Hygiene Monitoring and Intervention System Based on Environmental Parameters in Vacuum Textile Storage Environments
Patent Information
- Application Number
- TR202605052
- Authority / Receiving Office
- TR · TR
- Patent Type
- Applications
- Current Assignee / Owner
- Filing Date
- 2026-04-04
- Publication Date
- 2026-09-21
Abstract
Description
Hygiene Based on Environmental Parameters in Vacuum Textile Storage Environments Monitoring and Intervention System 1. Technical Area This invention enables the storage of textile products in closed and vacuum environments. Monitoring environmental parameters such as humidity, temperature, pressure, etc., that may occur, by evaluating and determining the hygiene status based on this data. It relates to a system for enabling automated intervention when necessary. The invention is particularly relevant to smart storage systems, IoT-based home solutions, and textile protection. It falls into the field of technologies. 2. State of the Art The vacuum storage systems currently in use are only physical. By providing air release, it reduces the volume of textile products and It partially isolates from the external environment. However, these systems: cannot measure indoor humidity, and cannot measure temperature changes. Unable to monitor, analyze vacuum loss, odor and microbial risks. It is unable to evaluate the data and provides no feedback to the user. In addition, current solutions result from textile products remaining sealed for extended periods. any active or passive measures against potential mold, odor and hygiene problems It does not include. Therefore, in the current technical situation, the processes that occur during the storage of textile products... Risks cannot be identified in advance, monitored, or managed through user intervention. It is delayed. 1.3. Purpose of the Invention The purpose of this invention is to analyze environmental data in vacuum or sealed textile storage environments. monitoring this data continuously or periodically, using specific rules, models and / or By analyzing the hygiene status according to calculation methods, It provides warnings and information to the user, automatically or semi-automatically when necessary. The goal is to develop a system that performs automated interventions. The invention also aims to: Increase the safe storage time of textile products, and reduce odor and mold. to prevent or reduce its formation, Use of stored textile products Its purpose is to determine its suitability and inform the user. 4. Summary of the Invention The invention involves sensors placed inside a vacuum or sealed textile storage unit. a device that measures ambient humidity, temperature, and pressure data and transmits this data to a control unit. It determines the hygiene status by processing it through this mechanism and provides ventilation and warnings when necessary. It is a system that triggers disinfection processes. The system also provides data transfer to the user via a mobile application. It generates warnings regarding storage conditions and provides information about the system status. It offers. 2.5. Detailed Description of the Invention 5.1 General System Structure The invention consists of the following main components: A vacuum or sealed textile storage unit. Sensor module, Control unit (microcontroller), Active intervention components, Communication. module, User Interface (mobile application) These components work together to monitor, evaluate, and conduct indoor environments. It enables management. The system has a modular structure and can accommodate different sensor combinations and intervention mechanisms. and is designed to be expandable with software infrastructures. 5.2 Storage Unit Storage unit; Vacuum-sealable, airtight or controlled airtight. A permeable, sack, bag, or similar enclosed container in which textile products are placed. It consists of structures. 5.3 Sensor Module The sensor module includes the following components: Humidity sensor, Temperature sensor, Pressure sensor. Sensor, Optional: Gas / VOC sensor, Light sensor Sensors continuously or periodically monitor environmental conditions within the storage unit. It measures within these ranges and transmits this data to the control unit. 5.4 Control Unit The control unit processes data received from sensors, using predefined rules and thresholds. The system behavior is evaluated based on values or calculation methods. It consists of a microcontroller or equivalent processing unit that controls it. 3 5.5 Hygiene Assessment Mechanism The system converts raw data from sensors into a meaningful hygiene score and intervention criteria. It uses the following analytical methods to convert it into a signal: described below methods refer to example applications of how the system works, and the invention It is not limited to these methods. Dynamic Threshold Value Analysis: Control unit, ambient temperature (T) and relative humidity (H) It constantly monitors these values. The Dew Point is critical for textile products. By performing these calculations, it monitors the risk of concentration in real time. If the relative humidity exceeds the limits set depending on the storage time (e.g., 60% relative humidity) If the humidity level exceeds a