SYSTEM FACILITATING SURVEILLANCE AND USER SAFETY DURING SWIMMING AND THE METHOD THEREOF

Abstract

The present invention discloses a system (100) facilitating surveillance and user safety during swimming and the method thereof. The system (100) includes a first set of cameras (104) to capture real-time video of a user (116) performing swimming in the swimming pool (102) and a second set of cameras (106) to capture the real-time video of the surroundings of the swimming pool with the motions and activities at the surface. System includes processors (112) configured to receive and process real-time data from the first set of cameras and the second set of cameras to identify a pattern and an anomaly indicating a drowning incident and predict the drowning incident the user involved. Processors alert a concerned person (124) about the drowning incident by providing a notification and provide location details of the user involved in the drowning incident. Processors activate an automated rescue technique (226) to assist the user.

Specification

Description:TECHNICAL FIELD
[0001] The present invention relates to the field of drowning detection systems. In particular, it relates to a system facilitating surveillance and user safety during swimming and the method thereof.

BACKGROUND
[0002] Background description includes information that may be useful in understanding the present disclosure. It is not an admission that any of the information provided herein is prior art or relevant to the presently claimed disclosure, or that any publication specifically or implicitly referenced is prior art.
[0003] Drowning accidents are a major global safety concern. Drowning events occur more frequently in indoor swimming pools and are significantly increased by inadequate safety features in the swimming pools. The vast supervision zone and the increasing quantity of swimmers make it difficult for lifeguards to visually search, which results in slower reaction times. Recently, early drowning detection has been a prominent area of research. SwimEye is an existing drowning detection and drowning prevention system for swimming pools. Another existing system is Angeleye smart lifeguard system which is an underwater monitoring camera and advanced warning system designed to enable aquatic safety and lifeguard operations. One of the existing prior art authored by T. He et. al., entitled "An improved swimming pool drowning detection method based on YOLOv8", discloses a drowning detection method based on YOLOv8. Another existing prior art authored by R. Yang et. al., entitled "An improved YOLOv5 algorithm for drowning detection in the indoor swimming pool", discloses a YOLOv5 algorithm aimed at improving the efficacy of indoor swimming pool drowning detection and facilitating the timely rescue of endangered individuals. One of the Chinese patent application publications CN117132924A entitled "ATT-YOLO-V7 network-based indoor swimming pool drowning detection method", discloses an indoor swimming pool drowning detection method based on an ATT-YOLO-V7 network.
[0004] However, the existing drowning detection models exhibit low accuracy, rendering them inadequate for practical drowning detection and rescue applications. The existing systems detect drowning incidents but don't predict distress or provide proactive interventions. However, the potential drawback is that the machine learning model can be trained with only a limited number of datasets, which limits its precision. The existing systems fail to address swimmer safety and also lack the usage of real-time rescue devices and visual feedback to assist lifeguards. Even though the existing systems provide alerts to the lifeguards but fail to provide the location data of the swimmer. Hence, there exists a need for a system which can overcome the limitations of the existing approaches and can provide an efficient and reliable drowning detection and prediction.

OBJECTS OF THE PRESENT DISCLOSURE
[0005] Some of the objects of the present disclosure, which at least one embodiment herein satisfies are as listed herein below.
[0006] It is an object of the present disclosure to provide a system facilitating surveillance and user safety during swimming and the method thereof.
[0007] It is another object of the present disclosure related to a system and method which facilitates drowning detection by analysing real-time swimming patterns and identifying pre-drowning behaviour of the user.
[0008] It is another object of the present disclosure related to a system and method that employs automated safety techniques such as deploying drones or robotic flotation devices once drowning is detected, and provides GPS-based location data to emergency responders.
[0009] It is another object of the present disclosure related to a system and method which incorporates dynamic visual safety indicators to provide instant visual feedback for swimmers and supervisors based on real-time safety levels.
[00010] It is another object of the present disclosure related to a system and method which continuously monitors water quality and triggers immediate alerts to the pool management once the water quality falls below safe levels.



SUMMARY
[00011] The present invention relates to the field of drowning detection systems. In particular, it relates to a system facilitating surveillance and user safety during swimming and the method thereof. In specific, it relates to a system and method which facilitates drowning detection by analysing real-time swimming patterns and identifying pre-drowning behaviour of the user.
