A system and method for improving skin condition

Abstract

The present invention disclosed a system and method for improving skin, scalp and hair condition. The method involves receiving user input comprising personal skin, scalp and hair characteristics and a geographical location, retrieving real-time environmental conditions for the geographical location, and processing this information using a recommendation engine to generate personalized skincare and haircare recommendations. The personal skin, scalp and hair characteristics include skin, scalp and hair type and skin, scalp and hair condition, while the real-time environmental conditions include humidity, temperature, UV index, pollution level, and wind conditions. The recommendation engine maps the skin, scalp and hair condition and the real-time environmental conditions to a dermatological and trochology knowledge base to provide customized product suggestions.

Description

[0001] A SYSTEM AND METHOD FOR IMPROVING SKIN CONDITION

[0002] FIELD OF INVENTION:

[0003] The present invention relates to a system and method for improving skin condition. Particularly it relates to a system and method which can analyzes skin, scalp and hair and recommends solutions to improve the conditions.

[0004] BACKGROUND OF INVENTION:

[0005] In recent years, skin, scalp and hair health whether on face or scalp has gained significant attention due to its impact on both appearance and overall well-being. Traditional methods for assessing skin, scalp and hair conditions, such as visual inspections by dermatologists / trichologists or self-diagnosis, are often subjective, time-consuming, and prone to inaccuracies. These methods rely heavily on the expertise of professionals, which may not always be accessible or affordable.

[0006] Traditional skincare and haircare recommendation systems suffer from several significant limitations that prevent users from receiving truly personalized and effective guidance. Existing approaches typically rely on static questionnaires or occasional self-assessments that fail to account for the dynamic nature of skin, scalp and hair conditions, which can vary significantly based on environmental factors, seasonal changes, and real-time conditions.

[0007] Most conventional systems operate in isolation, addressing skin concerns basis skin, or hair concerns basis the skin of the head / scalp type , or addressing either skincare or haircare separately, requiring users to navigate multiple platforms and potentially conflicting advice. Furthermore, existing recommendation engines typically provide generic advice based on broad categorizations rather than considering the specific environmental conditions a user will encounter on a particular date or in a specific location. Why are environmental factors important?

[0008] Because the skin, hair, and scalp continuously interact with the ambient environment, a truly personalized dermatocosmetic algorithm must treat weather parameters (humidity, temperature, UV, wind, pollution) as core inputs, not optional features. Environmental stressors impose dynamic fluctuations on barrier integrity, hydration gradients, oxidative load, and microbial equilibrium; neglecting them in a recommendation engine introduces systematic error that cannot be learned away via static user parameters alone (e.g. skin type, age). Incorporating weather data as mandatory predictors constitutes both a novel and necessary axis of personalization, filling a known gap in most D2C beauty recommendation systems, which typically rely only on user-reported features and ignore real-time microclimate modulation.

[0009] Humidity and Temperature. Low ambient humidity and high temperature accelerate transepidermal water loss (TEWL) by increasing vapor pressure gradients across the stratum corneum. TEWL is a well-validated metric of barrier disruption [Alexander et al., 2018; Kundu et al., 2025] and correlates with dryness, tightness, and sensitization. In hot, dry conditions, the lipid matrix becomes more fluid and permeability rises; conversely, very high humidity (>80 %) may saturate the barrier and disturb osmotic balance. These effects propagate to hair / scalp: elevated humidity can swell keratin and lift cuticle scales, increasing frizz and uptake of water (imbalance of internal water content) [Cedirian et al., 2025]. Temperature cycles also modulate sebum viscosity and microbial growth rates on scalp, altering local microflora equilibrium.

[0010] UV Radiation. Solar UV (UVA / UVB) exposure induces oxidative stress in both skin and hair. In skin, UV triggers lipid peroxidation, matrix metalloproteinase induction, and inflammatory mediator release, damaging the barrier and increasing TEWL. In hair shafts, UV degrades surface lipids (notably 18-MEA), oxidizes proteins, and breaks disulfide bonds, leading to increased porosity, brittleness, and loss of tensile strength [Yang et al., 2024; Samra et al., 2024]. The effect is intensified when hair is wet (amplified radical generation) [Samra et al., 2024].

[0011] Pollution and Particulate Matter. Airborne pollutants (PM2.5 / PM10, polyaromatic hydrocarbons, volatile organic compounds) deposit onto the skin and scalp, triggering reactive oxygen species (ROS), inflammation, and barrier lipid oxidation [Gu et al., 2024; Son et al., recent review]. On scalp, pollutants can clog follicles, exacerbate dandruff or sensitivity, and promote hair loss. On hair fibers, particulate matter infiltrates cuticle gaps, binds sebum, extracts lipids and proteins, and degrades gloss and strength [Qu et al., 2018; Samra et al., 2024].

[0012] Wind / Airflow. Wind increases the convective removal of the boundary layer of humid air, thereby steepening water vapor gradient and accelerating TEWL especially under moderate RH. It also mechanically lifts cuticle edges and may abrade delicate hair or compromise scalp integrity with microabrasions.

[0013] Interaction Effects and Algorithmic Necessity. Real- world exposure rarely involves a single parameter in isolation; for example, high humidity + heat + sunlight synergize to induce hyper-permeability, oxidative stress, and barrier fatigue faster than any one factor alone. A weather-aware algorithm can dynamically weight these interactions (e.g. UV stress weight increases under low humidity, or pollutant damage weight amplifies under wind) to tailor actives, dosage, frequency, and formulation type (e.g. water-rich gel in humid, occlusive cream in dry). Generic recommendation models that ignore environmental variability are blind to transient barrier perturbations and therefore cannot optimize product adjustment or anticipate flare periods. In sum, the integration of real-time weather parameters is both technically non-obvious and functionally essential to achieve robust personalization of skin / hair regimen across climates and microclimates.

[0014] Current personalization methods rely heavily on subjective self-reporting, which is prone to inaccuracies and inconsistencies. Users may misidentify their skin, scalp and hair type, underestimate environmental impacts, or fail to recognize subtle changes in their skin, scalp and hair condition. While some advanced systems incorporate basic environmental data such as general weather conditions, they lack the sophistication to provide date-specific, location-based recommendations that account for the complex interplay between personal characteristics and real-time environmental factors.

[0015] Additionally, existing systems lack objective validation mechanisms to verify the accuracy of user inputs or to provide real-time adjustments based on actual skin, scalp and hair conditions. The absence of integrated diagnostic tools means that recommendations remain static and cannot adapt to changing conditions or provide feedback on the effectiveness of suggested regimens.

[0016] Several commercial systems have attempted to address aspects of personalized skincare and haircare recommendations. Korean Patent No. KR101852511B1 discloses an "Apparatus and Method for Recommending Cosmetics according to User Skin Type," which determines skin type through questionnaires and recommends suitable cosmetics from a database. While this system provides personalized recommendations based on skin type classification, it relies entirely on static questionnaires without objective validation, lacks environmental data integration, and cannot provide date- specific or location-based guidance.

[0017] There is therefore a need for an integrated system that can provide unified skincare and haircare recommendations based on specific target dates and locations, incorporating real-time environmental data and objective diagnostic measurements to deliver truly personalized and adaptive cosmetic guidance.

[0018] Furthermore, the majority of these devices are not capable of providing personalized recommendations based on the unique characteristics of an individual’s skin, which can vary significantly due to factors like environment, location and lifestyle. Therefore, the Inventors of the present invention came up with the novel and inventive solution to the above mentioned problems.

[0019] OBJECT OF INVENTION

[0020] The principle object of the present invention is to overcome all the mentioned and drawbacks of the prior arts by providing a system and method for improving skin, scalp and hair condition.

[0021] Another object of the present invention is to provide a unified recommendation system that addresses both skincare and haircare needs through a single integrated platform, eliminating the need for multiple separate applications and potentially conflicting advice.

[0022] Another object of the present invention is to provide a system and method for improving skin, scalp and hair condition that can analyze the user’s skin, scalp and hair from images or manual inputs.

[0023] Yet another object of the present invention is to provide a system and method for improving skin, scalp and hair condition that incorporates external environment factors basis the location of the user.

[0024] Yet another object of the present invention is to provide a system and method for improving skin, scalp and hair condition that incorporates the user’s health and medical history.

[0025] Yet another object of the present invention is to provide a system and method for improving skin, scalp and hair condition that takes into consideration the current skin, scalp and hair care routine of the user. Yet another object of the present invention is to provide a system and method for improving skin, scalp and hair condition that analyses the data from various inputs and provides various suggestion to improve the skin, scalp and hair conditions. The inputs can be but not limited to the time based / outcome based solutions; hair washing habits, hair styling habits (coloring, heat styling, treatments etc.)

[0026] Another object of the present invention is to provide a system and method for enhancing skin, scalp and hair health by predicting future skin, scalp and hair conditions. The system utilizes various factors such as the user’s current skin, scalp and hair condition, medical history, lifestyle, habits, environmental factors, and geographic location to offer personalized recommendations and preventive measures, enabling the user to proactively safeguard their skin, scalp and hair from potential damage.

[0027] Yet another object of the present invention is to provide a system that receives a target date and geographical location from users, retrieving specific environmental conditions for that date and location to generate contextually relevant skincare and haircare recommendations.

