Method and system for detecting fluid level in vessel connected to patient

A system for detecting a fluid level in a fluid vessel connected to a patient, the system comprising:

• a processor;
• and
• a memory coupled to the processor, wherein the memory stores processor executable instructions, which, on execution, causes the processor to:
• receive in real time, via at least one camera, a multimedia content associated with a set of patients within a room, wherein multimedia content comprises at least one of an image or a video feed;
• process the multimedia content to detect a unique identifier associated with a bed of each patient of the set of patients;
• analysis, via a first Artificial Intelligence (AI) model, the multimedia content to detect a fluid vessel attached to the bed of each patient using a pre-defined detection technique;
• estimate the fluid level within the fluid vessel connected to each patient using a pre-defined estimation technique;
• iteratively update, via the AI model, a database based on the fluid level estimated within the fluid vessel connected to each patient and the unique identifier, at a pre-defined time frame;
• identify in real time an issue associated with the fluid level within the fluid vessel connected to at least one patient of the set of patients in response to the updating;
• and
• generate in real time an alert to notify at least one person about the issue associated with the fluid level within the fluid vessel connected to the at least one patient.

A non-transitory computer-readable medium storing computer-executable instructions for detecting a fluid level in a fluid vessel connected to a patient, the stored instructions, when executed by a processor, cause the processor to perform operations comprises:

• receiving in real-time, via at least one camera, a multimedia content associated with a set of patients within a room, wherein the multimedia content comprises at least one of an image or a video feed;
• processing the multimedia content to detect a unique identifier associated with a bed of each patient of the set of patients;
• analysing, via a first Artificial Intelligence (AI) model, the multimedia content to detect a fluid vessel attached to the bed of each patient using a pre-defined detection technique;
• estimating, via the first AI model, the fluid level within the fluid vessel connected to each patient using a pre-defined estimation technique;
• iteratively updating, via the first AI model, a database based on the fluid level estimated within the fluid vessel connected to each patient and the unique identifier, at a pre-defined time frame;
• identifying in real time an issue associated with the fluid level within the fluid vessel connected to at least one patient of the set of patients in response to the updating;
• and
• generating in real-time an alert to notify at least one person about the issue associated with the fluid level within the fluid vessel connected to the at least one patient.