[00012] An aspect of the present disclosure provides a system facilitating surveillance and user safety during swimming. The system includes a first set of cameras integrated within a swimming pool and a second set of cameras placed in the vicinity of the swimming pool. The first set of cameras are configured to capture real-time video of a user performing swimming in the swimming pool. The second set of cameras are configured to capture the real-time video of the surroundings of the swimming pool with the motions and activities at the surface. The first set of cameras and the second set of cameras are coupled to a plurality of processors associated with a computing device and a server.
[00013] Further, the plurality of processors is configured to receive real-time data from the first set of cameras and the second set of cameras. The real time data includes any or a combination of the real-time video on the motions and activities of the user inside the swimming pool, and the real-time video of the surroundings. Further, the plurality of processors is configured to process the real-time data by employing a machine learning module to identify a pattern and an anomaly indicating a drowning incident and predict the drowning incident the user involved. Further, the plurality of processors is configured to alert a concerned person about the drowning incident by providing a notification employing the computing device and provide location details of the user involved in the drowning incident. Furthermore, the plurality of processors is configured to activate an automated rescue technique to assist the user involved in the drowning incident.
[00014] In an aspect, the system includes a plurality of sensors integrated within the swimming pool. The plurality of sensors is configured to monitor and acquire a plurality of quality parameters associated with the water in the swimming pool. Further, the system includes a water quality module coupled to the plurality of sensors. The water quality module is configured to process the plurality of quality parameters acquired by the plurality of sensors to access the quality of the water in the swimming pool. The plurality of quality parameters includes any or a combination of a turbidity, a colour, an odour, a pH, a chemical composition, and a water level.
[00015] In an aspect, the system includes a plurality of visual safety indicators integrated within the swimming pool. The plurality of visual safety indicators is configured to change colour based on the detection of the drowning incident. The colour includes at least one of a green, a yellow, and a red. The green colour indicates a safe condition, the yellow colour indicates a caution, and the red colour indicates a high-risk situation.
[00016] In an aspect, the system includes a voice-controlled emergency activation system configured to activate the automated rescue technique and trigger alerts to an emergency service through a voice command by providing a hands-free response mechanism in a critical situation. The automated rescue technique includes at least one of an automatically deploying a drone and a robotic flotation device to assist the user in distress.
[00017] In an aspect, the system is configured to process the real-time video by a Graphics Processing Unit (GPU) based data processing unit employing the machine learning technique and a predictive behavioural technique to identify the drowning incident beforehand.
[00018] In an aspect, the system is configured to monitor a behaviour of the user in real-time by the predictive behavioural technique to identify a sign of fatigue and an irregular movement to trigger a pre-drowning alert to the concerned person by employing a mobile application and deploy automated rescue technique to assist the user once the system detects an actual drowning.
[00019] In an aspect, the system includes an Augmented Reality (AR) integration technique configured to provide a plurality of visual cues for the user in real-time. The plurality of visual cues includes any or a combination of a safe zone, a depth warning, and an exit guidance. Further the Augmented Reality (AR) integration technique is configured to enable the concerned person to locate the user involved in drowning incident and respond faster.
[00020] In an aspect, the system is configured to monitor the plurality of quality parameters continuously by the water quality module to trigger the alerts to a swimming pool management employing the mobile application once the plurality of quality parameters falls below a safe level. Further, the system is configured to employ the real-time data from a smart wearable device worn by the user and cross-reference the real-time data with the plurality of visual cues to trigger early warnings if the user swimmer is showing the signs of distress before to a visual sign of the drowning become apparent. The smart wearable device is configured to monitor any or a combination of a heart rate of the user, a body temperature of the user, and an oxygen levels of the user.
[00021] In an aspect, the first set of cameras are underwater cameras configured to capture the real-time video of the user within the water to monitor a submersion and an extended inactivity of the user. The second set of cameras are an overhead camera configured to capture a bird's-eye view of the swimming pool providing full surface coverage and detecting surface-level distress signals.
[00022] In an aspect, a method for facilitating surveillance and user safety during swimming by a system. The method includes the step of capturing, real-time data by a first set of cameras and a second set of cameras. The real time data comprises any or a combination of the real-time video on the motions and activities of the user inside the swimming pool, and the real-time video of the surroundings. Further, the method includes the step of processing, by a plurality of processors the real-time data received from the first set of cameras and the second set of cameras employing a machine learning module to identify a pattern and an anomaly indicating a drowning incident and predict the drowning incident the user involved. Further, the method includes the step of alerting, a concerned person about the drowning incident by providing a notification employing the computing device and provide a location detail of the user involved in the drowning incident. Furthermore, the method includes the step of activating, an automated rescue technique to assist the user involved in the drowning incident.