[0028] Yet another object of the present invention is to provide comprehensive skincare and haircare recommendations that include beneficial ingredients, ingredients to avoid, oral supplement recommendations, sleep habit advice, dietary suggestions, lifestyle and behavior changes, and skincare and haircare routine / styling modifications.

[0029] A further object of the present invention is to incorporate objective diagnostic measurements through disposable sensor elements embedded in product packaging, providing coded categorical outputs for parameters such as sebum level, hydration level, pH level, flake presence, redness level, and UV exposure level to refine personalized recommendations. A further object of the present invention is to enable validation of tokenized diagnostic codes from disposable sensor elements, mapping them to categorical parameters for seamless integration into the recommendation process while maintaining data integrity and user privacy.

[0030] An additional object of the present invention is to map personal skin, scalp and hair characteristics and real-time environmental conditions to a comprehensive dermatological / trichology based knowledge base comprising skincare / haircare ingredients and skincare / haircare products, ensuring scientifically-grounded recommendations.

[0031] An additional object of the present invention is to utilize external data sources such as open weather application programming interfaces (APIs) to ensure reliable, up- to-date environmental information for accurate recommendation generation.

[0032] Yet another object of the present invention is to provide a scalable system architecture that can accommodate future enhancements and additional diagnostic parameters without requiring fundamental changes to the core recommendation framework.

[0033] SUMMARY OF THE INVENTION:

[0034] This summary is provided to introduce a selection of concepts in a simplified form that are further disclosed in the detailed description of the invention. This summary is not intended to identify key or essential inventive concepts of the claimed subject matter, nor is it intended for determining the scope of the claimed subject matter.

[0035] The present invention is all about a system and method for improving skin, scalp and hair and hair condition. The main aspect of the present invention is to provide a system for improving skin, scalp and hair conditions having a user interface configured to receive user input comprising personal skin, scalp and hair characteristics and a geographical location, a data retrieval engine configured to retrieve real-time environmental conditions for the geographical location from an external data source, a recommendation engine configured to process the user input and the real-time environmental conditions to generate personalized skincare and haircare recommendations, said personal skin, scalp and hair characteristics can be skin, scalp and hair type and skin, scalp and hair condition, said real-time environmental conditions can be but not limited humidity, temperature, UV index, pollution level, and wind conditions, said recommendation engine being configured to map the skin, scalp and hair condition and said real-time environmental conditions to a dermatological knowledge and trichology knowledge base having skincare and haircare ingredients and skincare / haircare products, and said skincare and haircare recommendations comprises personalized product suggestions based on the user's skin, scalp and hair type, skin, scalp and hair condition, and the real-time environmental conditions.

[0036] Another aspect of the present invention is to provide a method for providing personalized skincare and haircare recommendations, the method comprising: receiving user input comprising personal skin, scalp and hair characteristics and a geographical location through a user interface; retrieving real-time environmental conditions for the geographical location from an external data source; processing the user input and the real-time environmental conditions using a recommendation engine to generate personalized skincare and haircare recommendations ; wherein the recommendation engine maps the personal skin, scalp and hair characteristics and the real-time environmental conditions to a dermatological and trochology knowledge base comprising skincare and haircare ingredients and skincare and haircare products; and providing customized product suggestions based on the user's skin, scalp and hair type, skin, scalp and hair condition, and the real-time environmental conditions; wherein the method further comprises receiving a target date for the personalized skincare and haircare recommendations, and the real-time environmental conditions are retrieved for the geographical location on the target date; wherein the method further comprises receiving diagnostic data from a disposable sensor element embedded in product packaging, the sensor element configured to produce a coded categorical output for at least one parameter selected from sebum level, hydration level, pH level, flake presence, redness level, and UV exposure level, and refining the personalized skincare and haircare recommendations based on the diagnostic data.

[0037] As per another aspect of the present invention, the personal skin, scalp and hair characteristics comprise skin type selected from but not limited to the group consisting of normal, oily, dry, combination, and sensitive and hair type selected from the group consisting of oily, dry, sensitive, and balanced respectively. This standardized categorization enables systematic processing and consistent recommendation generation across different user profiles.

[0038] As per another aspect of the present invention, the personal skin, scalp and hair characteristics comprise skin condition selected from but not limited to the group consisting of acne, redness, dullness, wrinkles, dark spots, and uneven skin tone and comprise hair condition selected from but not limited to the group consisting of hairfall, dandruff, breakage, frizz, greys, volume, scalp acne, and slow growth. This comprehensive condition assessment allows the system to address specific dermatological and trichology concerns with targeted ingredient recommendations.

[0039] As per another aspect of the present invention, the skin, scalp and hair condition is entered by the user through at least one of typing, photo upload, or face scanning. This multi-modal input approach accommodates different user preferences and capabilities while maintaining assessment accuracy.

[0040] As per another aspect of the present invention, the real-time environmental conditions comprise humidity, temperature, UV index, pollution level, and wind conditions. This comprehensive environmental profiling enables the system to account for all major external factors that influence skin, scalp and hair health and product performance.

[0041] As per another aspect of the present invention, the system for providing personalized skincare and haircare recommendations, the system comprising: a user interface configured to receive user input comprising personal skin, scalp and hair characteristics and a geographical location; a data retrieval engine configured to retrieve real-time environmental conditions for the geographical location from an external data source; a recommendation engine configured to process the user input and the realtime environmental conditions to generate personalized skincare and haircare recommendations ; wherein the recommendation engine is configured to map the personal skin, scalp and hair characteristics and the real-time environmental conditions to a dermatological and trichology knowledge base comprising skincare and haircare ingredients and skincare and haircare products; wherein the system is configured to provide customized product suggestions based on the user's skin, scalp and hair type, skin, scalp and hair condition, and the real-time environmental conditions; and a sensor interface configured to receive diagnostic data from a disposable sensor element embedded in product packaging, the sensor element configured to produce a coded categorical output for at least one parameter selected from sebum level, hydration level, pH level, flake presence, redness level, and UV exposure level, and refine the personalized skincare and haircare recommendations based on the diagnostic data. As per another aspect of the present invention, the personalized skincare and haircare recommendations further comprise at least one of oral supplement recommendations, sleep habit advice, dietary suggestions, lifestyle and behavior changes, and skincare and haircare routine modifications. This comprehensive wellness approach addresses skin, scalp and hair health through multiple intervention pathways, maximizing treatment effectiveness.

[0042] As per another aspect of the present invention, the system further comprises a sensor interface configured to receive diagnostic data from a disposable sensor element embedded in product packaging. This innovative integration enables objective biological measurement without requiring separate diagnostic devices or complex user procedures.

[0043] As per another aspect of the present invention, the sensor interface is configured to validate tokenized diagnostic codes and map them to categorical parameters for refining the personalized skincare and haircare recommendations. This validation and mapping system ensures data integrity while seamlessly integrating objective measurements into the recommendation process.

[0044] BRIEF DESCRIPTION OF THE DRAWINGS:

[0045] The foregoing summary, as well as the following detailed description of the invention, is better understood when read in conjunction with the appended drawings. For the purpose of illustrating the invention, exemplary constructions of the invention are shown in the drawings.

[0046] Figure 1 shows a flowchart of a method for providing personalized skincare and haircare recommendations including receiving user input, retrieving environmental conditions, and processing data through a recommendation engine, and providing tailored product / ingredient / supplement suggestions. Figure 2 shows a flowchart detailing the process of receiving user input comprising personal skin, scalp and hair characteristics and geographical location through a user interface.

[0047] Figure 3 shows a flowchart of retrieving real-time environmental conditions for a geographical location from an external data source and classifying environmental parameters.

[0048] Figure 4 shows a flowchart of processing user input and real-time environmental conditions using a recommendation engine to generate personalized skincare and haircare recommendations through dermatological and trichology knowledge base mapping.

[0049] Figure 5 shows a block diagram of a personalized skincare and haircare recommendation system comprising a user interface, data retrieval engine, recommendation engine, and database components.

[0050] Figure 6 shows a flowchart of the Phase 1 Skin Algorithm for single-date personalized skincare recommendations incorporating user inputs, environmental data, and decision engine processing.

[0051] Figure 7 shows a flowchart of the Phase 2 Hair and Scalp Algorithm for single-date personalized haircare recommendations integrating scalp and hair characteristics with environmental conditions.

[0052] Figure 8 shows a flowchart of the Phase 3 Sensor-Integrated Refinement incorporating disposable sensor elements for objective biological measurements and recommendation refinement. Figure 9 shows a flowchart of the Phase 4 Accuracy Expansion demonstrating advanced category inputs and enhanced environmental variables for maximum recommendation precision.

[0053] DETAILED DESCRIPTION OF THE INVENTION:

[0054] Detailed method of the present invention are disclosed herein, however, it is to be understood that the disclosed method are merely exemplary of the invention, which may be embodied in various forms. Therefore, specific details disclosed herein are not to be interpreted as limiting, but merely as a basis for the claims and as a representative basis for teaching one skilled in the art to variously employ the present invention in virtually any appropriately detailed structure.

[0055] Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which the invention belongs.

