Aquarium management system and computer implementation method thereof for determining aquatic environment quality

Abstract

The invention provides an aquarium management system and an implementation method thereof, and the system comprises a video module which is used for capturing video data, and the video data is composed of a series of frames which can display a water environment containing one or more life bodies; the sensing module is used for detecting one or more conditions of the water environment; an identification module for identifying visual features of one or more life entities from one or more frames of the video data; and an analysis module for analyzing the detected one or more water environment conditions and identifying visual features of the one or more life entities, thereby determining the quality of the water environment.

Description

Technical Field

[0001] The present invention relates to an aquarium management system and a computer-implemented method for determining the quality of an aquatic environment in an aquarium. The present invention is not limited thereto, but relates to an aquarium management system that can determine and control the quality of an aquatic environment in an aquarium based on artificial intelligence technology. Background Art

[0002] Aquariums provide artificial habitats for aquatic animals and plants and are widely used in home and commercial settings. In most aquarium environments, an aquarium usually includes a water storage container for raising fish and / or other aquatic animals and plants, an air pump and water filter to create water circulation, and landscape decorations to enhance the visual appeal of the aquarium. Aquariums can be used not only for leisure, but also for protecting or cultivating aquatic animals, as well as for educational purposes.

[0003] As we all know, most aquatic plants and animals are very sensitive to the aquatic environment they live in, and their health is easily affected by environmental changes such as water temperature and water quality. Any ecological imbalance may have an adverse effect on the health and growth of aquatic organisms, and may even endanger the lives of aquatic plants and animals.

[0004] However, maintaining an aquarium to provide a suitable environment for aquatic life is often complex, time-consuming and labor-intensive. In addition to regularly cleaning the aquarium and feeding the aquatic animals, keepers usually need to have various skills and experience to manage the ecology of the aquarium. Therefore, aquarium keepers use different methods to maintain and monitor the ecological conditions of the aquarium. For example, the color of the water in the tank is regularly checked by observation to monitor the water quality. Other equipment or tools such as pH test strips can also be used to detect the pH value to estimate the level of waste in the water, which may be caused by the excrement and / or uneaten food of the aquatic animals. Related detection systems have been developed, such as devices that automatically feed and / or filter water. Despite this, we still hope that there will be more effective and efficient systems to automatically manage the aquatic environment ecology of the aquarium.

[0005] Purpose of the Invention The object of the present invention is to provide a novel aquarium management system capable of determining the quality of an aquatic environment.

[0006] Another object of the present invention is to provide a novel aquarium system that is capable of determining and controlling and managing the quality of the aquatic environment.

[0007] It is another object of the present invention to provide a computer implemented method for determining and controlling and managing the quality of the aquatic environment of an aquarium system.

[0008] It is another object of the present invention to alleviate or avoid to some extent one or more of the problems associated with known aquariums, or at least provide a useful alternative.

[0009] The above-mentioned object is achieved by the feature combination of the main claim; the dependent claims reveal further advantageous implementations of the present invention.

[0010] Those skilled in the art may also derive other objects of the present invention from the following description. Therefore, the above object statements are not exhaustive, but are only intended to illustrate some of the numerous objects of the present invention. Summary of the invention

[0011] In a first aspect, the present invention provides an aquarium management system. The aquarium management system includes a video module for capturing video data, the video data consisting of a series of frames that can show a water environment containing one or more life forms; a sensor module for detecting one or more conditions of the water environment; a recognition module for identifying visual features of one or more life forms from one or more frames of the video data; and an analysis module for analyzing the detected one or more water environment conditions and identifying the visual features of one or more life forms, thereby determining the quality of the water environment.

[0012] In a second aspect, the present invention provides a computer-implemented method for determining the quality of a water environment of an aquarium system. The method comprises the following steps: capturing video data by a video module, the video data consisting of a series of frames showing a water environment containing one or more life forms; detecting one or more conditions of the water environment by a sensing module; identifying one or more visual features of the life forms from one or more frames of the video data by a recognition module; and analyzing the detected one or more conditions of the water environment and the identified one or more visual features of the life forms by an analysis module to determine the quality of the water environment.

