Description:
BACKGROUND
Field of Invention
[001] Embodiments of the present invention generally relate to a task manager and particularly to an automatic deadline prediction and stress monitoring system.
Description of Related Art
[002] Efficient task management remains a central concern in both professional and academic environments. Traditional digital task managers offer basic functionality such as calendar integration, reminders, and priority tagging. Despite widespread use, these systems often lack the ability to incorporate user-specific behavior or adapt to dynamic workload changes. Users frequently face difficulty in maintaining consistent productivity due to rigid schedules that fail to reflect individual working patterns or external stress factors. The reliance on static task allocation without any contextual awareness results in inefficiencies, delays, and burnout.
[003] Several commercial applications attempt to enhance productivity through artificial intelligence. Tools exist that analyze schedules and allocate time slots based on availability. Other applications provide insights into user productivity by tracking application usage, screen time, or keyboard activity. However, these tools operate in isolation, with little to no interoperability across systems. The lack of real-time adaptation to a user’s cognitive or emotional state presents a critical gap. While wearable devices and digital assistants collect various biometric signals, their data remains disconnected from task management workflows.
[004] Efforts to detect stress through physiological signals or behavioral patterns have advanced in recent years. Devices and software can now detect heart rate variability, facial expressions, or typing rhythm to infer stress levels. However, existing technologies do not correlate these stress indicators with workload adjustments or deadline modifications. Users must manually interpret this information and modify their plans accordingly, which diminishes the utility of these tools. The absence of an integrated, context-aware system that manages tasks, adapts deadlines, and optimizes schedules based on both past behavior and real-time data continues to limit overall productivity and well-being.
[005] There is thus a need for an improved and advanced automatic deadline prediction and stress monitoring system that can administer the aforementioned limitations in a more efficient manner.
SUMMARY
[006] Embodiments in accordance with the present invention provide an automatic deadline prediction and stress monitoring system. The system comprising a task manager adapted to receive task details from a predefined source. The system further comprising a monitoring unit adapted to monitor parameters of a user. The system further comprising a processing unit communicatively connected to the task manager and the monitoring unit. The processing unit is configured to receive the monitored parameter of the user from the monitoring unit; analyze the monitored parameters corresponding to the received task details using an Artificial Intelligence (AI) computational technique; generate a stress score from the analyzed parameters corresponding to the received task details; compare the generated stress score with a threshold score; and activate a stress relieving protocol, when the generated stress score is greater than the threshold score, wherein the stress relieving protocol is configured to enable task-breaks, redistribution of work, changes in deadlines, or a combination thereof.
[007] Embodiments in accordance with the present invention further provide a method for task management with automatic deadline prediction and stress monitoring. The method comprising steps of receiving task details from a predefined source; receiving a monitored parameter of a user from a monitoring unit; analyzing the monitored parameters using an Artificial Intelligence (AI) computational technique; generating a stress score from the analyzed parameters corresponding to the received task details; comparing the generated stress score with a threshold score; and activating a stress relieving protocol, when the generated stress score is greater than the threshold score, wherein the stress relieving protocol is configured to enable task-breaks, redistribution of work, changes in deadlines, or a combination thereof.
[008] Embodiments of the present invention may provide a number of advantages depending on their particular configuration. First, embodiments of the present application may be an automatic deadline prediction and stress monitoring system.
[009] Next, embodiments of the present application may provide a stress monitoring system that analyzes past task completion patterns to set achievable deadlines, preventing overcommitment and improving time management accuracy.
[0010] Next, embodiments of the present application may provide a stress monitoring system that detects stress through a typing speed, a keyboard pressure, and facial expressions, ensuring user well-being is continuously monitored without relying on external devices.
[0011] Next, embodiments of the present application may provide a stress monitoring system that adjusts task priorities and deadlines in real time based on current stress levels and workload, leading to a more balanced and sustainable workflow.
[0012] Next, embodiments of the present application may provide a stress monitoring system that provides customized recommendations based on individual work habits, including ideal times for performing different types of tasks, enhancing overall efficiency.
[0013] Next, embodiments of the present application may provide a stress monitoring system that combines multiple features in a single AI-driven platform, offering seamless user experience and superior functionality.