[0056] The objects, features, and advantages of the present invention will now be described in greater detail. Also, the following description includes various specific details and is to be regarded as merely exemplary. Accordingly, those of ordinary skill in the art will recognize that: without departing from the scope of the present disclosure and its various embodiments there may be any number of changes and modifications described herein.

[0057] Throughout the invention, the term ‘allergy’ herein refers to ingredient avoidance logic rather than medical allergy diagnostics.

[0058] It must also be noted that as used herein and in the appended claims, the singular forms "a", "an," and "the" include plural references unless the context clearly dictates otherwise. Although any systems and methods similar or equivalent to those described herein can be used in the practice or testing of embodiments of the present invention, the preferred, systems are now described.

[0059] The main embodiment of the present invention is to provide a system and method for improving skin, scalp and hair condition.

[0060] According to the main embodiment of the present invention, method for providing personalized skincare and haircare recommendations, the method comprising: a. receiving user input comprising personal skin, scalp and hair characteristics and a geographical location through a user interface; b. retrieving real-time environmental conditions for the geographical location from an external data source; c. processing the user input and the real-time environmental conditions using a recommendation engine to generate personalized skincare and haircare recommendations; d. wherein the recommendation engine maps the personal skin, scalp and hair characteristics and the real-time environmental conditions to a dermatological and trichology knowledge base comprising skincare and haircare ingredients and skincare and haircare products; and e. providing customized product suggestions based on the user's skin, scalp and hair type, skin, scalp and hair condition, and the real-time environmental conditions; f. wherein the method further comprises receiving a target date for the personalized skincare and haircare recommendations, and the realtime environmental conditions are retrieved for the geographical location on the target date; g. wherein the method further comprises receiving diagnostic data from a disposable sensor element embedded in product packaging, the sensor element configured to produce a coded categorical output for at least one parameter selected from sebum level, hydration level, pH level, flake presence, redness level, and UV exposure level, and refining the personalized skincare and haircare recommendations based on the diagnostic data.

[0061] As per detailed embodiment of the present invention, said skin and scalp type can be but not limited from the group consisting of normal, oily, dry, combination, and sensitive for skin and oily, dry, sensitive and balanced for scalp.

[0062] As per detailed embodiment of the present invention, the personal skin, scalp and hair characteristics comprise skin condition selected from the group consisting of acne, redness, dullness, wrinkles, dark spots, and uneven skin, scalp and hair tone and hair condition selected from the group consisting of hairfall, dandruff, breakage, frizz, greys, volume, scalp acne, and slow growth.

[0063] As per detailed embodiment of the present invention, the skin, scalp and hair condition is entered by the user through at least one of typing, photo upload, or face scanning.

[0064] As per detailed embodiment of the present invention, the real-time environmental conditions comprise humidity, temperature, UV index, pollution level, and wind conditions.

[0065] As per detailed embodiment of the present invention, the recommendation engine comprises an algorithm that processes the user input and the real-time environmental conditions to provide the personalized skincare and haircare recommendations.

[0066] As per detailed embodiment of the present invention, the personalized skincare and haircare recommendations comprise beneficial ingredients and ingredients to avoid for the user. As per detailed embodiment of the present invention, the personalized skincare and haircare recommendations further comprise information on oral supplements to mitigate skin, scalp and hair conditions.

[0067] As per detailed embodiment of the present invention, a system for providing personalized skincare and haircare recommendations, the system comprising: a. a user interface configured to receive user input comprising personal skin, scalp and hair characteristics and a geographical location; b. a data retrieval engine configured to retrieve real-time environmental conditions for the geographical location from an external data source; c. a recommendation engine configured to process the user input and the realtime environmental conditions to generate personalized skincare and haircare recommendations; d. wherein the recommendation engine is configured to map the personal skin, scalp and hair characteristics and the real-time environmental conditions to a dermatological and trichology knowledge base comprising skincare and haircare ingredients and skincare and haircare products; e. wherein the system is configured to provide customized product suggestions based on the user's skin, scalp and hair type, skin, scalp and hair condition, and the real-time environmental conditions; and f. a sensor interface configured to receive diagnostic data from a disposable sensor element embedded in product packaging, the sensor element configured to produce a coded categorical output for at least one parameter selected from sebum level, hydration level, pH level, flake presence, redness level, and UV exposure level, and refine the personalized skincare and haircare recommendations based on the diagnostic data.

[0068] As per detailed embodiment of the present invention, the personal skin, scalp and hair characteristics comprise skin type selected from the group consisting of normal, oily, dry, combination, and sensitive, and skin condition selected from the group consisting of acne, redness, dullness, wrinkles, dark spots, and uneven skin tone .The hair type selected from, but not limited to the group consisting of straight, wavy, curly and coily , scalp type selected from the group consisting of oily, dry, sensitive, balanced and hair condition selected from the group consisting of hairfall, dandruff, breakage, frizz, greys, volume, scalp acne, and slow growth.

[0069] As per detailed embodiment of the present invention, the user interface is configured to receive the skin, scalp and hair condition through at least one of typing, photo upload, or face scanning.

[0070] As per detailed embodiment of the present invention, the real-time environmental conditions comprise humidity, temperature, UV index, pollution level, and wind conditions.

[0071] As per detailed embodiment of the present invention, the external data source is an open weather application programming interface (API).

[0072] As per detailed embodiment of the present invention, a database configured to store the dermatological and trichology knowledge base.

[0073] As per detailed embodiment of the present invention, the recommendation engine comprises an algorithm configured to process the user input and the real-time environmental conditions to provide the personalized skincare and haircare recommendations.

[0074] As per detailed embodiment of the present invention, the personalized skincare and haircare recommendations further comprise at least one of oral supplement recommendations, sleep habit advice, dietary suggestions, lifestyle and behavior changes, and skincare routine modifications. As per detailed embodiment of the present invention, a sensor interface configured to receive diagnostic data from a disposable sensor element embedded in product packaging.

[0075] As per detailed embodiment of the present invention, the sensor interface is configured to validate tokenized diagnostic codes and map them to categorical parameters for refining the personalized skincare and haircare recommendations.

[0076] While the examples provided herein relate to the face skin, scalp and hair and scalp, it will be apparent to a person skilled in the art that the invention can be similarly applied to any other region of the body skin without departing from the scope of the present disclosure.

[0077] The system and method of the present invention can be further illustrated through the flow charts as shown in Fig. 1 to Fig.9 of the present invention. As depicted in Fig. 1 to Fig. 5, in step (100), the system initiates the process by receiving user input that includes personal skin, scalp and hair and scalp characteristics and a geographical location through a user interface. The user interface is designed to collect detailed personal skin, scalp and hair characteristics, which encompass both skin, scalp and hair type and skin, scalp and hair condition. The skin, scalp and hair type can be selected from categories such as normal, oily, dry, combination, and sensitive, as described in sub-step (100-a); scalp type can be selected from categories such as oily, dry, sensitive, balanced ; hair type can be selected from categories such as straight , wavy, curly and coily. Additionally, the skin condition can be specified from options including but not limited to acne, redness, dullness, wrinkles, dark spots, and uneven skin tone; hair and scalp condition can be specified from options including but not limited to hairfall, dandruff, breakage, frizz, greys, volume, scalp acne and slow growth, as outlined in sub-step (100-b). The user can enter their skin, scalp and hair condition through various methods such as typing, photo upload, or face scanning, as indicated in sub- step (100-c). The geographical location provided by the user is used for retrieving real-time environmental conditions, which will later be used to tailor the skincare and haircare recommendations. The user interface ensures that the input data is accurately captured and transmitted to the subsequent processing stages.

[0078] The actions associated with this step include receiving the skin, scalp and hair condition through at least one of typing, photo upload, or face scanning, and receiving user input comprising personal skin, scalp and hair characteristics and a geographical location through a user interface. These actions are aimed at collecting comprehensive user data for the personalized skincare and haircare recommendation process.

[0079] The system's user interface is configured to facilitate the collection of this data efficiently. The geographical location and personal skin, scalp and hair characteristics are gathered to provide a foundation for the recommendation engine to process and generate customized skincare and haircare advice. This initial step ensures that the subsequent steps have accurate and relevant data to work with, ultimately leading to effective and personalized skincare and haircare recommendations.

[0080] In step (102), the system retrieves real-time environmental conditions for the geographical location from an external data source. The entities involved in this step include temperature, geographical location, external data source, real-time environmental conditions, wind conditions, humidity, pollution level, and UV index. The external data source is exemplified by an open weather application programming interface (API), which provides the necessary environmental data.

[0081] The process begins with the data retrieval engine, which is configured to access the external data source. The engine retrieves various environmental parameters such as but not limited to the temperature, humidity, UV index, pollution level, and wind conditions for a given date and location. These parameters are then classified into categories: humidity as high or low or normal, temperature as high or low or normal, UV index as high or low, pollution level as high or low, and wind conditions as strong or calm. This classification helps in standardizing the data for further processing.

[0082] The retrieved and classified environmental conditions are then stored as real-time environmental conditions. These conditions are used by the recommendation engine to generate personalized skincare and haircare recommendations. The recommendation engine uses this data in conjunction with the user's personal skin, scalp and hair characteristics to map the conditions to a dermatological and trichology knowledge base. This knowledge base includes skincare and haircare ingredients and products that are suitable for different environmental conditions and skin, scalp and hair types.