[0013] In a third aspect, the present invention provides a non-transitory computer-readable medium storing machine-readable instructions which, when executed on a processor, can implement the method steps of the second aspect.

[0014] In a fourth aspect, the present invention provides an aquarium management system, comprising a memory for storing data and a processor for executing computer-readable instructions, wherein the processor is configured to implement the method of the second aspect when executing the computer-readable instructions.

[0015] The summary of the invention does not necessarily disclose all features necessary to define the invention; the invention may consist in various sub-combinations of the disclosed features. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] The above and further features of the present invention will become apparent from the following description of preferred embodiments, which are provided by way of example only with reference to the accompanying drawings, in which: Figure 1 is a schematic diagram of an aquarium equipped with an aquarium management system designed according to one embodiment of the present invention; Figure 2 yes Figure 1 A block diagram of the aquarium management system; and Figure 3 shows Figure 1 Flow chart of a computer-implemented method for evaluating water environmental quality in an aquarium system. DETAILED DESCRIPTION

[0017] The following describes preferred embodiments by way of example only and does not limit the feature combinations required to implement the present invention.

[0018] The "one embodiment" or "an embodiment" mentioned in this specification means that the specific features, structures or characteristics related to the embodiment are included in at least one embodiment of the present invention. The phrase "in one embodiment" appearing in different places in the specification does not necessarily refer to the same embodiment, and separate or alternative embodiments are not mutually exclusive with other embodiments. In addition, various features described in the specification may be exhibited in some embodiments but not in other embodiments. Similarly, various requirements described in the specification may be requirements of some embodiments but not in other embodiments.

[0019] It should be understood that the elements shown in the figure can be implemented by various forms of hardware, software or a combination thereof. It is preferred to implement these elements by a combination of hardware and software on one or more appropriately programmed general-purpose devices, which may include a processor, a memory and an input / output interface.

[0020] This description illustrates the principles of the invention. It will therefore be appreciated that those skilled in the art will be able to design various arrangements that, although not explicitly described or shown herein, embody the principles of the invention and are included within the spirit and scope of the invention.

[0021] In addition, all statements relating to the principles, aspects and embodiments of the present invention herein, as well as specific embodiments of the present invention, are intended to cover equivalents of their structures and functions. In addition, these equivalents include currently known equivalents and equivalents developed in the future, that is, any developed solution that performs the same function regardless of its structure.

[0022] Thus, for example, it will be appreciated by those skilled in the art that the block diagrams presented herein are merely conceptual views of the systems illustrative of the principles of the present invention.

[0023] The functions of the various elements shown in the figures may be implemented by dedicated hardware as well as hardware capable of executing software in combination with appropriate software. When provided by a processor, these functions may be provided by a single dedicated processor, a single shared processor, or multiple independent processors, some of which may be shared. In addition, the explicit use of the word "processor" should not be interpreted as only hardware capable of executing software, it may also implicitly include, but is not limited to, digital signal processor ("DSP") hardware, read-only memory ("ROM") for storing software, random access memory ("RAM"), and non-volatile storage.

[0024] In the claims of the present invention, any expression of "a method for performing a specific function" is intended to cover any way of performing the function, including, for example: a) a combination of circuit components that perform the function, or b) software in any form, including firmware, code, or similar methods, combined with appropriate circuits to execute the software to achieve the relevant function. The purpose of the present invention as defined by the relevant claims is to combine the functions provided by the various means in the manner required by the claims. Therefore, any means that can provide these functions are deemed to be equivalent to the scheme of the present invention.

