System for monitoring and personalizing comfort of an occupant in a vehicle

Abstract

The present disclosure provides a system for monitoring and personalizing comfort of an occupant in a vehicle. The system comprises a sensing unit integrated into the vehicle. The sensing unit comprises a photoplethysmography (PPG) sensor positioned within a seatback or armrest to measure a heart rate of the occupant, an electrodermal activity (EDA) sensor disposed on at least one surface of the vehicle to monitor a stress level of the occupant, and a posture sensor detecting and correcting a sitting posture of the occupant. A processing unit communicatively coupled to the sensing unit determines a required adjustment for at least one of a climate control setting, a seat positioning parameter, or an ambient lighting condition, generates the occupant-specific suggestions, manages communication between the vehicle and at least one external device, and enforces an encryption and access control to restrict unauthorized access to occupant data.

Description

SYSTEM FOR MONITORING AND PERSONALIZING COMFORT OF AN OCCUPANT IN A VEHICLE TECHNICAL FIELD

[0001] The present disclosure generally relates to vehicle comfort and health monitoring systems. Further, the present disclosure particularly relates to a system for monitoring and personalizing comfort of an occupant in a vehicle. BACKGROUND

[0002] The transportation sector has undergone significant improvements with the integration of digital techniques. The emergence of the Internet of Vehicles (IoV) has led to rapid technical improvements, comprising Machine-to-Machine (M2M) communication and big data analytics. The accelerated adoption of the Internet of Things (IoT) in the automotive sector has contributed to interconnected vehicle systems. Various conventional transportation systems lack personalized comfort aspects which enable real-time adjustments to climate, seating, and entertainment. The absence of such real-time adaptability results in a lack of solutions integrating biometric sensors, data analytics, and IoV connectivity to improve passenger wellness. Traditional systems frequently overlook passenger well-being, leading to discomfort and dissatisfaction among travellers. The absence of integrated biometric sensor techniques and machine learning techniques inDocket No. RP-2024.98.016 2 existing solutions poses challenges in monitoring passenger wellness effectively. Such challenges necessitate improvements in vehicle environments to address stress, fatigue, and air quality issues.

[0003] The lack of real-time monitoring and intervention for passenger well-being presents a major drawback in conventional transportation systems. The Canadian Council of Motor Transport Administrators has reported that 21% of collisions occur due to driver fatigue, leading to approximately 400 deaths and 2,100 serious injuries annually. The absence of real-time intervention mechanisms results in increased vulnerability to health risks, comprising medical emergencies, stress-related concerns, and discomfort during travel. Without adequate intervention, safety concerns are exacerbated, necessitating immediate amendments in monitoring mechanisms to improve passenger well-being. Further, conventional vehicles fail to integrate necessary techniques for monitoring and responding to important health-related factors. By 2030, approximately 95% of new vehicles sold globally will be connected, with 45% possessing intermediate and improved connectivity. Despite said, conventional vehicles remain deficient in integrated techniques which assess and respond to passenger well-being parameters. The lack of real-time adaptability in existing health monitoring mechanisms hinders the ability to assure a modern and safe travel environment. Said deficiency limits vehicle comfort optimization and compromises passenger wellness.Docket No. RP-2024.98.016 3

[0004] The occurrence of discomfort and health issues during prolonged journeys is another drawback associated with conventional vehicle systems. Extended travel durations, inadequate seating ergonomics, limited legroom, and poor air quality contribute to fatigue-related concerns. Such factors exacerbate existing medical conditions and introduce new health risks, affecting the overall travel experience. Without real-time monitoring and intervention mechanisms, passenger discomfort escalates into prolonged health issues, reducing travel efficiency. To mitigate fatigue-related risks, regulatory measures for example the National Safety Code impose restrictions on driving hours. However, the absence of intelligent monitoring systems results in a gap in effectively assessing and addressing passenger wellness.

[0005] Limited customization and non-diverse comfort settings further hinder individualized in-vehicle comfort. The lack of personalized comfort settings forces passengers to rely on standardized vehicle arrangements, restricting adaptability to individual preferences. A more personalized and adaptable vehicle experience improves consumer satisfaction and increases vehicle sales by up to 25%. However, the non-diverse nature of existing vehicle environments fails to accommodate varying passenger needs, leading to a one-size-fits-all experience.