[00023] Various objects, features, aspects, and advantages of the inventive subject matter will become more apparent from the following detailed description of preferred embodiments, along with the accompanying drawing figures in which like numerals represent like components.

BRIEF DESCRIPTION OF DRAWINGS
[00024] The accompanying drawings are included to provide a further understanding of the present disclosure, and are incorporated in, and constitute a part of this specification. The drawings illustrate exemplary embodiments of the present disclosure, and together with the description, serve to explain the principles of the present disclosure.
[00025] In the figures, similar components, and/or features may have the same reference label. Further, various components of the same type may be distinguished by following the reference label with a second label that distinguishes among the similar components. If only the first reference label is used in the specification, the description is applicable to any one of the similar components having the same first reference label irrespective of the second reference label.
[00026] FIG. 1 illustrates an exemplary architecture of the proposed system 100 facilitating surveillance and user safety during swimming, in accordance with an embodiment of the present disclosure.
[00027] FIG. 2 illustrates an exemplary block diagram of the proposed system 100 facilitating surveillance and user safety during swimming, in accordance with an embodiment of the present disclosure.
[00028] FIG. 3 illustrates exemplary process flow diagram 300 of the proposed system 100 facilitating surveillance and user safety during swimming, in accordance with an embodiment of the present disclosure.
[00029] FIG. 4 illustrates an exemplary flow diagram 400 of the method for facilitating surveillance and user safety during swimming by the system 100, in accordance with an embodiment of the present disclosure.
[00030] FIG. 5 illustrates exemplary drowning situations identified by the system 100 displayed through a user interface (a) possible drowning prediction, (b) a possible passive drowning, and (c) an active drowning, in accordance with an embodiment of the present disclosure.

DETAILED DESCRIPTION
[00031] The following is a detailed description of embodiments of the disclosure depicted in the accompanying drawings. The embodiments are in such detail as to clearly communicate the disclosure. However, the amount of detail offered 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 spirit and scope of the present disclosure as defined by the appended claims.
[00032] In some embodiments, the numbers expressing quantities of
ingredients, properties such as concentration, and so forth, used to describe and
claim certain embodiments of the invention are to be understood as being
modified in some instances by the term "about." Accordingly, in some
embodiments, the numerical parameters set forth in the written description are
approximations that can vary depending upon the desired properties sought to be
obtained by a particular embodiment. In some embodiments, the numerical
parameters should be construed in light of the number of reported significant
digits and by applying ordinary rounding techniques. Notwithstanding that the
numerical ranges and parameters setting forth the broad scope of some
30 embodiments of the invention are approximations, the numerical values set forth
in the specific examples are reported as precisely as practicable.
[00033] The recitation of ranges of values herein is merely intended to serve as a shorthand method of referring individually to each separate value falling within
the range. Unless otherwise indicated herein, each individual value is incorporated
into the specification as if it were individually recited herein.
[00034] Embodiment of the present disclosure relates to a system facilitating surveillance and user safety during swimming and the method thereof. In specific, it relates to a system and method that facilitates drowning detection by analyzing real-time swimming patterns and identifying the pre-drowning behaviour of the user.
[00035] Various aspects of the present disclosure are described with respect to FIGs. 1-5.
[00036] The present invention relates to the field of emergency services. In particular, it relates to a system facilitating surveillance and user safety during swimming and the method thereof.
[00037] FIG. 1 illustrates an exemplary architecture of the proposed system 100 facilitating surveillance and user safety during swimming, in accordance with an embodiment of the present disclosure.
[00038] In an embodiment, referring to FIG. 1, the architecture of the proposed system 100 facilitates surveillance and user safety during swimming. The system 100 may include a first set of cameras 104 integrated within a swimming pool 102 and a second set of cameras 106 placed in the vicinity of the swimming pool 102. The first set of cameras 104 are configured to capture real-time video of a user 116 performing swimming in the swimming pool 102. The second set of cameras 106 are configured to capture the real-time video of the surroundings of the swimming pool 102 with the motions and activities at the surface. The first set of cameras 104 and the second set of cameras 106 are coupled to a plurality of processors 112 associated with a computing device 202 and a server 122.
[00039] In an embodiment, the first set of cameras 104 are underwater cameras configured to capture the real-time video of the user 116 within the water to monitor a submersion and an extended inactivity of the user 116. The second set of cameras 106 are an overhead camera configured to capture a bird's-eye view of the swimming pool 102 providing full surface coverage and detecting surface-level distress signals.