[0025] The present invention relates to an aquarium management system and a computer-implemented method thereof for determining, managing and controlling the quality of an aquatic environment. In particular, but not limited to, the aquarium system of the present invention is capable of determining the quality of an aquatic environment in near real time, detecting through artificial intelligence (AI) technology, the suitability of the environment for aquatic organisms based on the integrated perception of one or more conditions of the aquatic environment, and determining one or more behavioral patterns of life forms in the aquatic environment based on the visual characteristics of the life forms. Therefore, the present invention can provide an intelligent aquarium setting for monitoring and managing the quality of an aquatic environment in near real time, thereby maintaining an ecological environment suitable for the survival of aquatic organisms. The present invention can further automatically control, adjust and / or modify various factors of the aquatic environment based on the detected quality of the water environment. The user can choose to receive the detected water quality report in the form of an alarm signal, which can be transmitted to various computer devices, including but not limited to portable mobile devices such as smartphones and smart watches, computer devices such as desktop and laptop computers, and / or general or customized alarms depending on the specific application. The present invention provides an automated aquarium management system for efficient, effective and reliable control and maintenance of an aquatic environment to improve the health of the life forms kept.

[0026] refer to Figure 1, the figure shows an aquarium 10 of an embodiment of the aquarium management system 100 of the present invention. The aquarium 10 generally may include a water storage tank 2 for raising aquatic plants and animals such as fish and water plants. The aquarium 10 may be equipped with some devices or equipment for maintaining the conditions of the aquarium 10, such as but not limited to a lighting device 3 such as a light emitting diode (LED) lighting, a water pump 4, and a filtering device 5. Other components and assemblies of the aquarium management system 100 will be further discussed below.

[0027] Figure 2 A block diagram of an aquarium management system 100 according to an embodiment of the present invention is shown. Figure 3 Further shown are method steps for system 100 to determine the quality of a water environment.

[0028] The system 100 may be connected to one or more computer processing devices 101, such as but not limited to a smartphone, tablet computer, laptop computer, personal computer (PC) or similar device, and any suitable data or signal processing device or system may be used. The system 100 may also be connected to any common or customized alarm system 102 to provide visual and / or audible alarms to the user. The computer processing device 101 and / or the alarm system 102 allow the user to receive reports and / or alarm signals from the system 100 when the system 100 detects that the water environment quality of the aquarium 10 is not up to standard. In one embodiment, the system 100 may be configured to connect to the computer processing device 101 and / or the alarm system 102 via a communication network (which may include a router 220) to connect to a local server and / or a remote database 300 (such as a cloud database 300 or similar device) for transmitting and storing data. In another embodiment, the communication network may include a wireless network, such as a wireless cellular network, a wired network, the Internet, or any combination of the above networks.

[0029] The system 100 may include a plurality of functional modules for performing various functions. In the illustrated embodiment, the system 100 includes a video module 110 for capturing video data. The video data may include one or more videos, consisting of a series of frames, showing the water environment of the aquarium 10 containing one or more life forms. The life forms may include animals such as aquatic microorganisms, fish, and / or plants such as water plants. In one embodiment, the video module 110 may include one or more cameras 30, preferably two or more cameras 30, to capture videos of the aquatic environment from different directions, thereby capturing the life forms living therein in an all-round and three-dimensional manner.

[0030] The system 100 may also include a sensor module 120 for detecting one or more conditions of the water environment. In one embodiment, the sensor module 120 may include one or more sensor devices, including Internet of Things (IoT) devices, such as but not limited to one or more temperature sensors 6, color sensors 7, pH sensors 8, chemical sensors 9 (such as ammonia sensors 9), turbidity sensors 11, conductivity sensors 12, pressure sensors 13, dissolved oxygen sensors 14, water level sensors 15, and leak sensors 18. The sensor module 120 is suitable for detecting one or more conditions of the water environment, which may include but are not limited to temperature, pH, ammonia level, water color, water turbidity, water conductivity, water pressure, oxygen level, etc. For example, the color sensor 7 and the turbidity sensor 11 can be used to monitor the color change of the water in the aquarium 10, which may be related to the overgrowth of unnecessary algae or bacteria, or the unconsumed food left over due to overfeeding. The water level sensor 15 can be used to determine the water level in the tank 2 to ensure that the aquarium 10 is provided with an appropriate amount of water. The pH sensor 8 may be used to monitor the pH of the water, as fluctuations in pH may cause stress to aquatic animals and plants, reducing their ability to resist disease. Chemical sensors 9, such as ammonia sensors 9, may be used to determine waste levels in the water, which may be caused by animal excrement, unconsumed food, and / or decaying plants. Temperature sensors 6 may be used to measure the temperature of the water in the aquarium 10. Water pressure sensors 13 may be used to determine the pumping speed of the water pump 5 and whether the water flow rate is appropriate. Conductivity sensors 12 may be used to measure the electrical conductivity (EC) of the water in the aquarium 10. Conductivity readings are important for assessing the concentration of dissolved ions, as different aquatic animals generally tend to live in water with different optimal conductivity values. For aquariums that house a variety of aquatic animals, it is recommended to maintain an appropriate conductivity range to ensure that ionic conditions are suitable for all animals. Changes in conductivity values ​​may reflect the presence of excessive impurities in the water.

