This paper aims to provide an overview of the capabilities of unmanned systems to monitor and manage aquaculture farms that support precision aquaculture using the Internet of Things. The locations ...of aquaculture farms are diverse, which is a big challenge on accessibility. For offshore fish cages, there is a difficulty and risk in the continuous monitoring considering the presence of waves, water currents, and other underwater environmental factors. Aquaculture farm management and surveillance operations require collecting data on water quality, water pollutants, water temperature, fish behavior, and current/wave velocity, which requires tremendous labor cost, and effort. Unmanned vehicle technologies provide greater efficiency and accuracy to execute these functions. They are even capable of cage detection and illegal fishing surveillance when equipped with sensors and other technologies. Additionally, to provide a more large-scale scope, this document explores the capacity of unmanned vehicles as a communication gateway to facilitate offshore cages equipped with robust, low-cost sensors capable of underwater and in-air wireless connectivity. The capabilities of existing commercial systems, the Internet of Things, and artificial intelligence combined with drones are also presented to provide a precise aquaculture framework.
Flame‐induced atmospheric pressure chemical ionization (FAPCI) has been used to directly characterize chemical compounds on a glass rod and drug tablet surfaces. In this study, FAPCI was further ...applied to interface thin layer chromatography (TLC) and mass spectrometry (MS) for mixture analysis.
Methods
A micro‐sized oxyacetylene flame was generated using a small concentric tube system. Hot gas flow and primary reactive species from the micro‐flame were directed toward a developed TLC gel plate to thermally desorb and ionize analytes on the gel surface. The resulting analyte ions subsequently entered the MS inlet for detection.
Results
A 1–1.5‐mm‐wide light‐brown line was observed on the TLC plate after the desorption FAPCI/MS (DFAPCI/MS) analysis, revealing that the gel surface withstood a high temperature from the impact of the micro‐flame. Volatile and semi‐volatile chemical compounds, including amine and amide standards, drugs, and aromatherapy oils, were successfully desorbed, ionized, and detected using this TLC/DFAPCI/MS. The limit of detection of TLC‐DFAPCI/MS was determined to be 5 ng/spot for dibenzylamine and ethenzamide.
Conclusions
TLC/DFAPCI/MS is one of the simplest TLC‐MS interfaces showing the advantages such as low costs and an easy set up. The technique is useful for characterizing thermally stable volatile and semi‐volatile compounds in a mixture.
The ocean resources have been rapidly depleted in the recent decade, and the complementary role of aquaculture to food security has become more critical than ever before. Water quality is one of the ...key factors in determining the success of aquaculture and real-time water quality monitoring is an important process for aquaculture. This paper proposes a low-cost and easy-to-build artificial intelligence (AI) buoy system that autonomously measures the related water quality data and instantly forwards them via wireless channels to the shore server. Furthermore, the data provide aquaculture staff with real-time water quality information and also assists server-side AI programs in implementing machine learning techniques to further provide short-term water quality predictions. In particular, we aim to provide a low-cost design by combining simple electronic devices and server-side AI programs for the proposed buoy system to measure water velocity. As a result, the cost for the practical implementation is approximately USD 2015 only to facilitate the proposed AI buoy system to measure the real-time data of dissolved oxygen, salinity, water temperature, and velocity. In addition, the AI buoy system also offers short-term estimations of water temperature and velocity, with mean square errors of 0.021 °C and 0.92 cm/s, respectively. Furthermore, we replaced the use of expensive current meters with a flow sensor tube of only USD 100 to measure water velocity.