[00040] In an embodiment, the processors 112 can be configured to receive real-time data from the first set of cameras 104 and the second set of cameras 106. The real time data may include any or a combination of the real-time video on the motions and activities of the user 116 inside the swimming pool 102, and the real-time video of the surroundings. Further, the processors 112 can be configured to process the real-time data by employing a machine learning module 214 to identify a pattern and an anomaly indicating a drowning incident and predict the drowning incident of the user 116 involved. Further, the processors 112 can be configured to alert a concerned person 124 about the drowning incident by providing a notification employing the computing device 202 and provide location details of the user 116 involved in the drowning incident. Furthermore, the processors 112 can be configured to activate an automated rescue technique 226 to assist the user 116 involved in the drowning incident.
[00041] In an exemplary embodiment, the first set of cameras 104 and the second set of cameras 106 transfer the real-time video the processors 112 coupled to the computing device 202 that runs on a Graphical Processing Unit (GPU). This GPU uses cutting-edge algorithms to recognize drowning episodes in the incoming video streams. High-speed and effective processing is made possible by using the GPU-based system, for fast intervention and real-time analysis. The computing device 202 monitors the real-time video continually for any irregularities and trends that could indicate a drowning, including extended submersion or immobility.
[00042] In an embodiment, the system 100 may include a plurality of sensors 110 integrated within the swimming pool 102. The plurality of sensors 110 can be configured to monitor and acquire a plurality of quality parameters associated with the water in the swimming pool 102. The plurality of quality parameters can include, but not limited to: a turbidity, a colour, an odour, a pH, a chemical composition, a water level, and the like.
[00043] In an embodiment, the system 100 can be configured to monitor a behaviour of the user 116 in real-time by the predictive behavioural technique to identify a sign of fatigue and an irregular movement to trigger a pre-drowning alert to the concerned person 124 by employing a mobile application and deploy automated rescue technique 226 to assist the user 116 once the system 100 detects an actual drowning.
[00044] In an embodiment, the system 100 can be configured to employ the real-time data from a smart wearable device 108 worn by the user 116 and cross-reference the real-time data with the plurality of visual cues to trigger early warnings if the user 116 is showing the signs of distress before to a visual sign of the drowning become apparent. The smart wearable device 108 can be configured to monitor any or a combination of a heart rate of the user 116, a body temperature of the user 116, and an oxygen levels of the user 116.
[00045] In an embodiment, the system 100 may include a cloud 118 configured to further process and store the data that is gathered from the cameras and the sensors 110. Data backup, remote access, and efficient data storage may be made possible by the cloud 118 connection. The server 122 can be configured to manage the data and performs the computing duties for the stability and dependability of the system 100. Scalability may be attained by the integration of the server 122 and the cloud 118 infrastructure, which enables the system 100 to handle pools of data based on need.
[00046] In an embodiment, once completing processing, a user interface 120 may receive the real-time data and alerts. The concerned person 124 may employ the user interface 120 to supervise the safety of the user 116. If the display notices any signs of drowning, the concerned person 124 may get notified right away and provide real-time information. The concerned can intervene quickly to help the user 116 involved in the drowning incident based on the timely notification. The concerned person 124 can include, but not limited to: a lifeguard, a pool supervisor, and the like.
[00047] FIG. 2 illustrates an exemplary block diagram of the proposed system 100 facilitating surveillance and user safety during swimming, in accordance with an embodiment of the present disclosure.
[00048] In an embodiment, referring to FIG. 2, the exemplary block diagram of the proposed system 100 facilitates surveillance and user safety during swimming. The system 100 may include a computing device 202 with processor 1, 112-1 configured to handle the initial processing and data collection from the first set of cameras 104, the second set of cameras 106, and the sensors 110. A memory module1, 114-1 coupled to the processor and may include a plurality of modules including, but not limited to: a camera module 1, 204-1, a camera module 2, 204-2, a sensor module, 206, a communication module 1, 208-1, and the like. The memory module 1, 114-1 may receive the real-time video from the first set of cameras 104 and the second set of cameras 106 through the camera module 1, 204-1 and the camera module 2, 204-2. Further, the memory module 1, 114-1 may provide a set of instructions to the processor to process the real-time video to precisely track the activities of the user 116 and to identify the indications of distress, drowning and the like.
[00049] In an exemplary embodiment, the computing device 202 which acts as the main data collection device. The underwater cameras and the overhead cameras, allowing for live, uninterrupted feeds of the swimming pool area. The surface of the swimming pool 102 may be monitored by the overhead camera, which records movements made by swimmers and other activities that take place above the water. The underwater camera records video simultaneously below the surface, providing a vivid image of the actions and motions of swimmers. Combining these two viewpoints by the system 100 to identify any anomalies or distress signals that could point to a possible drowning incident. Further, a display unit 1, 210-1 may be integrated for local data and alert presentation, enabling people on-site to keep an eye on the system 100 in real-time.