[0031] When the sensor module 120 detects various conditions of the water environment, the detection data will be transmitted to the analysis module 150, which may include or provide a processor 200 as a component, which runs software based on artificial intelligence (AI). The software based on artificial intelligence can process any input data, such as detection data from the sensor module 120, and / or based on any previously detected stored data. The previous data can be stored in a memory 210 or a database 310 located in a local server 300 and / or a remote cloud network 300. The software based on artificial intelligence may include, but is not limited to, one or more machine learning and / or data analysis programs or algorithms. In one embodiment, if the sensor module 120 detects that any one or more conditions of the water environment exceed a predetermined optimal range set for each sensor, such as below a predetermined lower threshold or above a predetermined upper threshold, the relevant data will be processed by the software and the processing results will be reported to the user. The execution module 160 may also perform one or more corresponding operations to adjust, modify or correct an undesirable condition.

[0032] The system 100 may also include an identification module 130 for identifying one or more visual features of lifeforms in the aquarium 10 from one or more frames collected from the captured video data. Similar to the analysis module 150, the identification module 130 may include or provide a processor 200 as a component, which runs artificial intelligence (AI) based software. In one embodiment, the one or more visual features of the lifeforms may include one or more of the size, color, shape, texture, position, direction and / or location of the lifeforms in one or more frames of video data. The identification or extraction of the visual features of the lifeforms may be processed using artificial intelligence based software, which may include but is not limited to any known computer vision program or algorithm. The computer vision algorithm may process any input video data, such as data captured by the video module 110 and / or any previous data stored in the memory 210 and / or database 310 on the local server 300 or the remote cloud network 300. By processing the identified data based on the computer vision algorithm, one or more aquatic animals may be individually identified and located. If multiple lifeforms are detected, the computer vision algorithm may further identify possible reactions of the lifeforms to avoid confusing detection. Responses from the same identified organism will be ignored and their features will not be processed further.

[0033] The recognition module 130 can derive one or more behavior patterns of the detected life form based on the one or more identified visual features. For example, the behavior pattern of the life form may include one or more of the following behaviors: swallowing air, staying on the water surface, staying at the bottom of the water tank, not eating, swimming irregularly, swimming backwards, accelerating or decelerating, jumping out of the water, lack of energy, spasms, biting other life forms in the water tank, swimming unsteadily, slow response to stimulation, friction with other objects and / or life forms in the water tank, etc. The recognition module 130 transmits the detection data including the visual features and / or the derived behavior pattern to the analysis module 150, and the analysis module uses artificial intelligence software to process based on the detected data and / or stored previous data to determine whether the derived behavior pattern is abnormal. If a behavior that deviates from the standard or normal behavior pattern is found (learned based on previous data and / or the user's preset instructions), it will be further processed by the analysis module 150 and reported to the user.