[0083] By retrieving and classifying real-time environmental conditions, the system ensures that the skincare and haircare recommendations are not only personalized based on the user's skin, scalp and hair characteristics but also optimized for the current environmental conditions. This step exemplifies the system's ability to adapt to dynamic environmental factors, thereby providing more accurate and effective skincare and haircare advice.

[0084] In step (104), the system processes the user input and the real-time environmental conditions using a recommendation engine to generate personalized skincare and haircare recommendations. This step is further divided into sub-steps (104-a), (104- b), and (104-c) to elaborate on the intricate processes involved.

[0085] In sub-step (104-a), the recommendation engine maps the skin, scalp and hair condition and the real-time environmental conditions to a dermatological and trichology knowledge base comprising skincare and haircare ingredients and skincare and haircare products. The dermatological and trichology knowledge base, which is stored in a database, serves as a repository of skincare and haircare information. This mapping process involves correlating the user's skin, scalp and hair condition and the environmental factors such as humidity, temperature, UV index, pollution level, and wind conditions with the knowledge base to identify suitable skincare and haircare ingredients and products. The recommendation engine utilizes an algorithm to facilitate this mapping, ensuring that the skincare and haircare recommendations are customized to the user's specific needs.

[0086] Sub-step (104-b) emphasizes that the dermatological and trichology knowledge base is stored in a database. This storage mechanism ensures that the knowledge base is easily accessible and can be efficiently queried by the recommendation engine. The database acts as a structured repository, maintaining a comprehensive collection of skincare and haircare ingredients and products, which are used for generating accurate and personalized recommendations.

[0087] In sub-step (104-c), the recommendation engine, which comprises an algorithm, processes the user input and the real-time environmental conditions to provide the personalized skincare and haircare recommendations. The algorithm plays a role in analyzing the data and generating recommendations that are customized to the user's skin, scalp and hair type, skin, scalp and hair condition, and the prevailing environmental conditions. The personalized skincare and haircare recommendations are customized ingredient / product suggestions that aim to address the user's unique skincare and haircare needs.

[0088] The recommendation engine's ability to process user input and real-time environmental conditions, map this data to a dermatological and trichology knowledge base, and utilize an algorithm to generate personalized skincare and haircare recommendations exemplifies a sophisticated and dynamic approach to skincare and haircare personalization. This method ensures that users receive skincare and haircare advice that is not only specific to their skin, scalp and hair characteristics but also responsive to the environmental conditions they are exposed to, thereby enhancing the effectiveness and relevance of the skincare and haircare ingredients / products recommended.

[0089] In step (106), the system provides customized product / ingredient suggestions based on the user's skin, scalp and hair type, skin, scalp and hair condition, and the realtime environmental conditions. The entities involved in this step include the realtime environmental conditions, skin, scalp and hair type, personalized skincare and haircare recommendations, and skin, scalp and hair condition.

[0090] The process begins with the system utilizing the real-time environmental conditions, which encompass factors such as humidity, temperature, UV index, pollution level, and wind conditions. These conditions are retrieved and classified by the data retrieval engine from an external data source, such as an open weather application programming interface (API). The classification of these conditions into categories like high or low or normal for humidity and temperature, strong or calm for wind conditions, and so on, helps in tailoring the recommendations more precisely.

[0091] Simultaneously, the user's skin, scalp and hair type and skin, scalp and hair condition are considered. The skin type can be normal, oily, dry, combination, or sensitive; scalp type can be oily, dry, sensitive, or balanced; hair type can be straight, wavy, curly or coily while the skin condition can include issues like acne, redness, dullness, wrinkles, dark spots, and uneven skin tone, scalp and hair condition can include issues like hairfall, dandruff, breakage, frizz, greys, volume, scalp acne, slow growth. These personal skin, scalp and hair characteristics are received through the user interface, which allows input via typing, photo upload, or face scanning.

[0092] The recommendation engine, which includes an algorithm, processes the user input and the real-time environmental conditions. This engine maps the skin, scalp and hair condition and the environmental data to a dermatological and trichology knowledge base stored in a database. This knowledge base comprises skincare and haircare ingredients and products, which are used to tailor product suggestions based on the user's skin, scalp and hair type, skin, scalp and hair condition, and the real-time environmental conditions.

[0093] The customized product suggestions are then provided to the user. These suggestions are based on the comprehensive analysis of the user's skin, scalp and hair type, skin, scalp and hair condition, and the current environmental conditions. The system ensures that the recommendations are personalized, taking into account the unique combination of factors affecting the user's skin, scalp and hair at any given time.

[0094] In essence, step (106) exemplifies the system's ability to integrate various data points and deliver customized skincare and haircare advice, thereby enhancing the user's skincare and haircare regimen with scientifically-backed, real-time recommendations.

[0095] In different embodiments, the user interface (502) is responsible for receiving user input, which includes personal skin, scalp and hair characteristics and geographical location. In certain embodiments, the user input comprises skin, scalp and hair type and skin, scalp and hair condition, which can be entered through typing, photo upload, or face scanning. The user interface (502) collects this data to gather personal skin, scalp and hair characteristics and geographical location. The geographical location allows the system to retrieve real-time environmental conditions pertinent to the user's location.

[0096] In certain embodiments, the user interface (502) works in conjunction with the data retrieval engine (504), which retrieves real-time environmental conditions such as humidity, temperature, UV index, pollution level, and wind conditions from an external data source, such as an open weather application programming interface (API). The data retrieval engine (504) categorizes these environmental conditions to provide accurate and relevant data for the recommendation engine (506).

[0097] The recommendation engine (506) processes the user input and the real-time environmental conditions to generate personalized skincare and haircare recommendations. This processing involves mapping the skin, scalp and hair condition and the real-time environmental conditions to a dermatological and trichology knowledge base stored in a database (508). The recommendation engine (506) uses an algorithm to process the data and generate customized product suggestions based on the user's skin, scalp and hair type, skin, scalp and hair condition, and the real-time environmental conditions. The dermatological and trichology knowledge base includes skincare and haircare ingredients and products and also includes lifestyle corrections, routine suggestions, which are used for providing accurate and effective skincare and haircare recommendations.

[0098] The personalized skincare and haircare recommendations are then provided to the user through the user interface (502). These recommendations are customized to the user's specific skin, scalp and hair type and condition, as well as the current environmental conditions, ensuring that the user receives the most suitable skincare and haircare advice. The system's comprehensive approach, involving the user interface (502), data retrieval engine (504), recommendation engine (506), and database (508), ensures that the personalized skincare and haircare recommendations are both accurate and effective.

[0099] In different embodiments, the data retrieval engine (504) is responsible for retrieving real-time environmental conditions from an external data source. In certain embodiments, the data retrieval engine (504) retrieves real-time environmental conditions such as temperature, humidity, UV index, pollution level, and wind conditions for the specified geographical location. In certain embodiments, the external data source is an open weather application programming interface (API), which provides the necessary environmental data. The data retrieval engine (504) categorizes these environmental conditions into classifications such as high or low for humidity, temperature, and UV index, and strong or calm for wind conditions.

[0100] In certain embodiments, the data retrieval engine (504) works in conjunction with the user interface (502), which receives user input including personal skin, scalp and hair characteristics and geographical location. The user input and real-time environmental conditions are then processed by the recommendation engine (506) to generate personalized skincare and haircare recommendations. The recommendation engine (506) maps the skin, scalp and hair condition and real-time environmental conditions to a dermatological and trichology knowledge base stored in the database (508). This knowledge base includes skincare and haircare ingredients and products, which are used to tailor product suggestions based on the user's skin, scalp and hair type, skin, scalp and hair condition, and the real-time environmental conditions.

[0101] The data retrieval engine (504) ensures that the environmental data is up-to-date and accurately reflects the current conditions of the user's geographical location. This real-time data is used by the recommendation engine (506) to provide relevant and effective skincare and haircare recommendations. The integration of the data retrieval engine (504) with other components such as the user interface (502) and the recommendation engine (506) exemplifies a comprehensive approach to personalized skincare, leveraging both user-specific data and environmental factors to optimize skincare and haircare advice.

[0102] In different embodiments, the recommendation engine (506) is responsible for processing user input and real-time environmental conditions to generate personalized skincare and haircare recommendations. In certain embodiments, the recommendation engine (506) processes the user input, which includes personal skin, scalp and hair characteristics and geographical location, and the real-time environmental conditions, which include humidity, temperature, UV index, pollution level, and wind conditions. The recommendation engine (506) maps the skin, scalp and hair condition and the real-time environmental conditions to a dermatological and trichology knowledge base 508 that includes skincare and haircare ingredients and products.

[0103] In certain embodiments, the recommendation engine (506) utilizes an algorithm to process the user input and the real-time environmental conditions. This algorithm is designed to generate personalized skincare and haircare recommendations by mapping the skin, scalp and hair condition and the real-time environmental conditions to the dermatological and trichology knowledge base (508). The dermatological and trichology knowledge base (508) is stored in a database and includes a comprehensive repository of skincare and haircare ingredients and products.

[0104] The recommendation engine (506) provides customized product suggestions based on the user's skin, scalp and hair type, skin, scalp and hair condition, and the realtime environmental conditions. These personalized skincare and haircare recommendations are generated by processing the user input and the real-time environmental conditions using the algorithm within the recommendation engine (506). The customized product suggestions are designed to address the specific needs of the user's skin, scalp and hair type and condition, taking into account the current environmental factors.