[00050] In an embodiment, the system 100 may include a sensor module 206 with a water quality module 216 coupled to the plurality of sensors 110. The water quality module 216 can be configured to process the plurality of quality parameters acquired by the plurality of sensors 110 to access the quality of the water in the swimming pool 102. The system 100 can be configured to monitor the plurality of quality parameters continuously by the water quality module 216 to trigger the alerts to a swimming pool management employing the mobile application once the plurality of quality parameters falls below a safe level.
[00051] In an exemplary embodiment, the sensor module 206 may receive the quality parameters acquired by the sensors 110 to assess the water quality in the swimming pool 102. The sensors 110 employed by the water quality and level management module 216-1 monitor on the water level in the swimming pool 102 and make sure it complies with safety regulations. The sensors 110 employed by the turbidity, colour, and odour testing module 216-2 evaluate the clarity, the colour, and the smell-the markers of cleanliness and quality. The chlorine level management module 216-3 checks if the water is kept disinfected and safe for swimming by keeping chlorine levels within safe bounds. The other disinfectants management module 216-4 configured to check for other chemical agents used in the swimming pool 102 care to provide a balanced and secure swimming environment.
[00052] In an exemplary embodiment, the system 100 may further include sensors 110, including but not limited to: a temperature sensor, a humidity sensor, a depth sensor, an air quality sensor, and the like. The real-time data from the sensors 110 may be analysed in conjunction with visual data to provide a comprehensive assessment of the swimming environment and the user behaviour.
[00053] In an exemplary embodiment, the communication module 1, 208-1 may enable to transfer the data gathered from the cameras and sensors 110 to the server 122 by facilitating data transmission (Tx1), 208-11 and reception (Rx1), 208-12. The communication module transfers the data gathered by the computing device 202 including the real-time video feeds and the sensor readings, and is transmitted via the cloud 118 to the server 122. The cloud 118 may enable to send massive amounts of data from the computing device 202 to the server 122 for processing and analysis.
[00054] In an embodiment, the server 122 may act as the primary hub for processing the data transferred from the computing device 202 employing the processor 2, 112-2. The communication module 2, 208-2 with transmission (Tx2), 208-21 and reception (Rx2), 208-22 capabilities of the server 122 may receive (Rx2) and perform preliminary organization of the data received from the cloud 118. The server 122 may include the machine learning techniques specifically built for drowning detection and prediction. The drowning detection and prediction module 212 coupled with the machine learning module 214 in the memory module 2, 114-2 may look for patterns, behaviours, and abnormalities that can point to a drowning episode by analysing the sensor data and live video feeds. Through continuous learning, the machine learning technique may be taught on large datasets to distinguish between potential crises and routine swimming activities.
[00055] In an exemplary embodiment, the machine learning technique employed by the system can include, but not limited to: a You Look Only Once (YOLO) v8, a Convolutional Neural Network (CNN), and the like. In an instance, the system may employ the YOLOv8 in combination with the CNNs for accurate class prediction and object localization.
[00056] In an exemplary embodiment, the server 122 may transfer the drowning prediction notifications to the user interface 120 once analysing the data and identifying a possible drowning scenario displayed on display unit 2, 210-2. The transmission mechanism checks that the concerned person 124 is promptly notified of any detected issues, hence facilitating timely response. The information transmitted to the user interface 120 includes comprehensive details on the incident that was detected, including, but not limited to: a behaviour of the user, a location within the swimming pool, and a particular indicator that pointed to a possible drowning.
[00057] In an embodiment, the concerned person 124 may employ the user interface 120 with processor 3, 112-3, as remote devices to communicate with the system 100. A CPU on each distant device controls the data it receives from the server 122. A communication module 3, 208-3 with transmission (Tx3), 208-31 and reception (Rx3), 208-32 capabilities is part of the memory module 3, 114-3. Thus, allows for smooth data exchange with the server 122. The concerned person 124 can check on the conditions of the swimming pool 102 and user safety from different locations in the facility employing the display unit 3, 210-3 on the user interface 120, which provides real-time data and alerts. The alert notification may be sent and the received data is displayed on the user interface 120.
[00058] In an embodiment, the system 100 may include a plurality of visual safety indicators 224 integrated within the swimming pool 102. The plurality of visual safety indicators 224 can be configured to change colour based on the detection of the drowning incident. The colour may include at least one of a green, a yellow, and a red. The green colour indicates a safe condition, the yellow colour indicates a caution, and the red colour indicates a high-risk situation.