[0034] Then, the analysis module 150 will analyze one or more conditions of the water environment detected by the sensing module 120, and one or more visual features and / or behavioral patterns of the life form identified by the recognition module 130 to determine the quality of the water environment, thereby evaluating the survival suitability of the life form. Preferably, the analysis module 150 further analyzes the detected water environment conditions and the identified life form visual features, based on previous data stored in one or more databases 310, and by processing artificial intelligence-based algorithms, the analysis module is able to continuously learn from the data received from the sensing module 120 and / or the recognition module 130. For example, the database 310 can be configured to store one or more data, such as video data captured by the video module 110, one or more visual features of the life form identified by the recognition module 130, one or more conditions of the water environment detected by the sensing module 120, and / or the quality of the water environment determined by the analysis module 150. The data from the database 310 can be used to train artificial intelligence algorithms, including one or more computer vision algorithms, machine learning algorithms, and / or data analysis algorithms, to further improve the speed and accuracy of the system 100. Therefore, the analysis module 150 analyzes the detected conditions by associating them with the characteristics and / or behaviors of the identified life forms, thereby evaluating whether the water environment has changed and how these changes have affected or may affect the ecology of the water environment. In addition, based on the previously collected data, if the determined water environment quality deviates from the recommended or preset level, the artificial intelligence algorithm may further recommend adjustments or modifications to the detected conditions. Such adjustments or modifications can be manually implemented by the user, after the user receives a report or alarm signal from the system 100, or automatically implemented by the execution module 160 of the system 100.

[0035] As long as the system 100 is turned on, the detection and analysis data is continuously transmitted to and stored in the database 310 of the local and / or cloud server 300. Individual life forms in the aquarium 10 will be identified and their instantaneous positions at any time will be determined. Relevant behavioral patterns of the life forms will also be derived and abnormal conditions will be evaluated. The behavioral patterns will be processed according to any preset instructions and / or past collected data and associated with the condition data detected by the sensing module 120. In addition, the detected position can be used to calculate relevant parameters such as the speed, acceleration and / or direction of movement of the life form, which can be used to determine the health status of the life form by comparing the current data with past data at different time periods using machine learning techniques. If certain life forms are detected to be in an undesirable or unhealthy state, relevant information will be immediately reported to the user. Based on the video data collected over time by the video module 110 and the sensing module 120, the system 100 can determine whether the correlation between the water environment and the life forms is undesirable or becoming undesirable so that appropriate actions can be taken in a timely or advance manner to resolve, prevent and / or correct these conditions.

[0036] While the sensing module 120 is used to detect various conditions of the water in the aquarium 10, the artificial intelligence-based software of the system 100 can further assist in monitoring the operation of the sensing module 120, in particular, continuing to adjust and optimize the set detection data set ranges of the various sensing devices. Data analysis and machine learning algorithms are implemented not to evaluate a specific aspect of the water condition, but to evaluate the overall environmental condition of the water environment. Through continuous learning based on current and past data, the system 100 can be configured to predict any possible deviations in future water environment parameters. For example, if any condition data measured from the sensing module 120 shows a deviation from a predetermined optimal range, potential problems that may occur in the water environment can be predicted and the user can be alerted in advance. For example, an alert signal in the form of a buzzer alarm, text message and / or email can be sent to the user's mobile phone and / or computer device 101. The computer device 101 may also be used to access data stored in a local and / or remote database 310, and / or control or adjust settings of the video module 110, the sensor module 120 and / or the execution module 160 through a developed computer platform and / or mobile application.

[0037] Preferably, the execution module 160 is designed to automatically adjust or modify one or more conditions of the water environment according to the water environment quality determined by the analysis module 150. In one embodiment, the execution module 160 may include one or more devices, such as a feeding device 19, a lighting device 3, a cooling device 17, a heating device 16, a water level controller 20, a water pump 5, a chemical dispenser 21, a filter 5 and / or a timer 22. One or more of these execution devices can be used to change the detected water environment conditions, and the adjustment or modification can be performed manually by the user and / or automatically by the system 100.

[0038] Those skilled in the art will appreciate that the present invention should not be limited to the specific embodiments described and illustrated. For example, those skilled in the art will appreciate that the video module 110, the sensor module 120, and the execution module 160 may include other IoT devices or types of devices, as long as these devices operate to perform the module functions as claimed.

