Description:Field of the Invention
This invention relates to Intelligent Aquatic Ecosystem Management System: Integrated Sedimentation Monitoring and Analysis for Fish Ponds.
Background of the Invention
Poor water quality is a significant problem in fish ponds. It results from factors such as inadequate oxygen levels, high ammonia or nitrite levels, improper pH balance, excessive organic matter, or the accumulation of toxic substances. Poor water quality can lead to stress, disease, and even death in fish. Fish in ponds can be susceptible to various diseases caused by bacteria, viruses, fungi, or parasites. Stress, overcrowding, poor nutrition, and compromised water quality weaken fish immune systems, making them more susceptible to infections and diseases. Common fish diseases include bacterial infections, viral infections, fungal infections, and parasitic infestations. Overstocking fish in a pond beyond it carrying capacity can lead to overcrowding. Overcrowding can result in increased competition for food and territory, poor water quality, stress, and disease outbreaks. It is important to maintain appropriate stocking densities to ensure the well-being and growth of the fish. Inadequate or imbalanced feeding practices can lead to nutritional deficiencies or excesses in fish. Poor nutrition can weaken the immune system, slow growth, and make fish more susceptible to diseases. It is essential to provide a balanced and appropriate diet for the specific species of fish being raised in the pond.
CN204579513U The utility model provides a kind of fishpond water quality fish pond monitoring system based on radio sensor network monitoring node, comprise Water-quality Monitoring Points, via node and Surveillance center, this fishpond water quality fish pond monitoring system, Real-Time Monitoring can be carried out to the water quality in fish pond, guarantee that fishpond water quality is in the state of optimum Fish Survival for a long time, improve the quantity and quality in fish pond; And adopting multiple Vertex cover fish pond to monitor, monitoring range is wide, and data accuracy is high; The wireless communication technology adopted, the cable that whole monitoring system is laid reduces in a large number, save system investments cost, the ZigBee wireless communication technology of selection, has low in energy consumption, economize energy, battery last longevity of service, the battery changing a wireless senser monitoring point can work a week, easy to operate, only need regularly to carry out changing the Effects of Water Quality that just can ensure to continue to monitor reliably fish pond, there is very high cost performance.
Research Gap: The system automates the process of sedimentation level detection, reducing the need for manual labor and saving time and effort for fish farm operators.
CN112325942A The invention provides a fishpond monitoring and control system based on the Internet of things, which comprises: the water quality monitoring terminal is used for monitoring and collecting environmental elements of water quality on line and uploading the collected data to the cloud server through the Internet of things transmission terminal in real time; the intelligent control end comprises field operation equipment and a control terminal connected with the field operation equipment, and the control terminal controls the field equipment to operate according to the cloud server instruction and the data acquired by the water quality monitoring end; the cloud server is connected with the control management center and the remote management terminal, the cloud server formulates a control scheme according to the front-end real-time environment data and performs drive control on the intelligent control terminal, and meanwhile, the remote control of the field equipment is achieved through the control management center and the remote management terminal. The invention carries out on-line monitoring on the water quality environment and realizes automatic control and equipment scheduling.
Research Gap: By providing real-time or near real-time information, the system enables prompt intervention to prevent adverse effects of excessive sedimentation on fish health and overall pond conditions.
CN206460577U The utility model discloses a kind of fish pond monitoring system, including:It is placed in the RFID chip floated on the water surface in the range of effective read-write of corresponding RFID reader, the RFID reader of effective RFID chip information is read in the range of effective read-write of this RFID reader, it is connected with RFID reader, the processor of the abnormal probability in fish pond is determined, the warning device alarmed when abnormal probability is more than predetermined threshold in fish pond;It can be seen that, in this pro gramme, RFID chip is placed in effective read-write scope of RFID reader, when effective RFID chip quantity that RFID reader is read and write tails off, then judge that fish pond there are abnormal conditions, is at this moment then alarmed by warning device, it is achieved thereby that the monitoring to fish pond abnormal conditions, and RFID reader is placed on the water surface, it is possible to increase the read-write scope of read write line, the problem of solving RFID reader service behaviour is low in water.