certain threshold, a potential risk is identified. Vacuum Loss Rate Algorithm: Data from the pressure sensor, on the time axis It is subjected to regression analysis. Sudden increases in pressure are rapid leaks, while leaks occur over time. Micro-increases are classified as Material Fatigue or Valve Deformation. The system provides a residual value indicating how long it will take for hygiene to deteriorate based on the leakage rate. It estimates the safe storage period. Fuzzy Logic and Decision Matrix: Hygiene status is determined by only one factor. not the parameter; temperature, humidity, storage time and textile type (wool, cotton, synthetic) (etc.) is determined according to a multivariate decision matrix it creates. For example; low High humidity at high temperatures poses less risk, while moderate humidity at high temperatures... It is coded as High Hygiene Risk. Artificial Intelligence and Machine Learning Integration: The system analyzes historical data. It has a learning mechanism. The user should turn the product on and off at regular intervals. or approval of the intervention mechanism, feedback for the Learning Algorithm. (labeling) is created. In this way, the system adapts to the season or geographical location (humid / dry). It offers an adaptive structure that optimizes its own threshold values according to the region. Anomaly Detection: Sudden deviations in data from gas / VOC sensors, micro- as a harbinger of organism activity or chemical decomposition (odor formation) This is accepted. The system considers any deviation outside the baseline as an anomaly. By marking it, it triggers the intervention unit (UV-C or Ventilation). 4. The system analyzes the environmental data in question using rule-based, statistical, and mathematical methods. using modeling methods and / or machine learning and artificial intelligence techniques It can analyze. In this context, data processing is based on predefined threshold values. This can be done based on, or adaptively, learning from past datasets. This can also be done through models. These analysis methods can be applied individually or in combination, and may involve different calculations and... This can also be done through evaluation techniques. The hygiene status, risk level, and suitability for use outputs generated by the system, used as a control signal to directly or indirectly affect system components. It can enable management. 5.6 Intervention Mechanism The system depends on the hygiene status and risk factors determined by the control unit. It performs the following active and passive intervention procedures: Active Air Circulation and Moisture Extraction: Integrated onto the storage unit, via a micro-valve connected to the outside environment and a low-power suction / discharge fan The humid air in the environment is removed. During this process, the vacuum level must be maintained or To maintain atmospheric balance in a controlled manner, the air intake is highly efficient. They are sterilized by passing them through particle filters (HEPA or activated carbon). Photolytic Disinfection (UV-C): In cases where humidity or odor thresholds are exceeded, Flexible UV-C LEDs are placed on the inner surfaces of the control unit storage unit. It activates the strips. Ultraviolet light of a specific wavelength (preferably 254-280 nm), by disrupting the DNA / RNA structure of bacteria, mold, and fungal spores on the textile surface It stops microbial growth. Ozone or Ionization Intervention: Data from odor (VOC) sensors If the ppm value exceeds a certain level, the system activates an internal micro-ozone generator. or it neutralizes unpleasant odors in the environment by triggering the ionizer module. Dynamic Vacuum Restoration: Pressure data (P) from the sensor module, vacuum If it indicates a leak, the system should be connected to an external vacuum pump. or by sending a signal to a miniature pump unit integrated into the system to create vacuum It automatically resets the level to its initial value. Hierarchical Alert System: When critical threshold values are exceeded, the system automatically activates. If the situation cannot be stabilized through intervention; via the mobile application The user receives a message such as "High Risk," "Emergency Ventilation Required," or "Check Products." Gradual notifications and audible alerts are transmitted. These intervention mechanisms can operate individually or in combination. It is configurable and can be used with equivalent technical solutions in different applications. realizable. 