[0006] The global IoV market and automotive IoT market have demonstrated significant growth possibility. The global IoV market is projected to grow from CAD 195.06 billion in 2023 to CAD 911.85 billion by 2030,Docket No. RP-2024.98.016 4 exhibiting a compound annual growth rate (CAGR) of 24.65%. Similarly, the global automotive IoT market is expected to grow from CAD 154.95 billion in 2022 to CAD 1310.36 billion by 2032, with a CAGR of 23.8%. Within the North American market, the Internet of Cars sector is projected to register a CAGR of 24.5% from 2024 to 2029. Additionally, the North American automotive active health monitoring system market was valued at CAD 1.75 billion in 2022 and is expected to dominate the market from 2023 to 2032. Within the IoT sector, the automotive industry in Canada is projected to reach a market volume of CAD 9.26 billion in 2024.

[0007] Despite such growth projections, existing vehicle monitoring systems remain limited in scope. Conventional health monitoring mechanisms offer basic characteristics but lack real-time adaptability and widespread monitoring of parameters for example stress, posture, and air quality assessment. The absence of such monitoring capabilities contributes to discomfort and health risks during extended travel. Addressing such challenges requires a shift towards intelligent, real-time monitoring systems which enable passenger well-being in transportation environments.

[0008] In light of the above discussion, there exists an urgent need for solutions that overcome the drawbacks associated with conventional systems and techniques for passenger health and comfort monitoring in transportation environments.Docket No. RP-2024.98.016 5 SUMMARY

[0009] An objective of the present disclosure is to provide a system for monitoring and personalizing comfort of an occupant in a vehicle by utilizing real-time biometric sensing and automated adjustment mechanisms. The system comprises a sensing unit integrated into the vehicle, including a photoplethysmography (PPG) sensor to measure heart rate, an electrodermal activity (EDA) sensor to monitor stress levels, and a posture sensor to detect and correct sitting posture. A processing unit communicatively coupled to the sensing unit determines a required adjustment for climate control, seat positioning, or ambient lighting, generates occupant-specific suggestions, manages communication with external devices, and enforces encryption and access control for data security. The sensing unit further comprises a temperature sensor and an air quality sensor to assess ambient conditions. The processing unit utilizes a machine learning model to predict occupant fatigue, clusters data to generate recommendations for first-time users, and triggers alerts for posture deviations. Additionally, the processing unit generates haptic feedback for posture correction, regulates climate settings, modulates seat adjustments, and modifies ambient lighting conditions to enhance occupant comfort.Docket No. RP-2024.98.016 6 BRIEF DESCRIPTION OF THE DRAWINGS

[0010] The summary above, as well as the following detailed description of illustrative embodiments, is better understood when read in conjunction with the appended drawings. For the purpose of illustrating the present disclosure, exemplary constructions of the disclosure are shown in the drawings. However, the present disclosure is not limited to specific methods and instrumentalities disclosed herein.

[0011] Embodiments of the present disclosure will now be described, by way of example only, with reference to the following diagrams.

[0012] FIG. 1 illustrates a system 100 for monitoring and personalizing comfort of an occupant of a vehicle, in accordance with various implementations of the present disclosure;

[0013] FIG. 2 illustrates a flow diagram of the system 100 for monitoring and personalizing comfort of an occupant in the vehicle, in accordance with embodiments of the present disclosure;

[0014] FIG. 3 illustrates an in-vehicle network (IvN) architecture, in accordance with embodiments of the present disclosure; and

[0015] FIG. 4 illustrates a vehicle communication within the Internet of Vehicles (IoV) ecosystem, in accordance with embodiments of the present disclosure.Docket No. RP-2024.98.016 7 DETAILED DESCRIPTION OF EMBODIMENTS

[0016] The following detailed description illustrates embodiments of the present disclosure and ways in which they can be implemented. Although some modes of carrying out the present disclosure have been disclosed, those skilled in the art would recognize that other embodiments for carrying out or practicing the present disclosure are also possible.