Research Gap: The collected data and visualizations help fish farm operators make informed decisions regarding sedimentation management strategies, such as dredging or adjusting feeding practices.
CN211532398U The utility model discloses a fishpond monitoring terminal based on Beidou satellite and a fishpond culture system, which comprises a power supply, a microprocessor, a Beidou satellite positioner, a sensor group, a Beidou communication circuit and a fishpond environment control circuit; the power respectively with microprocessor, big dipper satellite positioning ware, sensor group, big dipper communication circuit and pond environmental control circuit electricity are connected, microprocessor respectively with big dipper satellite positioning ware, sensor group, big dipper communication circuit and pond environmental control circuit electricity are connected, big dipper satellite positioning ware passes through big dipper communication circuit and is connected with big dipper satellite communication, pond environmental control circuit passes through big dipper communication circuit and sets up in the pond environmental control equipment communication connection of pond. The utility model discloses based on big dipper satellite positioning technique and big dipper short message communication, effectively improved data transmission stability and reliability, reduced the maintenance degree of difficulty, realized the real time monitoring to the pond environment, improved breed efficiency, be favorable to realizing the agricultural full automatization.
Research Gap: The data collected by the system can also be valuable for research and development purposes, contributing to a deeper understanding of fish pond ecosystems and sedimentation processes.
None of the prior art indicate above either alone or in combination with one another disclose what the present invention has disclosed. Present invention is Intelligent Aquatic Ecosystem Management System: Integrated Sedimentation Monitoring and Analysis for Fish Ponds
SUMMARY OF THE INVENTION
This summary is provided to introduce a selection of concepts, in a simplified format, that are further described in the detailed description of the invention.
This summary is neither intended to identify key or essential inventive concepts of the invention and nor is it intended for determining the scope of the invention.
To further clarify advantages and features of the present invention, a more particular description of the invention will be rendered by reference to specific embodiments thereof, which is illustrated in the appended drawings. It is appreciated that these drawings depict only typical embodiments of the invention and are therefore not to be considered limiting of its scope. The invention will be described and explained with additional specificity and detail with the accompanying drawings.
A vision and edge-enabled system for sedimentation level detection in fish ponds is an innovative approach that utilizes computer vision techniques and edge computing to monitor and analyze the sedimentation levels in fish ponds. This system aims to automate the process of detecting and measuring sedimentation, which is important for maintaining a healthy and productive fish pond environment. These sensors measure various parameters related to water quality, including Temperature Sensor (102), Dissolved oxygen Sensor (103), pH sensor (104), Turbidity Sensor (105), Conductivity Sensor (106) and Power Supply (107). They provide crucial data to assess the overall health of the pond and its potential impact on sedimentation.
Controlling Unit (101) it receives data from the various sensors deployed across the pond, processes the data, and performs the necessary analysis and decision-making it can also handle data storage, communication with edge devices, and control the overall operation of the system,
Temperature sensor (102) measure the water temperature and monitoring temperature variations can help understand the influence of thermal conditions on sedimentation processes and fish behavior, Dissolve Oxygen Sensor (103) measure the dissolved oxygen levels in the water, which is crucial for fish health and overall pond ecosystem low oxygen levels can lead to stress or even suffocation in fish, affecting sedimentation pattern, pH Sensor (104) measure the acidity or alkalinity of the water and monitoring pH levels is important as certain pH conditions can influence sedimentation dynamics and affect the overall health of the pond ecosystem, Conductivity Sensor (106) Electrical conductivity sensors measure the ability of water to conduct electrical current, which correlates with the concentration of dissolved salts and other ions. Changes in electrical conductivity can indicate variations in water composition, which may impact sedimentation processes, Turbidity Sensor (105) measure the haziness of the water caused by suspended particles high turbidity levels can indicate increased sedimentation and may affect water quality and fish health, Power Supply (107) it plans the distribution of power to the controlling unit and sensors across the fish pond.