[00059] In an exemplary embodiment, the LED lights may be employed as visual safety indicators 224. The LED light arranged around the swimming pool 102 may change colour to green, yellow, and red based on real-time safety levels, providing instant visual feedback for the user 116 and the concerned person 124. In an instance, once the chlorine levels or pH fall below safe thresholds, the system 100 sends an immediate notification to pool managers and adjusts the LED safety indicators to yellow, signalling caution to swimmers and lifeguards.
[00060] In an embodiment, the system 100 may include a voice-controlled emergency activation system 222 configured to activate the automated rescue technique 226 and trigger alerts to an emergency service through a voice command by providing a hands-free response mechanism in a critical situation. The automated rescue technique 226 may include at least one of an automatically deploying a drone and a robotic flotation device to assist the user 116 in distress.
[00061] In an embodiment, the system 100 can be configured to process the real-time video by a Graphics Processing Unit (GPU) based data processing unit employing the machine learning technique and a predictive behavioural technique to identify the drowning incident beforehand.
[00062] In an embodiment, the system 100 may include an Augmented Reality (AR) integration technique 220 configured to provide a plurality of visual cues for the user 116 in real-time. The plurality of visual cues includes any or a combination of a safe zone, a depth warning, and an exit guidance. Further the Augmented Reality (AR) integration technique 220 can be configured to enable the concerned person 124 to locate the user 116 involved in drowning incident and respond faster.
[00063] In an exemplary embodiment, the system 100 may include Blockchain technology to securely store all surveillance data, ensuring integrity and immutability for legal purposes.
[00064] FIG. 3 illustrates exemplary process flow diagram 300 of the proposed system 100 facilitating surveillance and user safety during swimming, in accordance with an embodiment of the present disclosure.
[00065] In an embodiment, referring to FIG. 3, the process flow diagram 300 of the proposed system 100 facilitates surveillance and user safety during swimming. The computing device 202 may gather the real-time video from the first set of cameras 104 and the second set of cameras 106 at step 302. The sensor module may receive the data from the sensors 110 and the water quality module 216 checks for the water quality at step 304. Further, the data is sent over the cloud 118 to the server 122 at step 306. The communication module may receive the data and the server 122 may employ the drowning detection and prediction module to identify potential drowning incidents by employing the machine learning techniques at step 308. The drowning predictions may be transferred to the user interface 120 including any drowning instances that are recognized at step 310, and notification alerts may be displayed to enable prompt action through the automated rescue technique 226 at step 312.
[00066] FIG. 4 illustrates an exemplary flow diagram 400 of the method for facilitating surveillance and user safety during swimming by the system 100, in accordance with an embodiment of the present disclosure.
[00067] In an embodiment, referring to FIG. 4, the method for facilitating surveillance and user safety during swimming by the system 100. The method includes step 402 of capturing, real-time data by a first set of cameras 104 and a second set of cameras 106. The real time data comprises any or a combination of the real-time video on the motions and activities of the user 116 inside the swimming pool 102, and the real-time video of the surroundings. Further, the method includes step 404 of processing, by a plurality of processors 112 the real-time data received from the first set of cameras 104 and the second set of cameras 106 employing a machine learning module 214 to identify a pattern and an anomaly indicating a drowning incident and predict the drowning incident the user 116 involved. Further, the method includes step 406 of alerting, a concerned person 124 about the drowning incident by providing a notification employing the computing device 202 and provide location details of the user 116 involved in the drowning incident. Furthermore, the method includes step 408 of activating, an automated rescue technique 226 to assist the user 116 involved in the drowning incident.
[00068] FIG. 5 illustrates exemplary drowning situations identified by the system 100 displayed through a user interface (a) possible drowning prediction, (b) a possible passive drowning, and (c) an active drowning, in accordance with an embodiment of the present disclosure.
[00069] In an exemplary embodiment, referring to FIG. 5, the exemplary drowning situations identified by the system 100 displayed through a user interface (a) possible drowning prediction, (b) a possible passive drowning, and (c) an active drowning. In FIG. 5(a) a person in a swimming pool with a bounding box labeled "Possible Passive Drowner" and a confidence score of 0.54 is shown on the main display. This suggests that the person has been flagged by the system as possibly being at risk of passive drowning, a situation in which the victim is immersed or floating but not actively moving, utilizing YOLOv8 (You Only Look Once) machine learning technique.