[0017] FIG. 1 illustrates a system 100 for monitoring and personalizing comfort of an occupant of a vehicle, in accordance with various implementations of the present disclosure. The system 100 for monitoring and personalizing comfort of the occupant of the vehicle comprises a sensing unit 102 integrated into the vehicle to monitor and personalize comfort of the occupant. The sensing unit 102 comprises multiple sensors which detect physiological and environmental parameters associated with the occupant. The sensing unit 102 gathers data in real-time and transmits such data to a processing unit 110 for further analysis and adjustments. The sensing unit 102 is placed within elements of the vehicle to enable continuous monitoring without interfering with occupant movement. The sensing unit 102 processes data using integrated circuitry and transmits signals to associated vehicle systems for adaptive modifications. The sensing unit 102 operates through wired or wireless communication with other vehicle components and external devices.Docket No. RP-2024.98.016 8

[0018] In an embodiment, the sensing unit 102 comprises a photoplethysmography (PPG) sensor 104 positioned within a seatback or armrest to measure a heart rate of the occupant. The PPG sensor 104 utilizes optical techniques to detect volumetric changes in blood circulation within peripheral vessels. The PPG sensor 104 comprises a light-emitting diode and a photodetector, wherein the light-emitting diode emits light into the skin surface, and the photodetector measures variations in light absorption. The PPG sensor 104 transmits acquired data to the processing unit 110 for heart rate analysis and trend identification. The PPG sensor 104 determines fluctuations in heart rate based on detected blood volume changes. The PPG sensor 104 is embedded within seating surfaces to maintain direct contact with the body of the occupant. The PPG sensor 104 adjusts signal sensitivity based on ambient lighting conditions and skin tone variations. The PPG sensor 104 generates heart rate data for assessing physiological responses to environmental factors within the vehicle.

[0019] In an embodiment, the sensing unit 102 comprises an electrodermal activity (EDA) sensor 106disposed on at least one surface of the vehicle to monitor a stress level of the occupant. The EDA sensor 106 detects variations in skin conductance caused by eccrine sweat gland activity. The EDA sensor 106 comprises conductive electrodes which measure electrical resistance across the skin surface. The EDA sensor 106 determines stress levels by analyzing fluctuations in skin conductivity over time. The EDA sensorDocket No. RP-2024.98.016 9 106 interfaces with the processing unit 110 to compare detected signals with predefined stress indicators. The EDA sensor 106 detects involuntary physiological responses triggered by environmental stimuli. The EDA sensor 106 is integrated into contact surfaces for example armrests, steering wheels, or dashboard panels to assure consistent signal acquisition. The EDA sensor 106 operates with minimal power consumption to enable continuous monitoring.

[0020] In an embodiment, the sensing unit 102 comprises a posture sensor 108 that detects and corrects a sitting posture of the occupant. The posture sensor 108 comprises multiple pressure sensors and gyroscopic components to assess spinal alignment and weight distribution. The posture sensor 108 identifies deviations from an optimal seating position based on predefined ergonomic parameters. The posture sensor 108 communicates with the processing unit 110 to generate correction prompts or automatic seat adjustments. The posture sensor 108 detects prolonged static postures and provides real-time feedback for improved seating ergonomics. The posture sensor 108 measures changes in occupant movement to differentiate between normal shifts and improper seating habits.

[0021] In an embodiment, the processing unit 110 is communicatively coupled to the sensing unit 102 to analyze data and generate occupantspecific adjustments. The processing unit 110 determines a required adjustment for at least one of a climate control setting, a seat positioningDocket No. RP-2024.98.016 10 parameter, or an ambient lighting condition based on received sensor inputs. The processing unit 110 executes predefined logic to compare detected parameters with stored comfort profiles. The processing unit 110 evaluates physiological responses and environmental conditions to implement adaptive modifications. The processing unit 110 prioritizes adjustments based on occupant preferences and real-time biometric signals. The processing unit 110 synchronizes with vehicle control systems to dynamically regulate comfortrelated parameters. The processing unit 110 incorporates historical data analysis to refine comfort adjustments over multiple interactions.

[0022] In an embodiment, the processing unit 110 generates occupantspecific suggestions based on analyzed sensor data. The processing unit 110 identifies behavioral patterns and physiological trends to provide personalized recommendations. The processing unit 110 categorizes suggestions based on detected stress levels, posture deviations, and heart rate fluctuations. The processing unit 110 communicates suggested adjustments through a vehicle interface, an external application, or an onboard display. The processing unit 110 ranks suggestions based on suggestions impact on occupant comfort. The processing unit 110 stores user preferences to refine future recommendations. The processing unit 110 enables interactive engagement by allowing manual acceptance or modification of suggested adjustments.

[0023] In an embodiment, the processing unit 110 manages communication between the vehicle and at least one external device. TheDocket No. RP-2024.98.016 11 processing unit 110 interfaces with mobile applications, cloud-based platforms, and external networks for data synchronization. The processing unit 110 transmits processed comfort data for remote access and analysis. The processing unit 110 enables secure connectivity through encrypted communication channels. The processing unit 110 integrates with smart home systems to align vehicle settings with external environmental conditions. The processing unit 110 communicates with wearable health devices to improve biometric monitoring accuracy.