6 5.7 Communication and User Interface The mobile application, which works integrated with the system, is not just a viewing tool; it processes data. It is an interactive management layer that operates and feeds user decisions back into the system. Product Identification and Tracking: The user places the product in the vacuum storage unit. The application identifies the type of textile (quilt, wool sweater, summer clothing, etc.). The algorithm determines the Critical Humidity and Maximum Storage Time according to the selected textile type. It updates its parameters automatically. Predictive Maintenance: The application uses historical data from sensors. It creates a Hygiene Projection using the data. For example; the current rate of increase in humidity. If it continues, a visual graph (temperature) will show the user that there is a risk of mold developing within 15 days. (map) reports. Intervention Approval Mechanism: In critical situations, the system can perform UV-C disinfection or It may request user approval before starting the ventilation cycle, or this The system manages the process automatically via "Automatic Protection Mode" and provides a report to the user. Cloud-Based Benchmarking: The application benchmarks similar climates based on anonymized data. other storage units under similar conditions (e.g., high humidity in Istanbul) By comparing performance data, the user is provided with storage based on their location. It offers smart suggestions such as "your time has been optimized". 5.8 Working Principle The system works as follows: Sensors measure environmental data, the measured data is checked. The data is transmitted to the control unit, the control unit analyzes the data, the hygiene status is determined, and the determined data is presented. Depending on the situation, intervention is carried out or a suggestion is made, and the user is informed. 7 5.9 Energy Management and Power Unit Energy management is used to enable the system to monitor and respond to incidents without interruption. Its mechanism has the following characteristics: Hybrid Power Supply Structure: The system includes an internal lithium-polymer (Li-Po) battery, can be powered by a supercapacitor or an external USB Type-C input It is structured. The battery unit is subject to physical deformation under vacuum pressure. a hardened and sealed enclosure (case) that will not be damaged It is included within. Low Power Consumption (Deep Sleep) Mode: Instead of continuously reading data, the control unit... It operates in "event-based" or "periodic wake-up" mode. Sensors only activate when specified. It activates at specific time intervals (e.g., every hour) to collect data, then the system... It enters a deep sleep mode that consumes minimum energy. Energy Harvesting Option: Integrated into the storage unit surface. energy from flexible and thin-film solar panels or from airflow in a vacuum valve. through micro-turbines that produce, from ambient light or during air extraction Battery charging is achieved using kinetic energy. Intelligent Battery Management System (BMS): The control unit continuously monitors the battery level. When the energy level falls below the critical threshold, intervention mechanisms (UV-C or By restricting the fan, it switches to data monitoring mode only and can be accessed via the mobile application. It sends a "Low Battery" warning to the user. Wireless Charging Integration: To avoid compromising the airtightness of the vacuum bag. In other words, power is transmitted via inductive (wireless) charging through the surface of the bag. This can be achieved. This eliminates the need for a physical connector. The sealing life is extended. 8 5.10 Sensor Sensitivity, Calibration and Data Stability To prevent the system from generating false alarms and to provide protection according to industrial standards. To ensure this, the sensor module has the following technical specifications: Differential Pressure Measurement: The pressure sensor operates with an accuracy of 1 hPa. It can detect micro-leaks (pinhole leaks) before hygiene is compromised. Sudden pressure fluctuations (for example, temporary changes caused by a load being placed on it) It uses digital filtering (such as a Kalman filter) that distinguishes it from a real leak. Temperature-Compensated Humidity Measurement: Humidity sensors compensate for temperature changes. Because it is affected, the system corrects the relative humidity while using simultaneous temperature data. This allows for a 2% error rate across all storage conditions between -10°C and +50°C. Sensitivity below the required level is achieved. Auto-Zeroing: The system resets at the beginning of each vacuuming process. It defines the atmospheric pressure in the environment as a "reference point". This is above sea level. It ensures the system functions correctly in every geographical location, even at high altitudes. Gas Sensor Selectivity: The VOC / odor sensor used; the natural properties of textile products. able to distinguish between the smell of microbial activity and gases produced as a result of microbial activity (mold odor, etc.). It is calibrated to have spectral sensitivity. These calibration and verification mechanisms are used for different sensor types and measurement technologies. It can also be done in an equivalent way. 6. Industrial Applicability The invention applies to home textile storage systems and smart cabinet and storage solutions. In hotel, hospital and textile storage areas, and in e-commerce and logistics warehouse systems. It is easily applicable. 9 7. Conclusion This invention transforms the storage process of textile products from a passive preservation method, a system that actively monitors, evaluates, and manages, supported by environmental data It offers. In this way, the hygiene status of textile products is constantly monitored, and risks are minimized. This is detected in advance and provides the user with a safe usage experience.