[0105] In certain embodiments, the recommendation engine (506) is configured to receive user input through a user interface (502), which collects personal skin, scalp and hair characteristics and geographical location. The real-time environmental conditions are retrieved by a data retrieval engine (504) from an external data source, such as an open weather application programming interface (API). The data retrieval engine (504) classifies the environmental conditions, including humidity, temperature, UV index, pollution level, and wind conditions, to provide accurate and relevant data for the recommendation engine (506). The recommendation engine (506) processes this data to generate personalized skincare and haircare recommendations, ensuring that the product suggestions are customized to the user's specific skin, scalp and hair type and condition, as well as the current environmental conditions. This comprehensive approach ensures that the skincare and haircare recommendations are both personalized and effective, addressing the unique needs of each user based on their individual skin, scalp and hair characteristics and the environmental factors they are exposed to.

[0106] In different embodiments, the database (508) is responsible for storing the dermatological and trichology knowledge base. In certain embodiments, the dermatological and trichology knowledge base includes comprehensive information on skincare and haircare ingredients and products. The database (508) ensures that this knowledge base is maintained and readily accessible for the recommendation engine (506). The recommendation engine (506) processes user input and real-time environmental conditions to generate personalized skincare and haircare recommendations. The user input includes personal skin, scalp and hair characteristics such as skin, scalp and hair type and skin, scalp and hair condition, while the real-time environmental conditions encompass factors like humidity, temperature, UV index, pollution level, and wind conditions.

[0107] In certain embodiments, the recommendation engine (506) maps the skin, scalp and hair condition and real-time environmental conditions to the dermatological and trichology knowledge base stored in the database (508). This mapping process involves an algorithm that correlates the user's skin, scalp and hair type and condition with the environmental data to provide customized product suggestions. The database (508) plays a role in this process by ensuring that the dermatological and trichology knowledge base is up-to-date and comprehensive, allowing the recommendation engine (506) to generate accurate and personalized skincare and haircare recommendations. The dermatological and trichology knowledge base stored in the database (508) is used by the recommendation engine (506) to function effectively. It includes detailed information on various skincare and haircare ingredients and products, which the recommendation engine (506) uses to tailor its recommendations based on the user's specific skin, scalp and hair type and condition, as well as the current environmental conditions. This ensures that the personalized skincare and haircare recommendations are not only accurate but also relevant to the user's needs and the prevailing environmental factors.

[0108] In summary, the database (508) stores the dermatological and trichology knowledge base, enabling the recommendation engine (506) to generate personalized skincare and haircare recommendations by mapping user input and real-time environmental conditions to the stored knowledge base. This process ensures that the recommendations are customized to the user's skin, scalp and hair type and condition, as well as the current environmental conditions, providing a comprehensive and personalized skincare and haircare solution.

[0109] Figure 6 illustrates an embodiment of the Phase 1 Skin Algorithm for single-date personalized skincare recommendations. This flowchart demonstrates the foundational phase of the system that processes user inputs and environmental data to generate date-specific skincare guidance for a selected target location and date.

[0110] The process begins with user inputs (601) comprising city and target date information, along with skin type selected from normal, oily, dry, combination, and sensitive categories, and skin conditions such as acne, redness, dullness, wrinkles, pigmentation, and uneven tone. These personal skin characteristics establish the individual profile that serves as the foundation for personalized recommendation generation.

[0111] Simultaneously, the system accommodates multiple capture modes (602) including dropdowns and quiz interfaces for standardized data entry, photo upload capabilities for visual skin, scalp and hair assessment, and face scan functionality using artificial intelligence for automated skin, scalp and hair analysis. This multimodal approach ensures accessibility while maintaining assessment accuracy across different user preferences and technological capabilities. The data entry may be mandatory for the phase 1 and phase 2 in order to collect the data and train the module.

[0112] The target-date environment fetch component (603) retrieves comprehensive environmental data for the specified city and target date, including humidity, temperature, UV index, pollution levels, and wind conditions. This environmental data integration enables the system to account for the specific external factors that will affect skin health and product performance on the selected date, distinguishing this approach from static recommendation systems.

[0113] The quantization process (604) transforms both user inputs and environmental data into categorical features through systematic mapping to bins such as low, medium, and high classifications. This categorization enables the system to process complex data inputs through configurable or learned thresholds, ensuring consistent and reproducible recommendations while maintaining the flexibility to adapt to varying conditions.

[0114] Safety and filters components (605) implement ingredient allergies and preferences screening along with sensitivity gates and avoid lists. Safety and Filters components (605) implement exclusion rules for contraindicated ingredients and known irritants unsuitable for specific skin / scalp / hair types or conditions. The term ‘allergy’ herein refers to ingredient avoidance logic rather than medical allergy diagnostics.

[0115] The decision engine (606) operates using rules, machine learning, or hybrid approaches to fuse profile and environment bins for optimal ingredient guidance and product selection. This sophisticated analytical framework processes the categorized inputs to generate scientifically-grounded recommendations that address both individual skin needs and environmental challenges for the specific target date.

[0116] The system generates same-day skin outputs (607) comprising ingredient guidance with specific recommendations for cleansers, moisturizers, night treatments, and sunscreen, along with comprehensive do's and don'ts for the target date. Additionally, the system provides ingredients to avoid and optional supplement pointers, delivering actionable guidance that users can immediately implement for their skincare routine on the specified date.

[0117] This implementation establishes the foundational capability for date-specific, location-based skincare recommendations that integrate personal skin characteristics with real-time environmental conditions. The systematic approach to data categorization and processing ensures consistent recommendation quality while the multi-modal input system enhances user accessibility. The result is a comprehensive skincare guidance system that adapts to both individual user needs and specific environmental conditions, providing unprecedented personalization accuracy for single-date skincare planning.

[0118] Figure 7 illustrates an embodiment of the Phase 2 Hair and Scalp Algorithm for single-date personalized haircare recommendations. This flowchart demonstrates the second phase of the system that extends the personalized recommendation framework to encompass both skincare and haircare guidance for a unified cosmetic care approach on a selected target date.

[0119] The process begins with user inputs (701) comprising city and target date information, along with scalp type classification such as dry, oily, balanced or sensitive, hair type and texture characteristics including straight, wavy, curly, coily and fine, medium, or thick classifications respectively, and primary concerns such as hairfall, dandruff, breakage , frizz, greys, volume, scalp acne or slow growth. These comprehensive hair and scalp characteristics establish the individual profile that serves as the foundation for personalized haircare recommendation generation, complementing the skin-focused inputs from Phase 1.

[0120] The system accommodates multiple capture modes (702) including dropdowns and quiz interfaces for standardized data entry, and optional photo cues for texture and volume assessment along with lifestyle toggles for heat styling frequency, chemical treatments, and environmental exposure patterns. This multi-modal approach ensures comprehensive data collection while maintaining user accessibility and assessment accuracy across different hair types and styling preferences. The data entry may be mandatory for the phase 1 and phase 2 in order to collect the data and train the module.

[0121] The target-date environment fetch (703) component retrieves the same comprehensive environmental data used in Phase 1, including humidity, temperature, UV index, and pollution levels for the specified city and target date. This environmental data integration enables the system to account for the specific external factors that will affect hair and scalp health on the selected date, recognizing that environmental conditions impact both skin, scalp and hair simultaneously.

[0122] The quantization process (704) transforms both user inputs and environmental data into categorical features through systematic mapping to bins such as low, medium, and high classifications for scalp type, hair type and texture, and environmental factors. This categorization enables the system to process complex hair-specific data inputs through configurable or learned thresholds, ensuring consistent and reproducible recommendations while maintaining the flexibility to adapt to varying hair conditions and styling needs.

[0123] Safety and filters components (705) implement fragrance sensitivity screening for scalp-applied products, allergies identification for common hair care ingredients, and regional availability considerations for product recommendations. Safety and Filters components (705) implement exclusion rules for contraindicated ingredients and known irritants unsuitable for specific skin / scalp / hair types or conditions. The term ‘allergy’ herein refers to ingredient avoidance logic rather than medical allergy diagnostics.

[0124] The decision engine (706) operates using rules, machine learning, or hybrid approaches to fuse profile and environment bins for optimal hair and scalp care guidance. The engine applies specialized logic for hair- specific concerns such as anti-humidity film formation for frizz control, chelation for hard water areas, and protein-moisture balance optimization based on hair porosity and damage levels, while maintaining consistency with the skin care decision framework from Phase 1.

[0125] The system generates same-day hair and scalp outputs (707) comprising ingredient guidance with specific recommendations for shampoos, scalp treatments, leave-in products, and masks, along with comprehensive do's and don'ts for hair care on the target date. Additionally, the system provides optional supplement pointers for hair health support, delivering actionable guidance that users can immediately implement for their haircare routine for the specified date while maintaining consistency with any concurrent skincare recommendations.