This figure 1.2 Environmental Monitoring Unit can include weather stations that measure parameters such as rainfall, humidity, and air temperature. It provides information on external environmental factors that may influence sedimentation patterns. The figure consists of Controlling unit (201) it receives data from the various sensors deployed across the pond, processes the data, and performs the necessary analysis and decision-making it can also handle data storage, communication with edge devices, and control the overall operation of the system, Temperature Sensor (102) measure the water temperature and monitoring temperature variations can help understand the influence of thermal conditions on sedimentation processes and fish behavior, Rainfall Sensor (202) Humidity Sensor (203) can provide valuable information about the moisture levels in the surrounding environment, Power supply (202) it plans the distribution of power to the controlling unit and sensors across the fish pond.
The figure 1.3 (Sedimentation Detection Unit) comprises of Controlling unit (51) it receives data from the various sensors deployed across the pond, processes the data, and performs the necessary analysis and decision-making it can also handle data storage, communication with edge devices, and control the overall operation of the system, Sediment Depth Sensor (52) are specifically designed to measure the depth of sediment accumulated at the bottom of the fish pond it provide direct measurements of sediment levels, allowing for accurate monitoring and analysis, Ammonia/Nitrate Sensor (53) detect the levels of ammonia and nitrate in the water, which are indicators of water quality and nutrient levels. Elevated ammonia or nitrate levels can contribute to sedimentation and can be important factors to monitor, Phosphorus Sensor (54) Phosphorus is another nutrient that can contribute to sedimentation in fish ponds. Phosphorus sensors measure the concentration of phosphorus in the water, helping to assess its impact on sedimentation levels, Carbon Dioxide (CO2) (59) CO2 sensors measure the concentration of carbon dioxide in the water. Excessive CO2 levels can indicate poor water quality or an imbalance in the pond ecosystem, potentially affecting sedimentation dynamics, Algae Sensor (55) Algae growth can contribute to sedimentation and impact water quality it also detects the presence and density of algae in the pond, providing valuable information on its contribution to sedimentation, Silt Density Index Sensor (57) measure the silt density index, which indicates the presence of suspended solids in the water. These sensors can provide insights into the turbidity of the water and the potential for sedimentation, Solar Radiation Sensor (58) measure the intensity of sunlight or solar radiation. Sunlight can affect the growth of algae and aquatic plants, which can contribute to sedimentation dynamics in fish ponds, Fish Behavior Sensor (56) can include acoustic or underwater video sensors that capture fish behavior and movement patterns. Monitoring fish behavior can help understand their interactions with sedimentation and how it affects their well-being, Camera (60) Multiple cameras are strategically deployed around the fish pond to capture images or videos of the water surface captured images or video frames are processed using computer vision algorithms to extract relevant information. This can include image enhancement, background subtraction, and segmentation techniques to isolate the water region, cameras or imaging devices, capturing visual data of the fish pond. Computer vision algorithms are applied to analyze the images and detect sedimentation levels.
Figure1.4 is a generalized architecture of fish pond monitoring system. It combines Figure 1.1, which is for Water Quality Monitoring System, Figure 1.2, for fish pond Environmental Monitoring system, Figure 1.3 for Sedimentation Detection System, and the collected Data Controlling unit (101) sends to Cloud server (65) and via internet it will display on Web Application (66).
BRIEF DESCRIPTION OF THE DRAWINGS
The illustrated embodiments of the subject matter will be understood by reference to the drawings, wherein like parts are designated by like numerals throughout. The following description is intended only by way of example, and simply illustrates certain selected embodiments of devices, systems, and methods that are consistent with the subject matter as claimed herein, wherein:
Figure 1.1 (Water Quality Monitoring Unit)
Figure 1.2 (Environmental Monitoring Unit)
Figure 1.3 (Sedimentation Detection Unit)
Figure 1.4 (System Architecture)
The figures depict embodiments of the present subject matter for the purposes of illustration only. A person skilled in the art will easily recognize from the following description that alternative embodiments of the structures and methods illustrated herein may be employed without departing from the principles of the disclosure described herein.
DETAILED DESCRIPTION OF THE INVENTION
The detailed description of various exemplary embodiments of the disclosure is described herein with reference to the accompanying drawings. It should be noted that the embodiments are described herein in such details as to clearly communicate the disclosure. However, the amount of details provided herein is not intended to limit the anticipated variations of embodiments; on the contrary, the intention is to cover all modifications, equivalents, and alternatives falling within the scope of the present disclosure as defined by the appended claims.