Imaging sonar systems are widely used for monitoring fish behavior in turbid or low ambient light waters. For analyzing fish behavior in sonar images, fish segmentation is often required. In this ...paper, Mask R-CNN is adopted for segmenting fish in sonar images. Sonar images acquired from different shallow waters can be quite different in the contrast between fish and the background. That difference can make Mask R-CNN trained on examples collected from one fish farm ineffective to fish segmentation for the other fish farms. In this paper, a preprocessing convolutional neural network (PreCNN) is proposed to provide “standardized” feature maps for Mask R-CNN and to ease applying Mask R-CNN trained for one fish farm to the others. PreCNN aims at decoupling learning of fish instances from learning of fish-cultured environments. PreCNN is a semantic segmentation network and integrated with conditional random fields. PreCNN can utilize successive sonar images and can be trained by semi-supervised learning to make use of unlabeled information. Experimental results have shown that Mask R-CNN on the output of PreCNN is more accurate than Mask R-CNN directly on sonar images. Applying Mask R-CNN plus PreCNN trained for one fish farm to new fish farms is also more effective.
Thin layer chromatography (TLC)—a simple, cost-effective, and easy-to-operate planar chromatographic technique—has been used in general chemistry laboratories for several decades to routinely ...separate chemical and biochemical compounds. Traditionally, chemical and optical methods are employed to visualize the analyte spots on the TLC plate. Because direct identification and structural characterization of the analytes on the TLC plate through these methods are not possible, there has been long-held interest in the development of interfaces that allow TLC to be combined with mass spectrometry (MS)—one of the most efficient analytical tools for structural elucidation. So far, many different TLC–MS techniques have been reported in the literature; some are commercially available. According to differences in their operational processes, the existing TLC–MS systems can be classified into two categories: (i) indirect mass spectrometric analyses, performed by scraping, extracting, purifying, and concentrating the analyte from the TLC plate and then directing it into the mass spectrometer's ion source for further analysis; (ii) direct mass spectrometric analyses, where the analyte on the TLC plate is characterized directly through mass spectrometry without the need for scraping, extraction, or concentration processes. Conventionally, direct TLC–MS analysis is performed under vacuum, but the development of ambient mass spectrometry has allowed analytes on TLC plates to be characterized under atmospheric pressure. Thus, TLC–MS techniques can also be classified into two other categories according to the working environment of the ion source: vacuum-based TLC–MS or ambient TLC–MS. This review article describes the state of the art of TLC–MS techniques used for indirect and direct characterization of analytes on the surfaces of TLC plates.
Mass spectrometric ionization methods that operate under ambient conditions and require minimal or no sample pretreatment have attracted much attention in such fields as biomedicine, food safety, ...antiterrorism, pharmaceuticals, and environmental pollution. These technologies usually involve separate ionization and sample-introduction events, allowing independent control over each set of conditions. Ionization is typically performed under ambient conditions through use of existing electrospray ionization (ESI) or atmospheric pressure chemical ionization (APCI) techniques. Rapid analyses of gas, liquid, and solid samples are possible with the adoption of various sample-introduction methods. This review sorts different ambient ionization techniques into two main subcategories, primarily on the basis of the ionization processes, that are further differentiated in terms of the approach used for sampling.
A simple and cheap design for interfacing thin layer chromatography (TLC) with electrospray ionization mass spectrometry (ESI/MS) was developed to scan and characterize compounds on TLC plate. The ...developed TLC plate was rapidly and easily modified into two sawtooth-edged pieces that were positioned on an XYZ stage so that one of the triangular tips was pointed toward the MS inlet. A drop of methanol and high DC voltage was applied at the tip to induce ESI. After the analytes in the first tip were analyzed, the TLC piece was moved so that the second triangular tip was pointed toward the MS inlet for analysis. The process was repeated until all the triangular tips on the piece were analyzed. In this manner, the analytes, no matter visible or non-visible bands, were scanned and characterized. Since a 4.8 cm long TLC track were cut to 32 triangles on two sawtooth pieces for analysis, the spatial resolution of using the sawtooth TLC-ESI/MS for analysis is 1.5 mm/band. A mixture of dye standards and Datura metel flower extract was analyzed to demonstrate the capability of sawtooth TLC-ESI/MS on scanning and characterizing chemical compounds on the TLC plates. The limits of detection of the dye standards were between 0.25 and 2.5 ng/band. TLC bands containing alkaloids such as scopolamine and norscopolamine from the Datura metel flower extract were not visualized on the developed TLC track, but were successfully detected at different triangular tips using sawtooth TLC-ESI/MS. Based on these results, the Rf values of scopolamine and norscopolamine were determined.