[0126] This Phase 2 implementation extends the personalized recommendation framework to create a unified skincare and haircare system that addresses both domains for the same target date and location. The integration of hair and scalp-specific inputs with the same environmental data used for skin recommendations ensures consistency and efficiency in the overall cosmetic care approach. The systematic approach to hair-specific categorization and processing ensures that recommendations account for the unique properties of hair and scalp care while maintaining the same level of personalization accuracy established in Phase 1, resulting in comprehensive cosmetic guidance that addresses the user's complete beauty care needs for any selected date. Figure 8 illustrates an embodiment of the Phase 3 Sensor- Integrated Refinement for single-date personalized recommendations. This flowchart demonstrates the third phase of the system that incorporates disposable sensor elements embedded in product packaging to provide objective biological measurements that refine the existing skincare and haircare recommendations established in Phases 1 and 2.

[0127] The process begins with base inputs from Phases 1-2 (801), comprising city and target date information, skin type and conditions, and scalp / hair type, texture, and concerns. These foundational inputs establish the user profile that has already been processed through the initial recommendation phases, providing a comprehensive baseline for sensor-based refinement.

[0128] Simultaneously, the system incorporates pack-embedded disposable indicator elements (802) that measure sebum levels, hydration levels, pH levels, flake presence, and UV exposure through simple 1-2 step processes involving dab, press, or peel actions. These disposable sensors are integrated directly into secondary packaging, eliminating the need for separate diagnostic devices while providing objective biological measurements that complement the subjective user inputs from previous phases.

[0129] The token capture and validation process (803) involves manual code entry or micro-QR scanning with checksum and lot provenance verification to ensure data integrity and quality control. This validation system prevents user error while maintaining privacy by avoiding the storage of raw images, instead processing only tokenized categorical outputs that map directly to the system's existing input framework.

[0130] The map indicator to categorical bins component (804) transforms the sensor outputs into low, medium, and high classifications or class labels that refine existing inputs for skin, scalp and hair type, condition, sebum, hydration, pH and UV exposure status. This mapping process ensures that the objective sensor data integrates seamlessly with the categorical framework established in Phases 1 and 2, maintaining consistency in the recommendation engine's processing approach.

[0131] The merge with target-date environment step (805) combines the refined sensorbased inputs with the same comprehensive environmental data used in previous phases, including humidity, temperature, UV index, pollution levels, and wind conditions. This integration ensures that the sensor refinements are contextualized within the specific environmental conditions that will affect the user on their selected target date.

[0132] The decision engine operates (806) using rules, machine learning, or hybrid approaches to reweight selections using indicator bins, improving texture and film selection while maintaining active intensity optimization. The engine processes the sensor-refined inputs through the same analytical framework used in Phases 1 and 2, but with enhanced precision due to the objective biological measurements that validate and adjust the initial user-reported characteristics.

[0133] The system generates both same-day skin outputs (807) and same-day hair and scalp outputs (808), each comprising ingredient guidance and do's and don'ts recommendations, along with optional ingredient / product-class suggestions for cleansers, moisturizers, night treatments, sunscreens, shampoos, scalp treatments, leave-in products, and masks. These outputs represent the refined recommendations that incorporate both the comprehensive user profiling from Phases 1-2 and the objective sensor validation, resulting in enhanced accuracy and personalization.

[0134] This Phase 3 implementation introduces objective biological validation into the personalized recommendation framework without disrupting the user experience or requiring complex procedures. The integration of disposable sensor elements provides real-time refinement of user inputs while maintaining the systematic approach to categorization and processing established in previous phases. The result is a significantly enhanced recommendation system that combines the convenience of self-reported inputs with the accuracy of objective measurements, delivering unprecedented personalization precision for both skincare and haircare guidance on any selected target date.

[0135] Figure 9 illustrates an embodiment of the Phase 4 Accuracy Expansion for singledate personalized recommendations. This flowchart demonstrates the fourth and most advanced phase of the system that incorporates additional category-level inputs and optional secondary sensor indicators to maximize recommendation precision while maintaining the same user-friendly approach established in previous phases.

[0136] The process begins with core inputs (901) from Phases 1-2, comprising city and target date information, skin type and conditions, and scalp / hair type, texture, and concerns. These foundational inputs represent the comprehensive user profile established through the initial phases, providing the baseline data that has already been processed through the basic recommendation framework and sensor refinement from Phase 3.

[0137] Phase 4 category inputs introduce (902) additional contextual variables that enhance recommendation accuracy without increasing user effort. These inputs include temporal and event context such as life events and special occasions, medical context for cosmetic use including procedural history and preferences, and constraints that help filter and refine product selections. This expanded input framework enables the system to account for nuanced factors that significantly impact skincare and haircare needs but are often overlooked in conventional recommendation systems.

[0138] Optional indicators version 2 (903) represent advanced sensor capabilities including narrow-range pH measurements, hard-water detection strips, optical glare index assessments, and other single-use diagnostic codes. These enhanced diagnostic tools provide even more precise biological measurements than the basic sensors introduced in Phase 3, enabling fine-tuned adjustments to recommendations based on specific environmental and physiological factors.

[0139] The target-date environment fetch component (904) continues to retrieve comprehensive environmental data including humidity, temperature, UV index, pollution levels, and wind conditions, but now incorporates extensions such as dew point measurements, diurnal temperature range analysis, pollutant mix composition, indoor climate and humidity flags, and water hardness indices. This expanded environmental profiling provides unprecedented detail about the conditions that will affect skin and hair health on the selected target date.

[0140] Validation and privacy measures (905) include token checksum and lot metadata verification to ensure data integrity, while maintaining privacy by requiring no raw images and implementing sanity checks on input ranges. This robust validation framework ensures that the enhanced diagnostic capabilities maintain the same privacy-light approach established in Phase 3 while providing additional quality control mechanisms.

[0141] The quantization process (906) maps all inputs to bins through low, medium, and high classifications or class labels, with configurable or learned thresholds that can be adjusted based on accumulated data and performance metrics. This systematic categorization ensures that the expanded input set maintains compatibility with the decision engine framework while enabling more nuanced differentiation between user profiles and environmental conditions.

[0142] Safety and filters components (907) implement comprehensive screening including medical contraindications for cosmetic use, buffer actives management, fragrance sensitivity and allergy filters, and regional availability and budget filters. These enhanced protective measures ensure that the increased recommendation precision does not compromise user safety or accessibility, maintaining the system's commitment to personalized yet responsible guidance.

[0143] The decision engine (908) operates using rules, machine learning, or hybrid approaches to reweight selections using Phase-4 categories, incorporating texture and film strength selection optimization, active intensity calibration, and deterministic processing for identical feature bins to ensure recalibratable results. This sophisticated analytical framework processes the expanded input set while maintaining the consistency and reproducibility established in previous phases, ensuring that identical inputs continue to produce identical outputs.

[0144] The system generates comprehensive same-day skin outputs (909) and same-day hair and scalp outputs (910), each comprising detailed ingredient guidance and do's and don'ts recommendations, along with optional product-class suggestions for cleansers, moisturizers, night treatments, sunscreens, shampoos, scalp treatments, leave-in products, and masks. These outputs represent the pinnacle of personalized cosmetic guidance, incorporating all available data sources to deliver maximum accuracy and relevance for the selected target date.

[0145] This Phase 4 implementation represents the complete evolution of the personalized recommendation system, incorporating every available data source and analytical capability to deliver unprecedented accuracy in cosmetic guidance. The systematic integration of expanded environmental data, advanced sensor capabilities, contextual variables, and enhanced safety measures creates a comprehensive platform that addresses virtually every factor that can influence skincare and haircare needs. The result is a sophisticated yet accessible system that maintains the user-friendly approach of earlier phases while delivering professional-grade personalization accuracy that adapts to the complete spectrum of individual needs and environmental conditions for any selected target date. The system implements a progressive four-phase architecture that evolves from basic personalization to comprehensive accuracy enhancement. Each phase builds upon the previous phase while maintaining backward compatibility and user accessibility.

[0146] Phase 1 implements the foundational skin algorithm for single-date personalized skincare recommendations. The algorithm processes user inputs comprising city and target date information, skin type selected from normal, oily, dry, combination, and sensitive categories, and skin conditions including acne, redness, dullness, wrinkles, pigmentation, and uneven tone. The system accommodates multiple capture modes including dropdowns and quiz interfaces for standardized data entry, photo upload capabilities for visual skin assessment, and face scan functionality using artificial intelligence for automated skin analysis. Environmental data retrieval encompasses humidity, temperature, UV index, pollution levels, and wind conditions for the specified target date and location. The quantization process transforms both user inputs and environmental data into categorical features through systematic mapping to low, medium, and high classifications. Safety filters implement ingredient allergies and preferences screening along with sensitivity gates and avoid lists. The decision engine operates using rules, machine learning, or hybrid approaches to generate same-day skin, scalp and hair outputs comprising ingredient guidance for cleansers, moisturizers, night treatments, and sunscreen, along with comprehensive do's and don'ts and optional supplement recommendations.

