investments also because there is no local technology available and imported technology is unreachable for small scale farmers.

An innovative extension service based on Wireless Sensor Networks, and software were developed to meet the demands of tilapia producers and tested conducting a 120 day trial operating a production module (three 100 cubic meter lined tanks) compared with conventional management in a similar module to prove the remote technical service prevents operational mistakes, increases energy efficiency (feed, electricity), and improves producer confidence and decision making.

The WSN monitoring station which includes water quality sensors (D.O. p.H. Temperature); voltage and electric current sensors motor actuators with a modular software to achieve the following functions: Data sampling and transmission, real time water quality monitoring, user and task administration, operation information recording (feeding, other quality parameters, biometry data), remote control of electromechanical equipment events and technical feedback. Remote technical service included permanent assessment, production indicators and operational recommendation.

The test resulted in the reduction of operational mechanic failure associated to variations in electric supply, sustained water quality, 11.7% savings on electricity, 8.5% reduction in feed consumption, increased confidence on decision making associated to real-time monitoring and access to up to date operational information indicators and expert  feedback.