[0014] These and other advantages will be apparent from the present application of the embodiments described herein.
[0015] The preceding is a simplified summary to provide an understanding of some embodiments of the present invention. This summary is neither an extensive nor exhaustive overview of the present invention and its various embodiments. The summary presents selected concepts of the embodiments of the present invention in a simplified form as an introduction to the more detailed description presented below. As will be appreciated, other embodiments of the present invention are possible utilizing, alone or in combination, one or more of the features set forth above or described in detail below.
BRIEF DESCRIPTION OF THE DRAWINGS
[0016] The above and still further features and advantages of embodiments of the present invention will become apparent upon consideration of the following detailed description of embodiments thereof, especially when taken in conjunction with the accompanying drawings, and wherein:
[0017] FIG. 1 illustrates an automatic deadline prediction and stress monitoring system, according to an embodiment of the present invention;
[0018] FIG. 2 illustrates a block diagram of a processing unit, according to an embodiment of the present invention; and
[0019] FIG. 3 depicts a flowchart of a method for task management with automatic deadline prediction and stress monitoring, according to an embodiment of the present invention.
[0020] The headings used herein are for organizational purposes only and are not meant to be used to limit the scope of the description or the claims. As used throughout this application, the word "may" is used in a permissive sense (i.e., meaning having the potential to), rather than the mandatory sense (i.e., meaning must). Similarly, the words “include”, “including”, and “includes” mean including but not limited to. To facilitate understanding, like reference numerals have been used, where possible, to designate like elements common to the figures. Optional portions of the figures may be illustrated using dashed or dotted lines, unless the context of usage indicates otherwise.
DETAILED DESCRIPTION
[0021] The following description includes the preferred best mode of one embodiment of the present invention. It will be clear from this description of the invention that the invention is not limited to these illustrated embodiments but that the invention also includes a variety of modifications and embodiments thereto. Therefore, the present description should be seen as illustrative and not limiting. While the invention is susceptible to various modifications and alternative constructions, it should be understood, that there is no intention to limit the invention to the specific form disclosed, but, on the contrary, the invention is to cover all modifications, alternative constructions, and equivalents falling within the scope of the invention as defined in the claims.
[0022] In any embodiment described herein, the open-ended terms "comprising", "comprises”, and the like (which are synonymous with "including", "having” and "characterized by") may be replaced by the respective partially closed phrases "consisting essentially of", “consists essentially of", and the like or the respective closed phrases "consisting of", "consists of”, the like.
[0023] As used herein, the singular forms “a”, “an”, and “the” designate both the singular and the plural, unless expressly stated to designate the singular only.
[0024] FIG. 1 illustrates an automatic deadline prediction and stress monitoring system 100 (hereinafter referred to as the system 100), according to an embodiment of the present invention. In an embodiment of the present invention, the system 100 may be adapted to monitor a behaviour and stress level of a user. Based upon the monitored behaviour and the stress level, the system 100 may delegate, manage, and allocate tasks to the user. The system 100 may further recommend breaks and recreational activities to the user.
[0025] According to the embodiments of the present invention, the system 100 may incorporate non-limiting hardware components to enhance the processing speed and efficiency such as the system 100 may comprise a task manager 102, a monitoring unit 104, a processing unit 106, and a computing unit 108. In an embodiment of the present invention, the hardware components of the system 100 may be integrated with computer-executable instructions for overcoming the challenges and the limitations of the existing systems.
[0026] In an embodiment of the present invention, the task manager 102 may be adapted to receive task details from a predefined source. The task details may include, but not limited to, a task description, a task deadline, a role in an assigned task, estimated effort or time required, task priority, dependencies on other tasks, deliverable format, recurrence pattern, performance benchmarks, and associated collaborators. The task manager 102 may also store metadata such as a creation timestamp, a task origin, a project category, and an assigned completion criteria. The system 100 may utilize this information to construct a structured task workflow. Embodiments of the present invention are intended to include or otherwise cover any form of task details, including those known in the art, disclosed in related systems, and/or developed in the future.