[0039] The present invention provides an aquarium management system for controlling and maintaining the water environment of an aquarium to improve the health of life forms therein. In particular, but not limited to, the system of the present invention can determine the quality of the water environment in near real time to determine whether the environment is suitable for aquatic life. The system operates by comprehensively sensing one or more conditions of the water environment and determining one or more behavioral patterns of life forms in the water environment based on visual characteristics of the life forms detected and analyzed using artificial intelligence (AI) technology. Based on real-time acquired data and data collected in the past, the present invention can predict any problems that may occur in the water environment so that adjustments, modifications or corrective measures can be taken early.

[0040] In addition to determining the quality of the aquarium water environment, the AI ​​algorithm can further infer or determine information related to the aquarium water environment and the life within it. This information may include, but is not limited to: •How much swimming does each aquatic animal do in 24 hours? •When are animals most or least active during the day? •Does each animal have the same activity period? • Do some animals swim more frequently than others? If so, how much more frequently? •Which animal is the most active and which animal is the least active? • Do some animals swim faster than others? Which are the fastest and slowest swimmers? •How fast does each animal accelerate or decelerate? •Can an animal maintain a constant swimming speed for a period of time? If so, for how long can the animal maintain a constant swimming speed? •How do aquatic animals sleep? •Do all aquatic animals sleep by moving or not moving their bodies? •Do some animals sleep more frequently than others? •Is movement speed a marker for sleep patterns in aquatic animals? •Do all fish swim backwards? •How often do fish turn? •Is it possible for aquatic animals to collide with each other? •Is there a relationship between fish size and swimming speed or frequency? •Is there a relationship between the activity of aquatic animals and water temperature? •Does each animal have a preferred spot in the tank? • Do some animals eat more than others? If so, how much more? This information may be useful for education and / or research.

[0041] The computer system 100 may also include a memory 21 for storing machine-readable instructions. The computer system 100 also includes a processor 22 configured to execute machine-readable instructions to implement the method of the present invention, which will be described in more detail below. The memory for storing machine-readable instructions and the processor for executing the instructions together constitute the system 100. It should be understood that the system 100 may include multiple components that are connected to a local server and / or a network 300 to implement the method of the present invention. It should also be understood that the system 100 can be implemented by an appropriate computer device 110, that is, by downloading appropriate software to the computer device 110. Although the video module 110, the sensor module 120, the recognition module 130, the analysis module 150 and / or the execution module 160 are shown as functional components of the system 100, according to the concept of the present invention, this deployment configuration is not limited thereto. For example, one or more of these modules can be deployed as a corresponding functional module independent of the system 100 but connected to the system 100. One or more modules may be independently implemented using logic circuits and / or executable code / machine readable instructions stored in the memory 210 of the system 100, and executed by the processor 200 to implement the functions described herein. For example, the executable code / machine readable instructions may be stored in one or more memories 210, such as random access memory (RAM), read-only memory (ROM), flash memory, magnetic storage, optical storage, etc., to store one or more instruction sets, such as application software, firmware, operating system, applets, etc., data, such as configuration parameters, operating parameters and / or thresholds, collected data, processed data, etc. The one or more memories 210 may include processor-readable memory that can be used by one or more processors 200, which can be used to execute code segments of any one or more of the above-mentioned functional modules, and / or use data provided thereby to perform the functions of the system 100 described herein. In addition, as an alternative, one or more modules described may include one or more special-purpose processors, such as application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), graphics processing units (GPUs), etc., configured to perform the functions of the system 100 described herein.

[0042] In one aspect of the present invention, a non-transitory computer-readable medium storing machine-readable instructions is provided, and when implemented on a processor, the machine-readable instructions implement the steps of the method described above. .

[0043] In another aspect of the present invention, an aquarium management system is provided, the system comprising a memory for storing data and a processor for executing computer-readable instructions, wherein the processor is configured by the computer-readable instructions when executing the computer-readable instructions to implement the above method.

[0044] This description illustrates the principles of the present invention. It will therefore be appreciated that those skilled in the art will be able to design various arrangements that, although not explicitly described or shown herein, embody the principles of the present invention and are included within its spirit and scope.

