Field of the Invention
This invention relates to AI enabled vision based edge device to observe behavioral activities in morris water maze (MWM)
Background of the Invention
CN205124681U: The utility model relates to a mouse water maze study memory test platform belongs to animal experiment instrument field, mouse water maze study memory test platform, multi -arm maze and morris water maze combine together, provide a multi -arm water maze test platform, in separate the arm, the swimming pool was arranged in to swimming pool, partition arm, one of them underwater of separating the arm terminal was provided with the platform of fleing, the partition arm be 3 -6 arm type, the utility model discloses a technical problem that ordinary morris water maze experimental design is difficult to to accomplish can have been overcome according to the complexity that how much decides the maze experiment of study memory water that increases the swimming arm in multi -arm water maze, and the device can very big degree solves the mouse that appears and floats the phenomenon that the surface of water is motionless, do not swim in the experiment of ordinary morris water maze.
Research Gap: Vision device is incorporated in the morris water maze to cut short the manual time.
CN105265334A: The invention relates to a mouse water maze learning and memory test platform, and belongs to the field of animal experiment instruments. According to the mouse water maze learning and memory test platform, a multi-arm maze is combined with a Morris water maze, and a multi-arm water maze test platform is provided. The mouse water maze learning and memory test platform comprises separation arms and a swimming pool, wherein the separation arms are placed inside the swimming pool, and an escape platform is arranged below the water surface of the tail end of each separation arm; and the separation arms are of a 3-6 arm type. The multi-arm water maze can determine the difficulty level of a water maze learning and memory experiment according to the number of increased swimming arms, and overcomes a technical problem that a common Morris water maze experiment design is difficult to be achieved. The mouse water maze learning and memory test platform can solve a phenomenon that a mouse floats on the water surface and does not move or swim of a common Morris water maze experiment to a great extent.
Research Gap: Vision based edge device is incorporated to keep keen observation to the behavioral activities.
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 explore the various areas of sciences like Neurophysiology, Neuropathology, Neurodegenerative disorders, Psychological disorders. The Morris Water Maze (MWM) is a test of spatial learning for rodents that relies on distal cues to navigate from start location around the perimeter of open swimming arena to locate a submerged escaped platform.
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.
Invention focuses to explore the various areas of sciences like Neurophysiology, Neuropathology, Neurodegenerative disorders, Psychological disorders. The Morris Water Maze (MWM) is a test of spatial learning for rodents that relies on distal cues to navigate from start location around the perimeter of open swimming arena to locate a submerged escaped platform. The Morris Water Maze is a behavioral model used to check the spatial learning. It is a time taking process, needs keen attention to observe the behavioral activity of each and every animal in every group. To reduce this manual time, the vision based edge device is used in Morris Water Maze (MWM), where simultaneously other works can be performed in laboratory.
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:
In Fig. 1, Morris Water Maze (600) is the animal model used to check the spatial learning for rodents is attached with Water Inlet/Outlet (800) to fill/empty the tank. The MWM contain two platform (700) in it. These platforms are used to check spatial learning property of animals. The vision based edge rotating device (500) is attached in it to capture the animal behaviour.
Fig. 1. AI enabled vision based edge device incorporated in Morris Water Maze
In Fig. 2, the vision based edge rotating device (500) is attached at the edge of the Morris Water Maze which will capture all the behavioural activities of the animal. The data will processed to the Computing Unit (400). The AC input (300) is attached to it for its power supply. The Computing Unit will transfer the information to the Neural Compute Stick (200). NCS is a tiny fan less deep learning device use to learn AI programming and deep neural network. In back end Machine learning algorithm will process all the information and data will be stored at Storage device (100). Simultaneously this information can be stored in Cloud (F) and can be accessed from any place with help of App.
Fig 2. : Internal processing of Vision Based Edge Device

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.
Morris Water Maze (600) is the animal model used to check the spatial learning for rodents is attached with Water Inlet/Outlet (800) to fill/empty the tank. The MWM contain two platform (700) in it. These platforms are used to check spatial learning property of animals. The vision based edge rotating device (500) is attached in it to capture the animal behavior. The vision based edge rotating device (500) is attached at the edge of the Morris Water Maze which will capture all the behavioral activities of the animal. The data will processed to the Computing Unit (400). The AC input (300) is attached to it for its power supply. The Computing Unit will transfer the information to the Neural Compute Stick (200). NCS is a tiny fan less deep learning device use to learn AI programming and deep neural network. In back end Machine learning algorithm will process all the information and data will be stored at Storage device (100). Simultaneously this information can be stored in Cloud (F) and can be accessed from any place with help of App.
Advantages of the Invention:
1. It will helps to cut short the time duration used observe the animal activity.
2. Simultaneously other activities can be performed in the laboratory.
3. The data can be stored for longer duration of time.
4. Data can be accessed from various location.

We Claims:

1. An AI Enabled vision-based edge device to observe behavioral activities in morris water maze (MWM) is comprises with Morris Water Maze (600) is the animal model used to check the spatial learning for rodents is attached with Water Inlet/Outlet (800) to fill/empty the tank.
2. The device as claimed in claim 1, wherein which is consists MWM contain two platform (700) in it.
3. The device as claimed in claim 1, wherein which is consists platforms are used to check spatial learning property of animals and a vision based edge rotating device (500) is attached in it to capture the animal behavior.
4. The device as claimed in claim 1, wherein which is consists vision-based edge rotating device (500) is attached at the edge of the Morris Water Maze which will capture all the behavioral activities of the animal.
5. The device as claimed in claim 1, wherein data is processed to the Computing Unit (400); AC input (300) is attached to it for its power supply and Computing Unit will transfer the information to the Neural Compute Stick (200).
6. The device as claimed in claim 1, wherein NCS is a tiny fan less deep learning device use to learn AI programming and deep neural network, and in back end Machine learning algorithm processes all the information and data will be stored at Storage device (100).