Abstract: An aquavoltaic system and an aquavoltaic method applied to the aquavoltaic system are provided. The aquavoltaic system comprises a fish pool, a photovoltaic power generation assembly, and a power storage assembly; a power-consuming device comprises a detection unit, a water quality regulating unit and a power regulator that are arranged in the fish pool; and an electric energy output end of the photovoltaic power generation assembly is connected to an electric energy input end of the power-consuming device via a first circuit, the electric energy output end of the photovoltaic power generation assembly is connected to an electric energy input end of the power storage assembly via a third circuit, the electric energy input end of the power-consuming device is connected to an electric energy output end of the power storage assembly via a fifth circuit, and a fifth switch is arranged on the third circuit.

Abstract: Provided are a method, system and device for classifying feeding intensity of fish school, relating to the field of aquaculture. The method includes: extracting features of an audio clip to be detected to determine a Mel spectrum-based fish school feeding depth speech spectrum feature vector, a CQT-based fish school feeding depth speech spectrum feature vector, and an STFT-based fish school feeding depth speech spectrum feature vector; fusing the Mel spectrum-based fish school feeding depth speech spectrum feature vector, the CQT-based fish school feeding depth speech spectrum feature vector and the STFT-based fish school feeding depth speech spectrum feature vector to generate a fused feature spectrogram; and inputting the fused feature spectrogram into a deep convolutional neural network model constructed by historical audio clips corresponding to different types of feeding intensities to determine a feeding intensity type corresponding to the audio clip to be detected.

Abstract: The disclosure provides a sensor fault diagnosis method, an apparatus, an electronic device and a storage medium. The method comprises: determining target concentration of electrolyte in a sensor at time t; determining residual concentration based on initial concentration and the target concentration of the electrolyte; acquiring an impedance value and determining a concentration measurement value based on the impedance value and correlation information between concentration and the impedance; determining fault information of the sensor based on the residual concentration and the concentration measurement value.

Abstract: A vibration self-generating battery of a water quality low-power sensor applicable to multiple scenarios, belonging to the technical field of self-generating energy supply. The battery includes a positive electrode magnetic cap, a battery outer cylinder, a negative electrode magnetic cap, a circuit module, a supporting component, an electromagnetic induction generating unit, and a friction nano generating unit. The positive electrode magnetic cap is arranged on the upper side of the battery outer cylinder, and the negative electrode magnetic cap is arranged at the lower side of the battery outer cylinder. The friction nano generating unit is arranged close to an inner wall of the battery outer cylinder. The electromagnetic induction generating unit is arranged at the center of the battery, and the supporting component and the circuit module are arranged below the electromagnetic induction generating unit in turn.

Abstract: The present disclosure provides an early warning method, apparatus, and system for a nitrogen concentration in industrialized aquaponic circulating water. The early warning method includes: obtaining video data of a sensitive fish farming container, where the video data includes a monitored movement behavior of a sensitive fish in the sensitive fish farming container, and the sensitive fish farming container is in communication with a farming pond of an aquaponic system; processing the video data using an object detection model and obtaining a behavior activity of the sensitive fish according to a processing result; processing the behavior activity using a neural network model to obtain a nitrogen concentration grade of the farming pond of the aquaponic system; and determining whether to send nitrogen concentration early warning information based on the nitrogen concentration grade.

Abstract: A water quality early warning system and method for aquaponics based on zebrafish behavior analysis is provided. The system includes a monitoring chamber, an infrared transceiver array, a signal driving and collecting board and a processor, where the infrared transceiver array includes infrared transceiver modules; each infrared transceiver module includes an infrared transmitting module and an infrared receiving module; the signal driving and collecting board is connected to the infrared transceiver array, and configured to drive the infrared transmitting module to transmit infrared light, collect induced currents generated by the infrared receiving module and generate a voltage matrix in M rows and N columns according to induced currents; the processor is connected to the signal driving and collecting board, and configured to calculate motion parameters of the target zebrafish according to the voltage matrix, and perform an early warning on a water quality of the target water body.

Abstract: The present disclosure relates to the technical field of growth environment control for plants, and provides a light regulation method, system, and apparatus for a growth environment of leafy vegetables. The method includes: obtaining a growth environment image and growth environment light parameters of leafy vegetables; inputting the growth environment image into an image segmentation model to obtain an initial pixel segmentation map; determining a leaf area of the leafy vegetables according to the initial pixel segmentation map by using a Class Activation Mapping (CAM)-K algorithm; inputting the leaf area and the growth environment light parameters of the leafy vegetables into a leafy vegetable growth index prediction model to obtain a growth index of the leafy vegetables; adjusting the growth environment light parameters according to the growth index of the leafy vegetables. This disclosure achieves automated and intelligent control of light conditions in the growth environment of leafy vegetables.

Abstract: The present disclosure relates to the technical field of aquafarm monitoring, and in particular to a method, system and apparatus for intelligently monitoring an aquafarm with multi-dimensional panoramic perception. The method includes: analyzing preprocessed multi-dimensional panoramic perception information with time series analysis to obtain a linear fitting model; constructing a water quality forecasting-alarming model according to the linear fitting model; inputting fused data to a convolutional neural network (CNN) for training to obtain an electrical device fault diagnosis model; and monitoring an aquafarm with the water quality forecasting-alarming model and the electrical device fault diagnosis model.