[0045] In addition, all statements describing the principles, details and embodiments of the present invention and their specific examples herein are intended to cover their structural and functional equivalents. In addition, these equivalents include both currently known equivalents and equivalents developed in the future, i.e., any components that perform the same function, regardless of the structure.

[0046] Although the present invention has been illustrated and described in detail in the accompanying drawings and the above description, these illustrations and descriptions should be regarded as exemplary rather than restrictive. It goes without saying that these illustrations and descriptions are only exemplary embodiments and do not limit the scope of the present invention in any way. It is understood that any feature described herein can be used in any embodiment. The exemplary embodiments of the present invention are not mutually exclusive, nor are they exclusive of other embodiments not described herein. Therefore, the present invention also provides an embodiment comprising a combination of one or more of the above illustrative embodiments. Without departing from the spirit and scope of the present invention, the present invention can be modified and varied, and therefore, only the contents specified in the appended claims should be limited.

[0047] In the following claims and the foregoing description of the invention, unless the context requires otherwise due to explicit language or necessary implication, the word "comprise" or variations such as "comprises" or "comprising" are used in an inclusive sense, i.e., to specify the presence of stated features, but not to exclude the presence or addition of further features in various embodiments of the invention.

[0048] It will be appreciated that if any prior art publication is referred to herein, this citation does not constitute an admission that the publication is part of the general knowledge in the art.

Claims

1. An aquarium management system, comprising: a video module for capturing video data, the video data comprising a series of frames showing an aquatic environment containing one or more living organisms; a sensor module for detecting one or more conditions of the aquatic environment; a recognition module for recognizing visual features of one or more living entities from one or more frames of video data; and an analysis module for analyzing the detected one or more water environment conditions and identifying the visual characteristics of one or more life forms to determine the quality of the water environment.

2. The aquarium management system of claim 1, wherein the one or more visual features of the life form include the size, color, shape, texture, position, direction and / or location of the life form displayed in one or more frames of video data.

3. The aquarium management system according to claim 1, wherein the recognition module is used to derive one or more behavior patterns of the living organism based on one or more visual features of the recognized living organism.

4. The aquarium management system of claim 3, wherein the one or more behavior patterns of the organism include one or more of the following behaviors: swallowing air, staying on the water surface, staying on the bottom of the aquarium, not eating, swimming erratically, swimming backwards, speeding up or slowing down, jumping out of the water, lack of energy, convulsions, biting other organisms in the aquarium, swimming erratically, being slow to respond to stimuli, and rubbing against other objects and / or other organisms in the aquarium.

5. The aquarium management system of claim 1, wherein the sensing module comprises one or more sensors, including a temperature sensor, a color sensor, a pH sensor, a chemical sensor, a turbidity sensor, a conductivity sensor, a pressure sensor, a dissolved oxygen sensor, a water level sensor, and a leak sensor.

6. The aquarium management system of claim 1, wherein the one or more conditions of the water environment include one or more of temperature, pH, ammonia level, water color, water turbidity, water conductivity, water pressure, and oxygen level.

7. The aquarium management system of claim 1, wherein the video module comprises one or more video cameras.

8. The aquarium management system of claim 7, wherein the one or more video cameras comprises two cameras arranged to capture video from different directions.

9. The aquarium management system of claim 1, further comprising one or more databases for storing one or more of the following data: captured video data, one or more visual characteristics of determined life forms, one or more conditions of the detected water environment, and / or determined quality of the water environment.

10. The aquarium management system of claim 9, said recognition module being adapted to process computer implemented algorithms including one or more computer vision algorithms.

11. The aquarium management system according to claim 9, wherein the recognition module recognizes one or more visual features of a living being from one or more frames of video data based on data stored in one or more databases.

12. The aquarium management system of claim 9, wherein the analysis module is adapted to process a computer-implemented algorithm comprising one or more of a machine learning algorithm and / or a data analysis algorithm.

13. The aquarium management system of claim 12, wherein the analysis module analyzes the detected water environment conditions and the identified visual characteristics of the life forms based on data stored in one or more databases.

14. The aquarium management system of claim 1, further comprising an execution module adapted to automatically adjust or modify one or more conditions of the water environment based on the quality of the water environment determined by the analysis module.