[0024] In an embodiment, the processing unit 110 enforces encryption and access control to restrict unauthorized access to occupant data. The processing unit 110 implements authentication mechanisms to verify authorized users. The processing unit 110 encrypts transmitted and stored data to prevent interception and misuse. The processing unit 110 restricts data access based on predefined security policies. The processing unit 110 employs multi-factor authentication for sensitive data retrieval. The processing unit 110 manages role-based access permissions for multiple occupants within the vehicle. The processing unit 110 logs access events to track data usage and modification history.

[0025] In an exemplary aspect, during an extended highway commute, an occupant enters a vehicle where the system 100 for monitoring and personalizing comfort initiates biometric assessments through the sensing unit 102. The PPG sensor 104 positioned within a seatback detects an initial heartDocket No. RP-2024.98.016 12 rate of 85 beats per minute (bpm), indicating a slightly elevated state. The EDA sensor 106 disposed on the steering wheel registers a skin conductance response of 0.08 micro siemens, suggesting mild stress. The posture sensor 108 embedded within the seat cushion and backrest detects the occupant weight distribution imbalance, identifying a 15-degree forward lean exceeding a predefined threshold for optimal lumbar support. The processing unit 110 analyzes incoming data and determines an adjustment which is required to improve comfort. The processing unit 110 transmits a command to a climate control system to decrease the cabin temperature from 24°C to 22°C based on elevated physiological readings. The processing unit 110 modulates seat positioning by adjusting the recline angle from 95 degrees to 100 degrees and improving lumbar support by 20% to correct the forward-leaning posture. The processing unit 110 modifies ambient lighting from a bright white setting to a warmer 2700K soft tone to promote relaxation. The processing unit 110 generates occupant-specific suggestions through the vehicle interface, recommending a guided breathing exercise to stabilize physiological responses. The processing unit 110 establishes secure communication with an authorized mobile application, enabling remote access to real-time biometric data. The processing unit 110 enforces encryption and access control by requiring a pre-registered authentication token before allowing external device synchronization. A continuous data stream confirms gradual stabilization, with heart rate reducing to 78 bpm and electrodermal activityDocket No. RP-2024.98.016 13 declining to 0.05 microsiemens, validating an effective adjustment. The system 100 continues adaptive monitoring to maintain occupant comfort throughout the journey.

[0026] In an embodiment, the sensing unit 102 may comprise a temperature sensor and an air quality sensor configured to assess ambient conditions within the vehicle. The temperature sensor detects variations in cabin temperature and transmits real-time data to the processing unit 110. The temperature sensor measures values as degrees Celsius or Fahrenheit, allowing dynamic adjustments based on occupant comfort preferences and external environmental conditions. The temperature sensor is positioned within an overhead console, dashboard, or seat to assure accurate detection of air temperature surrounding the occupant. The air quality sensor evaluates particulate matter, volatile organic compounds, and carbon dioxide levels within the vehicle. The air quality sensor analyzes gaseous pollutants and airborne contaminants by detecting changes in resistance across sensing elements. The air quality sensor transmits data to the processing unit 110, which determines whether ventilation adjustments are required. For instance, if the air quality sensor detects carbon dioxide levels exceeding 1000 ppm, the processing unit 110 triggers ventilation adjustments to introduce fresh air into the cabin. If the temperature sensor detects a temperature above 28°C, the processing unit 110 lowers the setpoint of an air conditioning system toDocket No. RP-2024.98.016 14 maintain thermal comfort. The air quality sensor also monitors humidity levels and triggers dehumidification control when relative humidity exceeds 60%.

[0027] In an embodiment, the processing unit 110 may utilize a machine learning model to determine a required adjustment and predict the occupant fatigue level. The processing unit 110 receives heart rate data from the PPG sensor 104 and skin conductance data from the EDA sensor 106. The processing unit 110 analyzes historical biometric trends and real-time physiological signals to assess fatigue patterns. For example, if heart rate of the occupant decreases to 60 bpm while electrodermal activity remains low for more than 15 minutes, the processing unit 110 detects a possible fatigue state. The processing unit 110 considers contextual factors, for example time of day and trip duration, to refine fatigue detection accuracy. The processing unit 110 utilizes facial microexpression data from an external device, for example a camera, to further verify fatigue likelihood. If the processing unit 110 determines a high probability of fatigue, an adjustment is implemented, comprising seat vibration activation, temperature reduction, or alert notifications. If the occupant displays signs of fatigue for an extended period, the processing unit 110 recommends a rest break through an auditory or visual alert.