[0027] The predefined source for receiving the task details may include, but not limited to, an email client, a messaging service, a chatbot interface, a team collaboration platform, a cloud-based portal, a mobile task input application, a voice assistant, an enterprise resource planning (ERP) system, a calendar application, or a task scheduling API integrated with third-party services. The task manager 102 may utilize natural language processing (NLP) or rule-based filters to extract structured task data from unstructured input sources, such as free-form emails or chat messages. Embodiments of the present invention are intended to include or otherwise cover any predefined input source, including existing technologies, variants described in prior art, and technologies later developed or improved for digital communication and task assignment.
[0028] In an embodiment of the present invention, the monitoring unit 104 may be adapted to monitor parameters of the user. The parameters may be, but not limited to, a typing speed, a keyboard press, facial expressions, a mouse movement, and so forth. Embodiments of the present invention are intended to include or otherwise cover any parameters of the user, including known, related art, and/or later developed technologies, that may be monitored by the monitoring unit 104. The monitoring unit 104 may comprise sensors such as, but not limited to, a gaze sensor, a keystroke sensor, an optical sensor, and so forth. Embodiments of the present invention are intended to include or otherwise cover any sensors, including known, related art, and/or later developed technologies, that may be encompassed in the monitoring unit 104.
[0029] In an embodiment of the present invention, the monitoring unit 104 may be integrated into the computing unit 108 of the user. The integration may be accomplished through built-in sensors and system-level Application Programming Interfaces (APIs) that may allow for real-time behavioral monitoring.
[0030] In another embodiment of the present invention, the monitoring unit 104 may be an add-on unit that may be adapted to be arranged in the surrounding environment of the user. The add-on unit may be in the form of an external device such as a sensor pod, a webcam with integrated thermal and gaze tracking capabilities, or an ergonomic desk accessory embedded with sensors. The monitoring unit 104 in this configuration may communicate with the processing unit 106 and computing unit 108 via wired or wireless connections, including but not limited to a Universal Serial Bus (USB), a Bluetooth connection, a Wi-Fi connection, and so forth, for enabling flexible deployment in various work environments.
[0031] In an embodiment of the present invention, the processing unit 106 may be communicatively connected to the monitoring unit 104. The processing unit 106 may further be configured to execute computer-executable instructions to generate an output relating to the system 100. The processing unit 106 may be, but not limited to, a Programmable Logic Control (PLC) unit, a microprocessor, a development board, and so forth. Embodiments of the present invention are intended to include or otherwise cover any type of the processing unit 106 including known, related art, and/or later developed technologies. In an embodiment of the present invention, the processing unit 106 may further be explained in conjunction with FIG. 2.
[0032] FIG. 2 illustrates a block diagram of the processing unit 106, according to an embodiment of the present invention. The processing unit 106 may comprise the computer-executable instructions in form of programming modules such as a data receiving module 200, a data analyzing module 202, a data generation module 204, a data comparison module 206, and a data activation module 208.
[0033] In an embodiment of the present invention, the data receiving module 200 may be configured to receive the task details from the predefined source. The data receiving module 200 may further be configured to receive the monitored parameter of the user. The data receiving module 200 may be configured to transmit the monitored parameter of the user, and the received task details to the data analyzing module 202.
[0034] The data analyzing module 202 may be activated upon receipt of the monitored parameter of the user, and the task details from the data receiving module 200. In an embodiment of the present invention, the data analyzing module 202 may be configured to analyze the monitored parameters corresponding to the received task details using an Artificial Intelligence (AI) computational technique. The Artificial Intelligence (AI) computational technique may be configured to carry out a behavior analysis, a stress adaptation, a predictive deadline recalculation, a dynamic deadline estimation, and so forth. The data analyzing module 202 may be configured to transmit the analyzed parameters to the data generation module 204.
[0035] For example, if the task details indicate that the user is assigned a high-priority, cognitively demanding task with a short deadline, the system 100 may correlate this with the monitored parameters such as increased keyboard pressure, erratic mouse movement, prolonged typing pauses, elevated facial tension, and reduced typing speed. These monitored parameters, associated with a specific task, may indicate heightened stress or cognitive fatigue. Based on this analysis, the AI may predict that the task is unlikely to be completed within the assigned timeframe and may recommend either deadline extension, task reassignment, or an inserted break period. The data analyzing module 202 may be configured to transmit the analyzed parameters, including stress level indicators, productivity scores, and task performance predictions, to the data generation module 204 for further processing.