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•Sawtooth TLC-ESI/MS was developed to characterize a mixture.•The developed TLC plate was modified into two sawtooth-edged pieces for inducing ESI at the triangular tips.•The entire TLC track was scanned with minimal gel particle detachment during analysis.•Visualizable and non-visualizable bands were both characterized, so that their Rf information was elucidated.
Monitoring the status of culture fish is an essential task for precision aquaculture using a smart underwater imaging device as a non-intrusive way of sensing to monitor freely swimming fish even in ...turbid or low-ambient-light waters. This paper developed a two-mode underwater surveillance camera system consisting of a sonar imaging device and a stereo camera. The sonar imaging device has two cloud-based Artificial Intelligence (AI) functions that estimate the quantity and the distribution of the length and weight of fish in a crowded fish school. Because sonar images can be noisy and fish instances of an overcrowded fish school are often overlapped, machine learning technologies, such as Mask R-CNN, Gaussian mixture models, convolutional neural networks, and semantic segmentation networks were employed to address the difficulty in the analysis of fish in sonar images. Furthermore, the sonar and stereo RGB images were aligned in the 3D space, offering an additional AI function for fish annotation based on RGB images. The proposed two-mode surveillance camera was tested to collect data from aquaculture tanks and off-shore net cages using a cloud-based AIoT system. The accuracy of the proposed AI functions based on human-annotated fish metric data sets were tested to verify the feasibility and suitability of the smart camera for the estimation of remote underwater fish metrics.
This article presents a performance investigation of a fault detection approach for bearings using different chaotic features with fractional order, where the five different chaotic features and ...three combinations are clearly described, and the detection achievement is organized. In the architecture of the method, a fractional order chaotic system is first applied to produce a chaotic map of the original vibration signal in the chaotic domain, where small changes in the signal with different bearing statuses might be present; then, a 3D feature map can be obtained. Second, five different features, combination methods, and corresponding extraction functions are introduced. In the third action, the correlation functions of extension theory used to construct the classical domain and joint fields are applied to further define the ranges belonging to different bearing statuses. Finally, testing data are fed into the detection system to verify the performance. The experimental results show that the proposed different chaotic features perform well in the detection of bearings with 7 and 21 mil diameters, and an average accuracy rate of 94.4% was achieved in all cases.
Flame atmospheric pressure chemical ionization (FAPCI) combined with negative electrospray ionization (ESI) mass spectrometry was developed to detect the ion/molecule reactions (IMRs) products ...between nitric acid (HNO
3
) and negatively charged amino acid, angiotensin I (AI) and angiotensin II (AII), and insulin ions. Nitrate and HNO
3
-nitrate ions were detected in the oxyacetylene flame, suggesting that a large quantity of nitric acid (HNO
3
) was produced in the flame. The HNO
3
and negatively charged analyte ions produced by a negative ESI source were delivered into each arm of a Y-shaped stainless steel tube where they merged and reacted. The products were subsequently characterized with an ion trap mass analyzer attached to the exit of the Y-tube. HNO
3
showed the strongest affinity to histidine and formed (M
histidine
-H+HNO
3
)
–
complex ions, whereas some amino acids did not react with HNO
3
at all. Reactions between HNO
3
and histidine residues in AI and AII resulted in the formation of dominant M
AI
-H+(HNO
3
)
-
and M
AII
-H+(HNO
3
)
–
ions. Results from analyses of AAs and insulin indicated that HNO
3
could not only react with basic amino acid residues, but also with disulfide bonds to form M-3H+(HNO
3
)
n
3-
complex ions. This approach is useful for obtaining information about the number of basic amino acid residues and disulfide bonds in peptides and proteins.
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