It is also to be understood that various arrangements may be devised that, although not explicitly described or shown herein, embody the principles of the present disclosure. Moreover, all statements herein reciting principles, aspects, and embodiments of the present disclosure, as well as specific examples, are intended to encompass equivalents thereof.
The terminology used herein is for the purpose of describing particular embodiments only and is not intended to be limiting of example embodiments. As used herein, the singular forms “a",” “an” and “the” are intended to include the plural forms as well, unless the context clearly indicates otherwise. It will be further understood that the terms “comprises,” “comprising,” “includes” and/or “including,” when used herein, specify the presence of stated features, integers, steps, operations, elements and/or components, but do not preclude the presence or addition of one or more other features, integers, steps, operations, elements, components and/or groups thereof.
It should also be noted that in some alternative implementations, the functions/acts noted may occur out of the order noted in the figures. For example, two figures shown in succession may, in fact, be executed concurrently or may sometimes be executed in the reverse order, depending upon the functionality/acts involved.
In addition, the descriptions of "first", "second", “third”, and the like in the present invention are used for the purpose of description only, and are not to be construed as indicating or implying their relative importance or implicitly indicating the number of technical features indicated. Thus, features defining "first" and "second" may include at least one of the features, either explicitly or implicitly.
Unless otherwise defined, all terms (including technical and scientific terms) used herein have the same meaning as commonly understood by one of ordinary skill in the art to which example embodiments belong. It will be further understood that terms, e.g., those defined in commonly used dictionaries, should be interpreted as having a meaning that is consistent with their meaning in the context of the relevant art and will not be interpreted in an idealized or overly formal sense unless expressly so defined herein.
These and other advantages of the present subject matter would be described in greater detail with reference to the following figures. It should be noted that the description merely illustrates the principles of the present subject matter. It will thus be appreciated that those skilled in the art will be able to devise various arrangements that, although not explicitly described herein, embody the principles of the present subject matter and are included within its scope.
A vision and edge-enabled system for sedimentation level detection in fish ponds is an innovative approach that utilizes computer vision techniques and edge computing to monitor and analyze the sedimentation levels in fish ponds. This system aims to automate the process of detecting and measuring sedimentation, which is important for maintaining a healthy and productive fish pond environment. These sensors measure various parameters related to water quality, including Temperature Sensor (102), Dissolved oxygen Sensor (103), pH sensor (104), Turbidity Sensor (105), Conductivity Sensor (106) and Power Supply (107). They provide crucial data to assess the overall health of the pond and its potential impact on sedimentation.
Controlling Unit (101) it receives data from the various sensors deployed across the pond, processes the data, and performs the necessary analysis and decision-making it can also handle data storage, communication with edge devices, and control the overall operation of the system,
Temperature sensor (102) measure the water temperature and monitoring temperature variations can help understand the influence of thermal conditions on sedimentation processes and fish behavior, Dissolve Oxygen Sensor (103) measure the dissolved oxygen levels in the water, which is crucial for fish health and overall pond ecosystem low oxygen levels can lead to stress or even suffocation in fish, affecting sedimentation pattern, pH Sensor (104) measure the acidity or alkalinity of the water and monitoring pH levels is important as certain pH conditions can influence sedimentation dynamics and affect the overall health of the pond ecosystem, Conductivity Sensor (106) Electrical conductivity sensors measure the ability of water to conduct electrical current, which correlates with the concentration of dissolved salts and other ions. Changes in electrical conductivity can indicate variations in water composition, which may impact sedimentation processes, Turbidity Sensor (105) measure the haziness of the water caused by suspended particles high turbidity levels can indicate increased sedimentation and may affect water quality and fish health, Power Supply (107) it plans the distribution of power to the controlling unit and sensors across the fish pond.