15. The aquarium management system of claim 1, wherein the one or more living organisms include aquatic microorganisms, animals and / or plants.

16. The aquarium management system of claim 14, wherein the execution module comprises one or more devices of a feeding device, a lighting device, a cooling device, a heating device, a water level controller, a water pump, a chemical dispenser, a filter and / or a timer.

17. A computer-implemented method for determining the quality of an aquatic environment of an aquarium system, comprising the steps of: capturing video data via a video module, the video data comprising a series of frames showing an aquatic environment containing one or more life forms; detecting one or more conditions of the aquatic environment via a sensor module; identifying, by a recognition module, one or more visual features of a life form from one or more frames of video data; as well as The quality of the aquatic environment is determined by analyzing one or more detected conditions of the aquatic environment and one or more visual characteristics of the identified life forms through the analysis module.

18. The computer-implemented method of claim 17, wherein the one or more visual features of the living being include one or more features shown in one or more frames of the video data, such as size, color, shape, texture, position, orientation and / or location of the living being.

19. The computer-implemented method of claim 17, further comprising the step of inferring a behavior pattern of one or more living beings based on one or more identified visual features of the living beings.

20. The computer-implemented method of claim 19, wherein the one or more behavior patterns of the life form include one or more of the following behaviors: breathing large gulps of air, staying at the surface, staying at the bottom of the aquarium, not eating, swimming erratically, swimming upside down, speeding up or slowing down, jumping out of the water, lack of energy, spasming, biting other life forms in the aquarium, swimming erratically, being unresponsive to stimuli, and rubbing against other objects and / or other life forms in the aquarium.

21. The computer-implemented method of claim 17, wherein the sensing module comprises one or more sensors such as a temperature sensor, a color sensor, a pH meter, a chemical sensor, a turbidity sensor, a conductivity sensor, a pressure sensor, a dissolved oxygen sensor, a water level sensor, and a water leak sensor.

22. The computer-implemented method of claim 17, wherein the one or more conditions of the water environment include one or more of temperature, pH, ammonia level, water color, water turbidity, water conductivity, water pressure, and oxygen level.

23. The computer-implemented method of claim 17, wherein the step of capturing video data comprises capturing one or more videos via one or more cameras.

24. The computer-implemented method of claim 17, further comprising the step of storing one or more of the following data in one or more databases: captured video data, identified visual features of one or more life forms, detected one or more water environment conditions, and / or determined water environment quality.

25. The computer-implemented method of claim 24, wherein the step of identifying visual features of one or more living things from one or more frames of video data further comprises processing a computer-implemented algorithm comprising one or more computer vision algorithms.

26. The computer-implemented method of claim 25, wherein the step of processing a computer-implemented algorithm comprises processing using data stored in one or more databases, the algorithm comprising one or more computer vision algorithms.

27. The computer-implemented method of claim 24, wherein the step of analyzing and detecting the conditions of the water environment and the visual features of the identified life forms further comprises processing a computer-implemented algorithm comprising one or more machine learning algorithms and / or data analysis algorithms.

28. A computer-implemented method according to claim 27, wherein the step of processing a computer-implemented algorithm includes processing using data stored in one or more databases, and the algorithm includes one or more machine learning algorithms and / or data analysis algorithms.

29. The computer-implemented method of claim 17, further comprising receiving instructions from the analysis module via the execution module to automatically adjust or modify one or more conditions of the water environment based on the quality of the water environment determined by the analysis module.

30. The computer-implemented method of claim 29, wherein the execution module includes one or more devices including a feeding device, a lighting device, a cooling device, a heating device, a water level controller, a water pump, a chemical dispenser, a filter and / or a timer.

31. A non-transitory computer readable medium having machine readable instructions stored therein, which when executed on a processor can implement the method steps of any one of claims 17 to 30.

32. An aquarium management system comprising a memory for storing data and a processor for executing computer readable instructions, wherein the processor is configured by the computer readable instructions when executing the computer readable instructions to implement the method of any one of claims 17 to 30.

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