[0036] The data generation module 204 may be activated upon receipt of the analyzed parameters from the data analyzing module 202. In an embodiment of the present invention, the data generation module 204 may be configured to generate a stress score from the analyzed parameters. The data generation module 204 may be configured to transmit the stress score to the data comparison module 206.
[0037] The data comparison module 206 may be activated upon receipt of the stress score from the data generation module 204. In an embodiment of the present invention, the data comparison module 206 may be configured to compare the generated stress score with a threshold score. Upon comparison, if the generated stress score is less than the threshold score, then the data comparison module 206 may transmit an activation signal to the data activation module 208. Else, the data comparison module 206 may be configured to reactivate the data receiving module 200 to continue receiving the monitored parameter of the user.
[0038] The data activation module 208 may be activated upon receipt of the activation signal from the data comparison module 206. In an embodiment of the present invention, the data activation module 208 may be configured to activate a stress relieving protocol. The stress relieving protocol may be configured to enable task-breaks, redistribution of work, changes in deadlines, and so forth. Embodiments of the present invention are intended to include or otherwise cover any type of activities, including known, related art, and/or later developed technologies, that may be a part of the stress relieving protocol.
[0039] The data activation module 208 may be configured to recommend suggestions to the user. The recommended suggestions may be based on individual user patterns, Further, the recommended suggestions may include dynamic workload adaptation. The suggestions may be, but not limited to, a time management tips, ideal working hours, ideal time slots to conduct different types of work, and so forth. Embodiments of the present invention are intended to include or otherwise cover any recommendations, including known, related art, and/or later developed technologies, that may be suggested to the user. The recommended suggestions may further be displayed on the computing unit 108 of the user. The computing unit 108 may be, but not limited to, a laptop, a smartphone, and so forth. Embodiments of the present invention are intended to include or otherwise cover any type of the computing unit 108, including known, related art, and/or later developed technologies.
[0040] The data activation module 208 may be configured to dynamically adapt workload based on the generated stress score and a task priority to keep a schedule of the user at optimal levels.
[0041] In an exemplary embodiment of the present invention, the system 100 may detect a high-stress level in a user during continuous engagement with high-priority tasks over an extended period. The stress score generated by the data generation module 204 may exceed a predefined threshold, triggering the data comparison module 206 to prevent further task activation. In response, the data activation module 208 may implement a stress-relieving protocol that includes suggesting a 15-minute break, reallocating a non-urgent meeting to the next day, and adjusting the deadline for a medium-priority report by 24 hours. The system 100 may additionally recommend that the user tackle a cognitively demanding task during their identified high-performance period, for example, between 10:00 a.m. and 12:00 p.m., as determined by past behavioral analysis. These suggestions may be displayed via a dashboard on the computing unit 108, which may include, but is not limited to, a laptop, smartphone, tablet, smart display, or wearable device. The system 100 may further provide visualizations such as task reallocation charts, stress trend graphs, and personalized time blocks to enhance the user’s understanding of their schedule and mental state.
[0042] In an embodiment of the present invention, the data activation module 208 may continue to monitor the user feedback and adapt subsequent recommendations through reinforcement learning techniques, ensuring that future suggestions become increasingly aligned with the user's productivity patterns and wellness needs.
[0043] FIG. 3 depicts a flowchart of a method 300 for task management with automatic deadline prediction and stress monitoring, according to an embodiment of the present invention.
[0044] At step 302, the system 100 may receive the task details from the predefined source.
[0045] At step 304, the system 100 may receive the monitored parameter of the user.
[0046] At step 306, the system 100 may analyze the monitored parameters using the Artificial Intelligence (AI) computational technique.
[0047] At step 308, the system 100 may generate the stress score from the analyzed parameters.
[0048] At step 310, the system 100 may compare the generated stress score with the threshold score. Upon comparison, if the generated stress score is greater than the threshold score, then the method 300 may proceed to a step 312. Else, the method 300 may revert to the step 302.