This figure 1.2 Environmental Monitoring Unit can include weather stations that measure parameters such as rainfall, humidity, and air temperature. It provides information on external environmental factors that may influence sedimentation patterns. The figure consists of Controlling unit (201) it receives data from the various sensors deployed across the pond, processes the data, and performs the necessary analysis and decision-making it can also handle data storage, communication with edge devices, and control the overall operation of the system, Temperature Sensor (102) measure the water temperature and monitoring temperature variations can help understand the influence of thermal conditions on sedimentation processes and fish behavior, Rainfall Sensor (202) Humidity Sensor (203) can provide valuable information about the moisture levels in the surrounding environment, Power supply (202) it plans the distribution of power to the controlling unit and sensors across the fish pond.
The figure 1.3 (Sedimentation Detection Unit) comprises of Controlling unit (51) it receives data from the various sensors deployed across the pond, processes the data, and performs the necessary analysis and decision-making it can also handle data storage, communication with edge devices, and control the overall operation of the system, Sediment Depth Sensor (52) are specifically designed to measure the depth of sediment accumulated at the bottom of the fish pond it provide direct measurements of sediment levels, allowing for accurate monitoring and analysis, Ammonia/Nitrate Sensor (53) detect the levels of ammonia and nitrate in the water, which are indicators of water quality and nutrient levels. Elevated ammonia or nitrate levels can contribute to sedimentation and can be important factors to monitor, Phosphorus Sensor (54) Phosphorus is another nutrient that can contribute to sedimentation in fish ponds. Phosphorus sensors measure the concentration of phosphorus in the water, helping to assess its impact on sedimentation levels, Carbon Dioxide (CO2) (59) CO2 sensors measure the concentration of carbon dioxide in the water. Excessive CO2 levels can indicate poor water quality or an imbalance in the pond ecosystem, potentially affecting sedimentation dynamics, Algae Sensor (55) Algae growth can contribute to sedimentation and impact water quality it also detects the presence and density of algae in the pond, providing valuable information on its contribution to sedimentation, Silt Density Index Sensor (57) measure the silt density index, which indicates the presence of suspended solids in the water. These sensors can provide insights into the turbidity of the water and the potential for sedimentation, Solar Radiation Sensor (58) measure the intensity of sunlight or solar radiation. Sunlight can affect the growth of algae and aquatic plants, which can contribute to sedimentation dynamics in fish ponds, Fish Behavior Sensor (56) can include acoustic or underwater video sensors that capture fish behavior and movement patterns. Monitoring fish behavior can help understand their interactions with sedimentation and how it affects their well-being, Camera (60) Multiple cameras are strategically deployed around the fish pond to capture images or videos of the water surface captured images or video frames are processed using computer vision algorithms to extract relevant information. This can include image enhancement, background subtraction, and segmentation techniques to isolate the water region, cameras or imaging devices, capturing visual data of the fish pond. Computer vision algorithms are applied to analyze the images and detect sedimentation levels.
Figure1.4 is a generalized architecture of fish pond monitoring system. It combines Figure 1.1, which is for Water Quality Monitoring System, Figure 1.2, for fish pond Environmental Monitoring system, Figure 1.3 for Sedimentation Detection System, and the collected Data Controlling unit (101) sends to Cloud server (65) and via internet it will display on Web Application (66).
ADVANTAGES OF THE INVENTION:
1. In this device we are using Raspberry Pi which is a popular single-board computer that provides greater processing capabilities and expanded connectivity options compared to Arduino. It can handle more complex tasks and has a larger memory capacity, making it suitable for managing a larger number of sensors and performing advanced data processing and analysis.
2. By monitoring humidity levels, you can gain insights into the ambient conditions that may impact sedimentation processes. High humidity can contribute to increased evaporation, while low humidity can affect water availability and sedimentation dynamics.
3. The system provides real-time and accurate data on sedimentation levels, water quality, and environmental conditions, enabling fish farm operators to make informed decisions for optimal pond management.
4. The system can detect changes in sedimentation levels at an early stage, allowing prompt intervention and preventing excessive sediment buildup that may harm fish health and pond productivity.
