Integration of technological solutions aims to improve accuracy, precision and repeatability in farming operations, and biosensor devices are increasingly used for understanding basic biology during livestock production. The aim of this study was to design and validate a miniaturized tri-axial accelerometer for non-invasive monitoring of farmed fish with re-programmable schedule protocols. The current device (AE-FishBIT v.1s) is a small (14 mm × 7 mm × 7 mm), stand-alone system with a total mass of 600 mg, which allows monitoring animals from 30 to 35 g onwards. The device was attached to the operculum of gilthead sea bream ( Sparus aurata ) and European sea bass ( Dicentrarchus labrax ) juveniles for monitoring their physical activity by measurements of movement accelerations in x - and y -axes, while records of operculum beats ( z -axis) served as a measurement of respiratory frequency. Data post-processing of exercised fish in swimming test chambers revealed an exponential increase of fish accelerations with the increase of fish speed from 1 body-length to 4 body-lengths per second, while a close relationship between oxygen consumption (MO 2 ) and opercular frequency was consistently found. Preliminary tests in free-swimming fish kept in rearing tanks also showed that device data recording was able to detect changes in daily fish activity. The usefulness of low computational load for data pre-processing with on-board algorithms was verified from low to submaximal exercise, increasing this procedure the autonomy of the system up to 6 h of data recording with different programmable schedules. Visual observations regarding tissue damage, feeding behavior and circulating levels of stress markers (cortisol, glucose, and lactate) did not reveal at short term a negative impact of device tagging. Reduced plasma levels of triglycerides revealed a transient inhibition of feed intake in small fish (sea bream 50–90 g, sea bass 100–200 g), but this disturbance was not detected in larger fish. All this considered together is the proof of concept that miniaturized devices are suitable for non-invasive and reliable metabolic phenotyping of farmed fish to improve their overall performance and welfare. Further work is underway for improving the attachment procedure and the full device packaging.

 AEFishBIT provides simultaneous measures of fish respiration and locomotion.  Device measures highlight species differences in anatomical and locomotor features.  Coupling of activity and respiration rhythms emerges as fish performance indicator.

In this paper, we present the design of a practical underwater sensor network for offshore fish farm cages. An overview of the current structure of an offshore fish farm, applied sensor network solutions, and their weaknesses are given. A mixed wireless–wired approach is proposed to mitigate the problem of wire breakage in underwater wired sensor networks. The approach is based on the serial arrangement of identical sections with wired and wireless interconnections areas. Wireless section alleviates underwater maintenance operations when cages are damaged. The analytical model of the proposed solution is studied in terms of maximum power transfer efficiency and the general formulas of the current in their transmitting antennas and sensor nodes are provided. Subsequently, based on simulations, the effects of parasitic resistance across the network are evaluated. A practical underwater sensor network to reach the 30 m depth with sensor nodes distanced 6 m is used to determine the proposal compliance with the ISO 11784/11785 HDX standard in its normal operation. Taking into account the cable breakage scenario, the results from experiments demonstrate the robustness of the proposed approach to keep running the sensor nodes that are located before the short circuit. Sensor node run time is reduced only 4.07% at most using standard values when a cable breakage occurs at the second deepest section.

The biosensor technology has the potential to revolutionize the aquaculture industry, but the selection of tagging method, operational mode (stand-alone vs. wireless systems) and telemetry technology ultimately depends on living species, life stage and research question. In particular, AEFishBIT is a small and stand-alone device composed of a triaxial accelerometer, a microprocessor, a battery, and a RFID tag that was designed to be externally attached to the operculum. This unique location serves to provide simultaneous measurements of activity patterns (signals of x-and y-axes) and respiratory frequency (z-axis signal) processed by on-board algorithms. The validity of measurements was initially proved in exercised fish in a swim tunnel respirometer, and its use as a reliable tool for the individual monitoring of whole-organism traits in freeswimming gilthead sea bream was tested then in fish facing a wide range of biotic and abiotic stressors. The impact of the tagging method, based on the use of monel piercing fish tags with a flexible heat shrink polyethylene ring, was also evaluated and no signs of growth impairment, operculum damage or gill lamellae haemorrhage were found 10 days post-tagging. The autonomy of the device was 6 hours of continuous recording with re-programmable lag times and recording schedules of 2 min windows at regular intervals along the experimental period (2-8 days). Such procedure underlined a negative linear correlation between fasting weight loss and operculum breaths, becoming respiratory frequency a reliable indicator of basal metabolic rates. Biosensing signals also highlighted the more continuous physical activity and increased respiratory rates of young fish when comparisons were made between one-and three-year old fish. Also, AEFishBIT measurements evidenced a generalized increase of respiratory frequency during severe hypoxia (2-3 ppm), but the individuals classified as proactive fish also shared an increased physical activity for supporting escape reactions in a milieu with low oxygen availability. Likewise, we also observed an overall increase of physical activity with the decrease of tank space availability, which can contribute to establish stricter criteria of welfare in farmed fish. Finally, the reduction of respiratory frequency was a consistent diagnostic marker of the progression of parasitic enteritis in experimentally infected fish with the myxozoan Enteromyxum leei. Altogether, this work constitutes the proof of concept of the use of biosensor technology as a reliable tool for individual fish phenotyping of whole-organism traits in farmed fish, contributing to improve animal welfare and productivity of aquaculture industry.