[0049] At step 312, the system 100 may activate the stress relieving protocol.
[0050] At step 314, the system 100 may recommend suggestions to the user.
[0051] While the invention has been described in connection with what is presently considered to be the most practical and various embodiments, it is to be understood that the invention is not to be limited to the disclosed embodiments, but on the contrary, is intended to cover various modifications and equivalent arrangements included within the scope of the appended claims.
[0052] This written description uses examples to disclose the invention, including the best mode, and also to enable any person skilled in the art to practice the invention, including making and using any devices or systems and performing any incorporated methods. The patentable scope of the invention is defined in the claims, and may include other examples that occur to those skilled in the art. Such other examples are intended to be within the scope of the claims if they have structural elements that do not differ from the literal language of the claims, or if they include equivalent structural elements within substantial differences from the literal languages of the claims. , Claims:CLAIMS
I/We Claim:
1. An automatic deadline prediction and stress monitoring system (100), the system (100) comprising:
a task manager (102) adapted to receive task details from a predefined source;
a monitoring unit (104) adapted to monitor parameters of a user; and
a processing unit (106) communicatively connected to the task manager (102) and the monitoring unit (104), characterized in that the processing unit (106) is configured to:
receive the monitored parameter of the user from the monitoring unit (104);
analyze the monitored parameters corresponding to the received task details using an Artificial Intelligence (AI) computational technique;
generate a stress score from the analyzed parameters corresponding to the received task details;
compare the generated stress score with a threshold score; and
activate a stress relieving protocol, when the generated stress score is greater than the threshold score, wherein the stress relieving protocol is configured to enable task-breaks, redistribution of work, changes in deadlines, or a combination thereof.
2. The system (100) as claimed in claim 1, wherein the processing unit (106) is configured to recommend suggestions selected from a time management tips, ideal working hours, ideal time slots to conduct different types of work, or a combination thereof, when the generated stress score is less than the threshold score.
3. The system (100) as claimed in claim 1, wherein the processing unit (106) is configured to dynamically adapt workload based on the generated stress score and a task priority to keep a schedule of the user at optimal levels.
4. The system (100) as claimed in claim 1, wherein the monitored parameters are selected from a typing speed, a keyboard press, facial expressions, a mouse movement, or a combination thereof.
5. The system (100) as claimed in claim 1, wherein the monitoring unit (104) comprises a gaze sensor, a keystroke sensor, an optical sensor, or a combination thereof.
6. The system (100) as claimed in claim 1, wherein the Artificial Intelligence (AI) computational technique is adapted to carry out a behavior analysis, a stress adaptation, a predictive deadline recalculation, a dynamic deadline estimation, or a combination thereof.
7. A method (300) for task management with automatic deadline prediction and stress monitoring, the method (300) is characterized by steps of:
receiving task details from a predefined source;
receiving a monitored parameter of a user from a monitoring unit (104);
analyzing the monitored parameters using an Artificial Intelligence (AI) computational technique;
generating a stress score from the analyzed parameters corresponding to the received task details;
comparing the generated stress score with a threshold score; and
activating a stress relieving protocol, when the generated stress score is greater than the threshold score, wherein the stress relieving protocol is configured to enable task-breaks, redistribution of work, changes in deadlines, or a combination thereof.
8. The method (300) as claimed in claim 7, comprising a step of recommending suggestions selected from a time management tips, ideal working hours, ideal time slots to conduct different types of work, or a combination thereof, when the generated stress score is greater than the threshold score.
9. The method (300) as claimed in claim 7, wherein the monitored parameters are selected from a typing speed, a keyboard press, facial expressions, a mouse movement, or a combination thereof.
10. The method (300) as claimed in claim 7, wherein the Artificial Intelligence (AI) computational technique is adapted to carry out a behavior analysis, a stress adaptation, a predictive deadline recalculation, a dynamic deadline estimation, or a combination thereof.
Date: June 03, 2025
Place: Noida

Nainsi Rastogi
Patent Agent (IN/PA-2372)
Agent for the Applicant