[0147] Phase 2 extends the system to encompass hair and scalp care through a unified algorithm that processes the same target date and location data. User inputs include scalp type classification such as oily, dry, sensitive, or balanced, hair type and texture characteristics including straight, wavy, curly or coily and fine, medium, or thick classifications respectively, and primary concerns such as hairfall, dandruff, breakage, frizz, greys, volume, scalp acne, slow growth. The system incorporates optional photo cues for texture and volume assessment along with lifestyle toggles for heat styling frequency, chemical treatments, and environmental exposure patterns. Environmental data integration utilizes the same comprehensive parameters as Phase 1, recognizing that environmental conditions impact both skin, scalp and hair simultaneously. The quantization process maps hair-specific inputs including scalp type, hair type, hair texture and environmental factors into categorical bins. The decision engine applies specialized logic for hair-specific concerns such as hairfall, dandruff, breakage, frizz, greys, volume, scalp acne, slow growth, generating same-day hair and scalp outputs with ingredient guidance for shampoos, scalp treatments, leave-in products, and masks.

[0148] Phase 3 introduces sensor-integrated refinement through disposable diagnostic elements embedded in secondary packaging. The system processes base inputs from Phases 1-2 while incorporating pack-embedded disposable indicators that measure sebum levels, hydration levels, pH levels, flake presence, and UV exposure through simple 1-2 step processes involving dab, press, or peel actions. Token capture and validation involves manual code entry or micro-QR scanning with checksum and lot provenance verification to ensure data integrity. The mapping process transforms sensor outputs into low, medium, and high classifications that refine existing inputs for skin, scalp and hair type, condition, and environmental exposure status. Environmental data merging combines the refined sensor-based inputs with comprehensive environmental conditions. The decision engine reweights selections using indicator bins to improve texture and film selection while maintaining active intensity optimization, generating refined same-day outputs for skin, scalp and hair care with enhanced accuracy through objective biological measurements.

[0149] Phase 4 implements accuracy expansion through additional category-level inputs and optional secondary sensor indicators. Core inputs from previous phases are supplemented with Phase 4 category inputs including temporal and event context such as life events and special occasions, medical context for cosmetic use including procedural history and preferences, and constraints for product selection filtering. Optional indicators provide advanced sensor capabilities including narrow-range pH measurements, hard-water detection strips, optical glare index assessments, and other single-use diagnostic codes. Environmental data retrieval incorporates extensions such as dew point measurements, diurnal temperature range analysis, pollutant mix composition, indoor climate and humidity flags, and water hardness indices. Enhanced validation and privacy measures include comprehensive token checksum and lot metadata verification while maintaining privacy through no raw image requirements and sanity checks on input ranges. The quantization process maps expanded inputs to configurable or learned thresholds enabling more nuanced differentiation. Safety filters implement medical contraindications screening, buffer actives management, fragrance sensitivity and allergy filters, and regional availability and budget filters. The decision engine processes the expanded input set using Phase-4 categories for texture and film strength selection optimization, active intensity calibration, and deterministic processing for identical feature bins, generating comprehensive same-day outputs with maximum personalization accuracy.

[0150] Environmental data processing utilizes standardized classification systems to ensure consistent recommendation generation across different geographical locations and seasonal conditions. Humidity levels are classified as low (<40%), moderate (40-60%), high (60-75%), and very high (>75%) relative humidity. Temperature classifications encompass low / cold (<10°C), mild (10-20°C), warm (20-28°C), hot (29-35°C), and very hot (>35°C) ambient daily mean temperatures. UV index categorization includes low (0-2), moderate (3-5), high (6-7), very high (8-10), and extreme (>11) classifications. Pollution levels utilize either PM2.5 measurements or Air Quality Index (AQI) values with low (AQI 0-50, PM2.5 <12 pg / m3), moderate (AQI 51-100, PM2.5 12-35 pg / m3), high (AQI 101-200, PM2.5 35-55 pg / m3), and very high (AQI >200, PM2.5 >55 pg / m3) classifications. Wind conditions are categorized as calm or strong based on local meteorological standards and their impact on skin exposure. The system implements sophisticated ingredient mapping logic that correlates environmental conditions with specific skincare and haircare and haircare ingredients based on dermatological and trichology research and efficacy data. For high temperature conditions, the system recommends cooling and antiinflammatory ingredients including cucumber extract for its cooling and soothing properties, green tea extract rich in antioxidants for environmental protection, and niacinamide for anti-inflammatory and skin barrier- strengthening capabilities. Low temperature conditions trigger recommendations for moisture -retaining ingredients such as honey as a natural humectant for deep hydration, shea butter for intense nourishment and protection, hyaluronic acid for powerful moisture attraction and retention, glycerin for moisture drawing and barrier formation, and various emollients including cocoa butter, lanolin, jojoba oil, aloe vera, coconut oil, and beeswax for protective barrier formation and moisture retention.

[0151] Humidity- specific ingredient mapping addresses the varying moisture levels in environmental conditions. High humidity environments benefit from lightweight hydration ingredients such as aloe vera for soothing properties without greasiness and niacinamide for sebum regulation and barrier strengthening. Low humidity conditions require intensive moisture -binding ingredients including hyaluronic acid for deep hydration and ceramides for barrier restoration and moisture retention. Pollution- specific recommendations emphasize protective and antioxidant ingredients, with high pollution environments requiring antioxidants such as vitamin E and vitamin C for free radical protection and niacinamide for barrier strengthening against environmental stressors. Wind condition mapping addresses mechanical stress on skin with strong wind conditions requiring barrier- supporting ingredients such as ceramides for skin barrier restoration and squalane for lightweight intense hydration, supplemented by panthenol for barrier strengthening, oat extract for soothing protection, and various protective oils and extracts.

[0152] The system maintains comprehensive ingredient matrices that correlate specific skin, scalp and hair conditions with appropriate active ingredients across different skin, scalp and hair types. For facial cleansing applications, redness conditions are addressed with hyaluronic acid for combination skin, panthenol / vitamin B5 for dry skin, green tea for normal skin, BHA / B3 for oily skin, and aloe vera / hyaluronic acid with glycerin for sensitive skin. Acne conditions utilize salicylic acid for combination, normal, and oily skin types, cetyl alcohol for dry skin, and aloe vera / chamomile for sensitive skin. Wrinkle concerns are universally addressed with hyaluronic acid across all skin types, while uneven skin tone benefits from microdermabrasion / exfoliating approaches, dullness from glycolic acid, and dark spots from brightening cleansers with kojic acid.

[0153] Moisturizer formulations follow specific ingredient protocols based on skin, condition and type combinations. Dark spot treatment utilizes niacinamide with vitamin C for combination, normal, and oily skin, niacinamide with licorice for dry skin, and niacinamide alone for sensitive skin. Acne management employs salicylic acid for combination and oily skin, salicylic acid with hyaluronic acid for dry skin, tea tree oil for normal skin, and salicylic acid for sensitive skin. Dullness correction combines hyaluronic acid with vitamin C for combination skin, vitamin E with vitamin A for dry skin, vitamin C with hyaluronic acid for normal skin, vitamin C alone for oily skin, and vitamin C for sensitive skin. Redness reduction utilizes aloe vera with green tea for combination and sensitive skin, aloe vera with chamomile for dry skin, calendula with chamomile for normal skin, and green tea for oily skin.

[0154] Hair and scalp care ingredient selection follows environmental adaptation principles that address the unique challenges of hair fiber and scalp skin. High temperature conditions require gentle sebum control through low-SLS or sulfate- free bases with chelators such as EDTA for salt and sweat removal, optional salicylic acid up to 2% for oily scalp conditions, piroctone olamine or zinc pyrithione for flakes and itch, niacinamide with panthenol for barrier support, heat and UV shields including silicone quaterniums and amodimethicone, and lightweight amino acids with ceramides for moisture without heaviness. Low temperature conditions emphasize moisture retention through mild surfactants, panthenol and aloe with allantoin for comfort, pH-balanced toners at 5.0-5.5 for barrier support, squalane and argan with ceramides for slip, anti-static polymers, and rich conditioning agents including shea and cocoa butter for coarse hair and ceramides with hydrolyzed proteins for damaged hair.

[0155] Humidity- specific hair care addresses the hygroscopic nature of hair fibers and their response to atmospheric moisture. High humidity conditions require anti-humidity film formation through amodimethicone, dimethicone, and polyquatemium compounds, moderate glycerin levels to prevent excessive swelling, light clarifying protocols to reset product buildup, and piroctone olamine with low salicylic acid for oily scalp with flakes. Low humidity conditions necessitate humectant and occlusive pairing such as glycerin or hyaluronic acid with squalane or esters, panthenol with niacinamide for scalp comfort, gentle conditioning surfactants with polyquaterniums, and rich conditioning treatments with ceramides, butters, and oils for coarse hair, plus bond builders for chemically treated hair.

[0156] Pollution require specialized protective approaches for hair and scalp health. High pollution environments demand chelators such as EDTA and citric acid, antipollution clarifying protocols 1-2 times weekly without stripping, antioxidants including EGCG and vitamin E with niacinamide for scalp protection, and antipollution polymer films with UV shields for leave-in protection. Strong wind conditions require mechanical protection through slip and film-forming ingredients including silicones and quatemiums, UV and heat shields, protective styling recommendations, and ceramides with proteins for cuticle reinforcement. The system adjusts these recommendations based on hair porosity, chemical treatment history, and styling frequency to optimize protection and performance.