[00070] In another exemplary embodiment, in FIG. 5(b) a person in a swimming pool with a bounding box labeled "Possible Passive Drowner" and a high confidence score of 0.85, indicates that someone is submerged in a pool within the frame identified by analysing the recorded or live videos. This means that the person is not actively moving and may be in danger, suggesting that the YOLOv8 model has identified a possible passive drowning scenario.
[00071] In still another exemplary embodiment, in FIG. 5(c), a person in a swimming pool with a bounding box labeled "Active Drowner" and a confidence score of 0.62, indicates that someone is fully submerged in a pool within the frame identified by analysing the recorded or live videos. This means that the person is not actively moving and may be in danger, suggesting that the YOLOv8 model has identified a possible passive drowning scenario.
[00072] If the specification states a component or feature "may", "can", "could", or "might" be included or have a characteristic, that particular component or feature is not required to be included or have the characteristic.
[00073] As used in the description herein and throughout the claims that follow, the meaning of "a," "an," and "the" includes plural reference unless the context clearly dictates otherwise. Also, as used in the description herein, the meaning of "in" includes "in" and "on" unless the context clearly dictates otherwise.
[00074] It is to be appreciated by a person skilled in the art that while various embodiments of the present disclosure have been elaborated for a system facilitating surveillance and user safety during swimming and the method thereof. However, the teachings of the present disclosure are also applicable for other types of applications as well, and all such embodiments are well within the scope of the present disclosure. However, the smart ambulance providing rapid emergency medical service, and the method thereof is also equally implementable in other industries as well, and all such embodiments are well within the scope of the present disclosure without any limitation.
[00075] Accordingly, the present disclosure provides a system facilitating surveillance and user safety during swimming and the method thereof.
[00076] Moreover, in interpreting the specification, all terms should be interpreted in the broadest possible manner consistent with the context. In particular, the terms "comprises" and "comprising" should be interpreted as referring to elements, components, or steps in a non-exclusive manner, indicating that the referenced elements, components, or steps may be present, or utilized, or combined with other elements, components, or steps that are not expressly referenced. Where the specification claims refer to at least one of something selected from the group consisting of A, B, C….and N, the text should be interpreted as requiring only one element from the group, not A plus N, or B plus N, etc.
[00077] While the foregoing describes various embodiments of the disclosure, other and further embodiments of the disclosure may be devised without departing from the basic scope thereof. The scope of the disclosure is determined by the claims that follow. The disclosure is not limited to the described embodiments, versions or examples, which are included to enable a person having ordinary skill in the art to make and use the disclosure when combined with information and knowledge available to the person having ordinary skill in the art.

ADVANTAGES OF THE PRESENT DISCLOSURE
[00078] The present disclosure provides a system facilitating surveillance and user safety during swimming and the method thereof.
[00079] The present disclosure provides a system and method which facilitates drowning detection by analysing real-time swimming patterns and identifying the pre-drowning behaviour of the user.
[00080] The present disclosure provides a system and method that employs automated safety techniques such as deploying drones or robotic flotation devices once drowning is detected, and provides GPS-based location data to emergency responders.
[00081] The present disclosure provides a system and method that incorporates dynamic visual safety indicators to provide instant visual feedback for swimmers and supervisors based on real-time safety levels.
[00082] The present disclosure provides a system and method that provides guidance such as safe zones, depth warnings, and exit points to swimmers and lifeguards through real-time AR cues using mobile devices.
[00083] The present disclosure provides a system and method that continuously monitors water quality and triggers immediate alerts to the pool management once the water quality falls below safe levels.
[00084] The present disclosure provides a system and method which employs a voice controlled emergency feature to enable the lifeguards to activate rescue mechanisms, trigger alerts, or call emergency services, through voice commands to provide a hands-free response mechanism in critical situations.
 
, Claims:1. A system (100) facilitating surveillance and user safety during swimming, the system (100) comprising:
a first set of cameras (104) integrated within a swimming pool and a second set of cameras (106) placed in the vicinity of the swimming pool (102), wherein the first set of cameras (104) are configured to capture real-time video of a user (116) performing swimming in the swimming pool (102), wherein the second set of cameras (106) are configured to capture the real-time video of a plurality of surroundings of the swimming pool (102) with the motions and activities at the surface, wherein the first set of cameras (104) and the second set of cameras (106) are coupled to a plurality of processors (112) associated with a computing device (202) and a server (122), wherein the plurality of processors (112) is configured to:
receive real-time data from the first set of cameras (104) and the second set of cameras (106), wherein the real time data comprises any or a combination of the real-time video on the motions and activities of the user (116) inside the swimming pool (102), and the real-time video of the surroundings;
process the real-time data by employing a machine learning module (214) to identify a pattern and an anomaly indicating a drowning incident and predict the drowning incident the user (116) involved;
alert a concerned person (124) about the drowning incident by providing a notification employing the computing device (202) and provide location details of the user (116) involved in the drowning incident; and
activate an automated rescue technique (226) to assist the user (116) involved in the drowning incident.