Claims
1. A vacuum or sealed textile storage unit, at least one sensor module and a control unit. It is a system that includes a unit, and its feature is the humidity obtained from the sensor module in question. temperature, pressure, gas composition and / or time-dependent data, singular or multiple in the form of parameters, rule-based, statistical, mathematical modeling and / or by evaluating using machine learning and artificial intelligence techniques hygiene status, risk level and / or suitability for use of the storage environment the generation of the output, the use of this output as a control signal, and the operation of this output. depending on the system behavior, it can be directed automatically or semi-automatically. A textile storage system characterized by its features.
2. It is a system according to Claim 1, the characteristic of which is that the hygiene situation in question factors such as retention period, last access time and / or frequency of use are determined characterized by the inclusion of time-dependent parameters in the evaluation. system.
3. According to claim 1, it is a system whose characteristic is the hygienic condition; humidity, temperature, pressure, gas a multi-faceted approach where concentration, textile type, and time parameters are evaluated together a multivariate decision model, decision matrix, multivariate data fusion approach and / or A system characterized by its determination using a fuzzy logic approach.
4. It is a system according to Claim 1, the characteristic of which is the evaluation of the data in question. Rule-based, statistical, mathematical modeling, regression analysis, anomaly detection. and / or equivalent data processing methods and / or machine learning, artificial intelligence, by using adaptive algorithms and / or systems that learn from historical datasets a system characterized by its implementation.
5. According to claim 4, it is a system whose characteristic is machine learning, artificial intelligence, through adaptive algorithms and / or systems that learn from past datasets, hygiene assessment criteria, threshold values, risk parameters and / or Intervention timing depends on user behavior, retention history, and seasonal conditions. and / or characterized by its dynamic adaptation depending on geographical conditions. The system that was created. 12 6. It is a system according to claim 1, and its characteristic is the analysis of pressure data on the time axis. by determining the vacuum loss rate, leakage characteristics and / or integrity of the storage medium. A system characterized by making a situational assessment regarding a particular issue.
7. A system according to Claim 1, whose characteristic is derived from gas and / or VOC sensors. Deviations in the data are considered anomalies, and these deviations are attributed to odor. formation, used as an indicator of microbial activity and / or chemical degradation a system characterized by.
8. According to Claim 1, it is a system with the following characteristics: defined hygiene status, risk level. and / or automatic or semi-automatic depending on the output produced by the system. Ventilation, moisture removal, triggered, controlled and / or managed in this manner, at least one that provides disinfection, gas neutralization and / or vacuum restoration A system characterized by the activation of an intervention mechanism.
9. It is a system according to claim 8, the characteristic of which is that the disinfection process is carried out with ultraviolet light, by using ionization, ozone production and / or equivalent microbial reduction methods a system characterized by its implementation.
10. It is a system according to claim 8, whose characteristic is the detection of pressure changes. the vacuum level is achieved through a pump system and / or an external vacuum source A system characterized by its automatic regeneration.
11. According to claim 1, it is a system whose characteristic is the wireless communication module of the system. exchanging data with a user interface, providing warnings to the user, providing recommendations and / or usage suitability information and / or user decisions, Characterized by providing feedback of approvals or preferences to the control unit. system.
12. According to Claim 1, it is a system whose characteristic is based on historical and / or current sensor data. based on future hygiene risks, safe storage period and / or Anticipating the need for intervention and providing the user with a preventive warning accordingly. A system characterized by the submission of a proposal and / or intervention plan.
13. It is a system according to Claim 1, the characteristic of which depends on the type of textile product being stored. as hygiene assessment criteria, threshold values and / or risk A system characterized by the dynamic adaptation of its parameters.
14. It is a system according to Claim 1, and its characteristics include a sensor module, intervention components and The control unit has a modular structure and can be expanded in different combinations. A system characterized by its structure.
15. According to claim 1, it is a system whose characteristic is that the system operates with low power consumption. modes, periodic wake-up and / or event-based operation logic, energy management algorithms that will work with battery management systems and / or alternative energy sources. A system characterized by its structure in this way.
16. It is a system according to Claim 1, and its characteristic is what is produced by that system. Hygiene score of the output, risk level, suitability for use and / or intervention recommendation. Characterized by being created as a numerical and / or classified value. the system that was used.
17. According to Claim 1, it is a system whose characteristics include different sensor types and data processing. in a platform structure that can work with methods and intervention mechanisms A system characterized by its design. 14