[0028] In an embodiment, the processing unit 110 can execute a realtime analysis to cluster occupant data to generate recommendations for firsttime users using unsupervised learning techniques. The processing unit 110Docket No. RP-2024.98.016 15 collects biometric and behavioral data from multiple sensors to identify common occupant comfort profiles. The processing unit 110 clusters historical and real-time data points without predefined labels to categorize occupant preferences. For instance, if multiple first-time users exhibit a resting heart rate between 70 bpm and 80 bpm while preferring a cabin temperature of 22°C, the processing unit 110 assigns subsequent first-time users with similar biometric patterns to the same preference category. The processing unit 110 analyzes correlations between posture adjustments, temperature preferences, and ambient lighting selections to create occupant-specific comfort settings. The processing unit 110 applies pattern recognition to refine default recommendations based on evolving biometric data. The processing unit 110 generates recommended seat adjustments and climate control settings for first-time users to improve comfort without requiring manual customization.

[0029] In an embodiment, the processing unit 110 may trigger an alert based on a deviation beyond a threshold posture angle detected by the posture sensor 108. The posture sensor 108 monitors spinal alignment, weight distribution, and seat pressure to detect deviations exceeding ergonomic thresholds. If the occupant leans forward beyond a threshold angle of 20 degrees for more than five minutes, the processing unit 110 triggers a visual alert on a vehicle display or an auditory warning through an onboard speaker system. The processing unit 110 evaluates sustained posture deviations by assessing variations in weight distribution over time. If a detected deviationDocket No. RP-2024.98.016 16 remains uncorrected despite initial alerts, the processing unit 110 increases alert frequency or introduces additional corrective actions.

[0030] In an embodiment, the processing unit 110 may generate a haptic feedback signal via a vibration element embedded in a seat when posture correction is required. The processing unit 110 determines the required intensity and duration of haptic feedback based on the severity of posture deviation detected by the posture sensor 108. For example, if the occupant exhibits a slouched posture for more than five minutes, the processing unit 110 initiates a low-intensity vibration to prompt realignment. If the occupant leans excessively toward one side, the processing unit 110 triggers directional vibration cues on the affected seat region to indicate corrective movement.

[0031] In an embodiment, the processing unit 110 can regulate a climate control setting by adjusting at least one of a temperature, a humidity level, a ventilation level, an airflow level, and a direction thereof. The processing unit 110 processes real-time ambient temperature and humidity data to determine climate adjustments. For instance, if a detected cabin temperature exceeds a predefined threshold, the processing unit 110 lowers the air conditioning setpoint to restore occupant comfort. If humidity levels rise above 70%, the processing unit 110 activates a dehumidification mode. If the occupant registers a skin temperature above 37°C, the processing unit 110 increases ventilation airflow toward the upper body region.Docket No. RP-2024.98.016 17

[0032] In an embodiment, the processing unit 110 may modulate a motorized seat adjustment unit to modify a seat angle, a lumbar support, a seat inclination, and a headrest position. The processing unit 110 retrieves stored occupant preferences or analyzes real-time posture data to determine required adjustments. If the posture sensor 108 detects prolonged discomfort, the processing unit 110 modifies lumbar support by increasing or decreasing pressure applied to the lower back. If upper body of the occupant exhibits tension, the processing unit 110 reclines the seat by 5 degrees to alleviate strain. The processing unit 110 adjusts a headrest position based on detected head tilt patterns to improve neck support.

[0033] In an embodiment, the processing unit 110 may adjust an ambient lighting condition by modifying at least one of a color, a temperature, an intensity, and a distribution pattern. The processing unit 110 evaluates biometric data to determine optimal lighting configurations for occupant comfort. If the EDA sensor 106 detects heightened stress, the processing unit 110 reduces light intensity and shifts the color spectrum to warmer tones. If the occupant displays signs of fatigue, the processing unit 110 increases blue light intensity to improve alertness.