2. The system (100) as claimed in claim 1, wherein the system (100) comprising:
a plurality of sensors (110) integrated within the swimming pool (102) and the plurality of sensors (110) is configured to monitor and acquire a plurality of quality parameters associated with the water in the swimming pool (102); and
a water quality module (216) coupled to the plurality of sensors (110), and the water quality module (216) is configured to process the plurality of quality parameters acquired by the plurality of sensors (110) to access the quality of the water in the swimming pool (102),
wherein the plurality of quality parameters comprises any or a combination of a turbidity, a colour, an odour, a pH, a chemical composition, and a water level.
3. The system (100) as claimed in claim 1, wherein the system (100) comprising:
a plurality of visual safety indicators (224) integrated within the swimming pool (102), and the plurality of visual safety indicators (224) is configured to change colour based on the detection of the drowning incident, wherein the colour comprises at least one of a green, a yellow, and a red,
wherein the green colour indicates a safe condition, the yellow colour indicates a caution, and the red colour indicates a high-risk situation.
4. The system (100) as claimed in claim 1, wherein the system (100) comprising:
a voice-controlled emergency activation system (222) configured to activate the automated rescue technique (226) and trigger alerts to an emergency service through a voice command by providing a hands-free response mechanism in a critical situation,
wherein the automated rescue technique (226) comprises at least one of an automatically deploying a drone and a robotic flotation device to assist the user (116) in distress.
5. The system (100) as claimed in claim 1, wherein the system (100) is configured to:
process the real-time video by a Graphics Processing Unit (GPU) based data processing unit employing the machine learning technique and a predictive behavioural technique to identify the drowning incident beforehand.
6. The system (100) as claimed in claim 1, wherein the system (100) is configured to:
monitor a behaviour of the user (116) in real-time by the predictive behavioural technique to identify a sign of fatigue and an irregular movement to trigger a pre-drowning alert to the concerned person (124) by employing a mobile application and deploy automated rescue technique (226) to assist the user (116) once the system (100) detects an actual drowning.
7. The system (100) as claimed in claim 1, wherein the system (100) comprising:
an Augmented Reality (AR) integration technique (220) configured to:
provide a plurality of visual cues for the user (116) in real-time, wherein the plurality of visual cues comprises any or a combination of a safe zone, a depth warning, and an exit guidance; and
enable the concerned person (124) to locate the user (116) involved in drowning incident and respond faster.
8. The system (100) as claimed in claim 1, wherein the system (100) is configured to:
monitor the plurality of quality parameters continuously by the water quality module (216) to trigger the alerts to a swimming pool (102) management employing the mobile application once the plurality of quality parameters falls below a safe level;
employ the real-time data from a smart wearable device (108) worn by the user (116) and cross-reference the real-time data with the plurality of visual cues to trigger early warnings if the user (116) is showing the signs of distress before to a visual sign of the drowning become apparent, wherein the smart wearable device (108) is configured to monitor any or a combination of a heart rate of the user, a body temperature of the user, and an oxygen levels of the user.
9. The system (100) as claimed in claim 1, wherein the first set of cameras (104) are underwater cameras configured to capture the real-time video of the user (116) within the water to monitor a submersion and an extended inactivity of the user (116),
wherein the second set of cameras (106) are an overhead camera configured to capture a bird's-eye view of the swimming pool (102) providing full surface coverage and detecting surface-level distress signals.
10. A method (400) for surveillance and user safety during swimming by a system (100), the method (400) comprising:
capturing (402), real-time data by a first set of cameras (104) and a second set of cameras (106), wherein the real time data comprises any or a combination of the real-time video on the motions and activities of a user (116) inside the swimming pool (102), and the real-time video of the surroundings;
processing (404), by a plurality of processors (112) the real-time data received from the first set of cameras (104) and the second set of cameras (106) employing a machine learning module to identify a pattern and an anomaly indicating a drowning incident and predict the drowning incident the user (116) involved;
alerting (406), a concerned person (124) about the drowning incident by providing a notification employing the computing device (202) and provide location details of the user (116) involved in the drowning incident; and
activating (408), an automated rescue technique (226) to assist the user (116) involved in the drowning incident.

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