, Claims:We Claim:
1. An Intelligent Aquatic Ecosystem Management System comprises Controlling Unit (101), Temperature Sensor (102), Dissolve Oxygen Sensor (103), PH Sensor (104), turbidity Sensor (105), Conductivity Sensor (106), Power Supply (107), Temperature Sensor (102), Controlling Unit (201), Power Supply (202), Rainfall Sensor (202), Humidity Sensor (203), Controlling Unit (51), Sediment Depth Sensors (52), Ammonia/Nitrate Sensors (53), Phosphorus Sensors (54), Algae Sensors (55), Fish Behavior Sensors (56), Silt Density Index Sensors (57), Solar Radiation Sensors (58), Carbon Dioxide (CO2) Sensors (59), Power Supply (59), Controlling Unit (101), Cloud Server (65), and Web Application (66).
2. The system as claimed in claim 1, wherein Controlling Unit (101) receives data from the various sensors deployed across the pond, processes the data, and performs the necessary analysis and decision-making it also handle data storage, communication with edge devices, and control the overall operation of the system; wherein Temperature sensor (102) measure the water temperature and monitoring temperature variations can help understand the influence of thermal conditions on sedimentation processes and fish behavior, Dissolve Oxygen Sensor (103) measure the dissolved oxygen levels in the water, which is crucial for fish health and overall pond ecosystem low oxygen levels lead to stress or even suffocation in fish, affecting sedimentation pattern, pH Sensor (104) measure the acidity or alkalinity of the water and monitoring pH levels is important as certain pH conditions influence sedimentation dynamics and affect the overall health of the pond ecosystem, Conductivity Sensor (106) Electrical conductivity sensors measure the ability of water to conduct electrical current, which correlates with the concentration of dissolved salts and other ions.
3. The system as claimed in claim 1, wherein Turbidity Sensor (105) measure the haziness of the water caused by suspended particles high turbidity levels indicate increased sedimentation and affects water quality and fish health, Power Supply (107) it plans the distribution of power to the controlling unit and sensors across the fish pond.
4. The system as claimed in claim 1, wherein Controlling unit (201) receives data from the various sensors deployed across the pond, processes the data, and performs the necessary analysis and decision-making it can also handle data storage, communication with edge devices, and control the overall operation of the system, Temperature Sensor (102) measure the water temperature and monitoring temperature variations can help understand the influence of thermal conditions on sedimentation processes and fish behavior, Rainfall Sensor (202) Humidity Sensor (203) provides valuable information about the moisture levels in the surrounding environment, Power supply (202) it plans the distribution of power to the controlling unit and sensors across the fish pond.
5. The system as claimed in claim 1, wherein Controlling unit (51) it receives data from the various sensors deployed across the pond, processes the data, and performs the necessary analysis and decision-making it also handles data storage, communication with edge devices, and control the overall operation of the system, Sediment Depth Sensor (52) are specifically designed to measure the depth of sediment accumulated at the bottom of the fish pond it provide direct measurements of sediment levels, allowing for accurate monitoring and analysis, Ammonia/Nitrate Sensor (53) detect the levels of ammonia and nitrate in the water, which are indicators of water quality and nutrient levels.
6. The system as claimed in claim 1, wherein Phosphorus Sensor (54) measure the concentration of phosphorus in the water, helping to assess its impact on sedimentation levels, Carbon Dioxide (CO2) (59) CO2 sensors measure the concentration of carbon dioxide in the water.
7. The system as claimed in claim 1, wherein Algae Sensor (55) Algae growth contribute to sedimentation and impact water quality it also detects the presence and density of algae in the pond, providing valuable information on its contribution to sedimentation, Silt Density Index Sensor (57) measure the silt density index, which indicates the presence of suspended solids in the water.
8. The system as claimed in claim 1, wherein said sensors provide insights into the turbidity of the water and the potential for sedimentation, Solar Radiation Sensor (58) measure the intensity of sunlight or solar radiation. Sunlight can affect the growth of algae and aquatic plants, which contributes to sedimentation dynamics in fish ponds, Fish Behavior Sensor (56) includes acoustic or underwater video sensors that capture fish behavior and movement patterns.
9. The system as claimed in claim 1, wherein Camera (60) Multiple cameras are strategically deployed around the fish pond to capture images or videos of the water surface captured images or video frames are processed using computer vision algorithms to extract relevant information.
10. The system as claimed in claim 1, wherein for Sedimentation Detection System, and the collected Data Controlling unit (101) sends to Cloud server (65) and via internet it will display on Web Application (66).