[0034] FIG. 2 illustrates a flow diagram of the system 100 for monitoring and personalizing comfort of an occupant in the vehicle, in accordance with embodiments of the present disclosure. The system 100 begins operation when the occupant enters the vehicle, initiating a sensing unit 102 whichDocket No. RP-2024.98.016 18 collects real-time biometric and environmental data. The sensing unit 102 comprises a PPG sensor 104 measuring heart rate, an EDA sensor 106 monitoring stress levels, and a posture sensor 108 detecting and correcting sitting posture. The sensing unit 102 transmits collected data to a processing unit 110, which analyzes received inputs to determine required adjustments. Based on processed data, the processing unit 110 regulates climate control, seat positioning, and ambient lighting to improve occupant comfort. Additionally, the processing unit 110 manages security protocols and external communication by enforcing encryption and access control measures. The processing unit 110 continuously refines adjustments based on evolving biometric trends, assuring a personalized comfort experience. The system 100 completes operation by dynamically modifying vehicle settings to align with occupant-specific physiological and environmental conditions.

[0035] FIG. 3 illustrates an in-vehicle network (IvN) architecture, in accordance with embodiments of the present disclosure. The IvN architecture integrates multiple gateways, sensors, and communication protocols for data exchange. The IoV access gateway is centrally positioned to connect various IvN using an Ethernet Backbone. Two IvN domain gateways manage communication between LiDAR sensors, electronic control units (ECUs), and additional vehicle sensors through high-speed controller area network flexible data-rate (CAN-FD) communication. LiDARs are connected via Ethernet for high-bandwidth data transmission. Sensors distributed throughout the vehicleDocket No. RP-2024.98.016 19 collect environmental and biometric data, enabling real-time monitoring and decision-making.

[0036] FIG. 4 illustrates a vehicle communication within the IoV ecosystem, in accordance with embodiments of the present disclosure. A central vehicle, labeled LoV, interacts with multiple external entities using various communication channels. Vehicle-to-Vehicle (V2V) communication enables direct data exchange with nearby vehicles to improve safety and traffic coordination. Vehicle-to-Infrastructure (V2I) links the vehicle with traffic management systems and smart road infrastructure. Vehicle-to-Person (V2P) facilitates interaction with personal devices, enabling passenger-specific services. Vehicle-to-Cloud (V2C) connects the vehicle to cloud-based servers for data processing, over-the-air updates, and remote diagnostics. Vehicle-toSensor (V2S) communication integrates the vehicle with environmental monitoring sensors for real-time adjustments. The interconnected system enables autonomous decision-making, predictive analytics, and improved situational awareness within the IoV ecosystem.

Claims

CLAIMS What is claimed is:

1. A system for monitoring and personalizing comfort of an occupant of a vehicle, comprising: a sensing unit integrated into the vehicle, wherein the sensing unit comprises: a photoplethysmography (PPG) sensor positioned within a seatback or an armrest to measure a heart rate of the occupant; an electrodermal activity (EDA) sensor disposed on at least one surface of the vehicle to monitor a stress level of the occupant; and a posture sensor configured to detect and correct a sitting posture of the occupant; a processing unit communicatively coupled to the sensing unit, wherein the processing unit is configured to: determine a required adjustment for at least one of a climate control setting, a seat positioning parameter, or an ambient lighting condition;Docket No. RP-2024.98.016 21 generate the occupant-specific suggestions; manage communication between the vehicle and at least one external device; and enforce an encryption and access control to restrict an unauthorized access to occupant data.

2. The system of claim 1, wherein the sensing unit further comprises a temperature sensor, and an air quality sensor configured to assess the ambient conditions within the vehicle.

3. The system of claim 1, wherein the processing unit utilizes a machine learning model to determine the required adjustment and predict an occupant fatigue level.

4. The system of claim 1, wherein the processing unit executes a real-time analysis to cluster the occupant data to generate the recommendations for the first-time users using the unsupervised learning techniques.

5. The system of claim 1, wherein the processing unit triggers an alert based on a deviation beyond a threshold posture angle detected by the posture sensor.

6. The system of claim 1, wherein the processing unit generates a haptic feedback signal via a vibration module embedded in the seat when posture correction is required.Docket No. RP-2024.98.016 22 7. The system of claim 1, wherein the processing unit regulates a climate control setting by adjusting at least one of a temperature, a humidity level, or a ventilation level, an airflow level and direction thereof.

8. The system of claim 1, wherein the wherein the processing unit modulates a motorized seat adjustment unit to modify a seat angle, a lumbar support, a seat inclination, and a headrest position. The system of claim 1, wherein the processing unit adjusts an ambient lighting condition by modifying at least one of a color, a temperature, an intensity, and a distribution pattern.