[0157] Sensor integration logic transforms objective biological measurements into actionable refinements of existing user inputs through validated tokenization systems. Sebum level measurements ranging from 0-3 scale refine skin type classifications and influence cleanser strength selection, moisturizer texture recommendations, and SPF formulation preferences. Hydration level assessments categorized as low, medium, or high adjust barrier repair ingredient emphasis, humectant concentration recommendations, and occlusive layer requirements. Surface pH measurements classified as acidic, optimal, or elevated trigger barriersupporting active selection, buffering protocol adjustments, and fragrance sensitivity routing. Flake presence indicators for scalp conditions activate antifungal ingredient pathways, soothing protocol emphasis, and low-fragrance formulation preferences. UV exposure measurements influence antioxidant coactive selection, high-SPF routing decisions, and color-fade protection protocols for hair care.

[0158] Phase 4 context variables provide granular personalization enhancement through systematic categorization of lifestyle, medical, and environmental factors. Temporal and event context including weddings, festivals, and photoshoots triggers finish priority adjustments between matte and dewy preferences, pre-event caution flags to avoid strong exfoliants, and anti-flashback filtering for photography optimization. Life-event context such as pregnancy, lactation, perimenopause, travel, and occupational exposures activates gentler active ingredient lists, soothing bias protocols, and film strength adjustments for comfort and safety. Medical context for cosmetic personalization incorporates oncology therapy history, PCOS, thyroid conditions, and dermatitis tendencies to implement safety filters, buffer retinoid and AHA protocols, and activate hair-fall support ingredients. Cosmetic and procedural history including peels, lasers, chemical treatments, and styling damage triggers barrier rebuilding emphasis, bond builder recommendations, and protein versus emollient balance optimization.

[0159] Environmental and infrastructure extensions in Phase 4 provide enhanced precision through additional meteorological and contextual parameters. Dew point measurements enable frizz behavior prediction and texture selection optimization, with high dew point conditions triggering lighter textures and anti-tack finishes for skin care and stronger anti-humidity films with moderated glycerin for hair care. Diurnal temperature range analysis addresses barrier stress from temperature fluctuations, implementing buffered retinoid and AHA protocols with barrier support for large temperature swings and increased emollients with anti-static aids for hair care. Pollutant composition analysis distinguishing PM particulates from ozone exposure enables targeted antioxidant selection and anti-pollution film emphasis. Water hardness indices activate chelating cleanser and shampoo recommendations with clarifying guidance protocols. Indoor climate flags for heating and air conditioning systems adjust occlusive step requirements and antistatic formulation needs based on artificial climate exposure.

[0160] The decision engine architecture implements a hybrid approach combining rulebased logic, machine learning algorithms, and deterministic processing to ensure consistent, reproducible recommendations while enabling continuous optimization. Rule-based components handle safety filters, ingredient contraindications, and basic environmental correlations through expert-derived logic trees. Machine learning components process complex multi-variable interactions, user feedback integration, and pattern recognition for recommendation refinement. Deterministic processing ensures that identical categorical inputs produce identical outputs, maintaining system reliability and user trust while enabling recalibration through threshold adjustments. The engine processes all input categories through standardized binning systems, applies weighted scoring algorithms, and generates ranked recommendations with confidence intervals and alternative suggestions.

[0161] Without further description, it is believed that one of ordinary skill in the art can, using the preceding description and the illustrative examples, make and utilize the present invention and practice the claimed methods. It should be understood that the foregoing discussion and examples merely present a detailed description of certain preferred embodiments. It will be apparent to those of ordinary skill in the art that various modifications and equivalents can be made without departing from the spirit and scope of the invention.

Claims

Claims:I Claim:

1. A method for providing personalized skincare recommendations, the method comprising: a. receiving user input comprising personal skin, scalp and hair characteristics and a geographical location through a user interface; b. retrieving real-time environmental conditions for the geographical location from an external data source; c. processing the user input and the real-time environmental conditions using a recommendation engine to generate personalized skincare and haircare recommendations; d. wherein the recommendation engine maps the personal skin, scalp and hair characteristics and the real-time environmental conditions to a dermatological and trichology knowledge base comprising skincare and haircare ingredients and skincare and haircare products; and e. providing customized product suggestions based on the user's skin, scalp and hair type, skin, scalp and hair condition, and the real-time environmental conditions; f. wherein the method further comprises receiving a target date for the personalized skincare and haircare recommendations, and the realtime environmental conditions are retrieved for the geographical location on the target date; g. wherein the method further comprises receiving diagnostic data from a disposable sensor element embedded in product packaging, the sensor element configured to produce a coded categorical output for at least one parameter selected from sebum level, hydration level, pH level, flake presence, redness level, and UV exposure level, and refining the personalized skincare and haircare recommendations based on the diagnostic data.

2. The method for providing personalized skincare and haircare recommendations as claimed in claim 1, wherein the personal skin, scalp and hair characteristics comprise skin type selected from the group consisting of normal, oily, dry, combination, and sensitive; scalp type selected from the group consisting of oily, dry, sensitive, or balanced and hair type selected from the group consisting of straight, wavy, curly or coily.

3. The method for providing personalized skincare recommendations as claimed in claim 1, wherein the personal skin, scalp and hair characteristics comprise skin condition selected from the group consisting of acne, redness, dullness, wrinkles, dark spots, and uneven skin, tone; scalp and hair condition selected from the group consisting of hairfall, dandruff, breakage, frizz, greys, volume, scalp acne or slow growth.

4. The method for providing personalized skincare recommendations as claimed in claim 1, wherein the skin, scalp and hair condition is entered by the user through at least one of typing, photo upload, or face scanning.

5. The method for providing personalized skincare recommendations as claimed in claim 1, wherein the real-time environmental conditions comprise humidity, temperature, UV index, pollution level, and wind conditions.

6. The method for providing personalized skincare recommendations as claimed in claim 1, wherein the recommendation engine comprises an algorithm that processes the user input and the real-time environmental conditions to provide the personalized skincare and haircare recommendations .

7. The method for providing personalized skincare recommendations as claimed in claim 1, wherein the personalized skincare and haircare recommendations comprise beneficial ingredients and ingredients to avoid for the user.

8. The method for providing personalized skincare recommendations as claimed in claim 1, wherein the personalized skincare and haircare recommendations further comprise information on oral supplements to mitigate skin, scalp and hair conditions.

9. A system for providing personalized skincare recommendations, the system comprising: a. a user interface configured to receive user input comprising personal skin, scalp and hair characteristics and a geographical location; b. a data retrieval engine configured to retrieve real-time environmental conditions for the geographical location from an external data source for a given date; c. a recommendation engine configured to process the user input and the real-time environmental conditions to generate personalized skincare and haircare recommendations; d. wherein the recommendation engine is configured to map the personal skin, scalp and hair characteristics and the real-time environmental conditions to a dermatological and trichology knowledge base comprising skincare and haircare ingredients and skincare and haircare products; e. wherein the system is configured to provide customized product suggestions based on the user's skin, scalp and hair type, skin, scalp and hair condition, and the real-time environmental conditions; and f. a sensor interface configured to receive diagnostic data from a disposable sensor element embedded in product packaging, the sensor element configured to produce a coded categorical output forat least one parameter selected from sebum level, hydration level, pH level, flake presence, redness level, and UV exposure level, and refine the personalized skincare and haircare recommendations based on the diagnostic data.

10. The system for providing personalized skincare recommendations as claimed in claim 9, wherein the personal skin, scalp and hair characteristics comprise skin, scalp and hair type selected from the group consisting of normal, oily, dry, combination, and sensitive, and skin, scalp and hair condition selected from the group consisting of acne, redness, dullness, wrinkles, dark spots, and uneven skin, scalp and hair tone; said scalp type selected from the group consisting of oily, dry, sensitive, or balanced; hair type selected from the group consisting of straight, wavy, curly or coily and scalp and hair condition selected from the group consisting of Hair fall, dandruff, breakage, frizz, greys, volume, scalp acne, slow growth.

11. The system for providing personalized skincare recommendations as claimed in claim 9, wherein the user interface is configured to receive the skin, scalp and hair condition through typing and at least one of, photo upload, or face scanning.

12. The system for providing personalized skincare recommendations as claimed in claim 9, wherein the real-time environmental conditions comprise humidity, temperature, UV index, pollution level, and wind conditions.

13. The system for providing personalized skincare recommendations as claimed in claim 9, wherein the external data source is an open weather application programming interface (API).

14. The system for providing personalized skincare recommendations as claimed in claim 9, further comprising a database configured to store the dermatological and trichology knowledge base.

15. The system for providing personalized skincare recommendations as claimed in claim 9, wherein the recommendation engine comprises an algorithm configured to process the user input and the real-time environmental conditions to provide the personalized skincare and haircare recommendations .

16. The system for providing personalized skincare recommendations as claimed in claim 9, wherein the personalized skincare and haircare recommendations further comprise at least one of oral supplement recommendations, sleep habit advice, dietary suggestions, lifestyle and behavior changes, and skincare and haircare routine modifications.

17. The system for providing personalized skincare recommendations as claimed in claim 9, further comprising a sensor interface configured to receive diagnostic data from a disposable sensor element embedded in product packaging.

18. The system for providing personalized skincare recommendations as claimed in claim 9, wherein the sensor interface is configured to validate tokenized diagnostic codes and map them to categorical parameters for refining the personalized skincare and haircare recommendations.

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