The advanced development of sensor technologies has led to the emergence of fish biosensors that are currently used for research and commercial purposes. AEFishBIT is a miniaturized biosensor attached to fish operculum that measures physical activity and respiration frequencies. In this study, we determined the effect of the tagging method and evaluated the use of this biosensor to monitor post-smolt Atlantic salmon in a tank-based system. The use of piercing fish tag had a negative impact on the gills and operculum, unlike the identical protocols used in gilthead sea bream and European sea bass. In contrast, a surgical thread did not show any apparent tissue damage. Two data recording schedules were considered to monitor immediate early reaction to fish handling and light regime changes (records every 15 min over 2 days) or adaptation to new light conditions (records every 30 min over 4 days). Data showed stabilization of physical activity 8 h post-tagging, with different steady states for the activity/respiratory ratio after changes in light intensity that reflected a different time course adaptation to new light conditions. High correlations were observed between AEFishBIT and video recording data. These findings supported the use of AEFishBIT as a promising tool for smart sensing of Atlantic salmon.

In this paper, we present a novel charging method for underwater batteryless sensor node networks. The target application is a practical underwater sensor network for oceanic fish farms. The underwater sections of the network use a wireless power transfer system based on the ISO 11784/11785 HDX standard for supplying energy to the batteryless sensor nodes. Each sensor has an accumulator capacitor, which is charged for voltage supplying to the sensor node. A new distributed charging scheme is proposed and discussed in detail to reduce the required time to charge all sensor nodes of the underwater sections. One important key is its decentralized control of the charging process. The proposal is based on the self disconnection ability of each sensor node from the charging network. The second important key is that the hardware implementation of this new feature is quite simple and only requires to include a minimal circuitry in parallel to the current sensor node antenna while the rest of the sensor network remains unaltered. The proposed charging scheme is evaluated using real corner cases from practical oceanic fish farms sensor networks. The results from experiments demonstrate that it is possible to charge up to 10 sensor nodes which is the double charging capability than previous research presented. In the same conditions as the approach found in the literature, it represents reaching an ocean depth of 60 m. In terms of energy, in case of an underwater network with 5 sensors to reach 30 m deep, the proposed charging scheme requires only a 25% of the power required using the traditional approach.

A blood pressure sensor suitable for wireless biomedical applications is designed and optimized. State-of-the-art blood pressure sensors based on piezoresistive transducers in a full Wheatstone bridge configuration use low ohmic values because of relatively high sensitivity and low noise approach resulting in high power consumption. In this paper, the piezoresistance values are increased in order to reduce by one order of magnitude the power consumption in comparison with literature approaches. The microelectromechanical system (MEMS) pressure sensor, the mixed signal circuits signal conditioning circuitry, and the successive approximation register (SAR) analog-to-digital converter (ADC) are designed, optimized, and integrated in the same substrate using a commercial 1 μm CMOS technology. As result of the optimization, we obtained a digital sensor with high sensitivity, low noise (0.002 μV/Hz), and low power consumption (358 μW). Finally, the piezoresistance noise does not affect the pressure sensor application since its value is lower than half least significant bit (LSB) of the ADC.

Purpose -Nowadays, in order to improve current applications, industry incorporates to their solution approaches artificial intelligence techniques and methodologies like Fuzzy Logic, neural networks and/or genetic algorithms (GA). Artificial intelligence techniques complement classical methodologies and include concepts that simulate the way humans solve problems or how processes work in nature. In this work, the Fuzzy Logic system cancels the effects of load perturbances in an energy plant, by implementing a secondary controller which complements the main controller. The purpose of this paper is to use GA to tune this new secondary controller. The authors particularize the proposal for three specific applications: control the angular speed and position of a Direct Current (DC) motor and control the output voltage of a DC/DC buck converter. Design/methodology/approach -The authors use GA for tuning a Proportional-Integral Fuzzy Controller (PI-Fuzzy). The proposal defines a new objective function in comparison with literature approaches. The main key in the new objective function is combining the best features of Integral Square Error (ISE) function and taking out the overshoot response. Findings -In order to demonstrate the proposed methodology based on GA tuning a PI-Fuzzy, the authors apply the literature benchmark to the solution. The results are compared with the following techniques: Robust control, continuous PID control, discrete PID control, Optimal Control, Fuzzy Control and Artificial Neural Network based control. Comparisons are presented in terms of setting time and overshot. Originality/value -Results demonstrate that ISE or integral of absolute value of error function do not provide the desired response. Achieved results demonstrate the usefulness of the proposal to eliminate the overshoot of the traditional behaviour without lost any of the main features of the literature methodologies.