Sleep ecosystem and control method thereof

Abstract

The invention discloses a sleep ecosystem and a control method thereof. Comprising a bed body, a cloud computing system, a remote control end, environment detection equipment and an environment control module, a micro sensing module of the bed body collects human body sleep parameters and transmits the human body sleep parameters to the cloud computing system, and the remote control end is used for guests to input sleep and environment parameters. A sleep function calculation module of the cloud computing system processes and analyzes various data, a sleep parameter analysis sub-module of the cloud computing system can construct a personalized sleep parameter model, a sleep mode generation sub-module optimizes environmental parameters, and a sleep effect evaluation sub-module evaluates and adjusts in real time. And the music control module and the aromatherapy control module can be used for receiving instructions of the cloud computing system or preference information of guests for operation. And the micro-sensing modules are of various types and are transversely and uniformly distributed on the bed body. The system can provide personalized sleep experience for guests, comprehensively regulate and control the sleep environment, realize intelligent data processing and efficient utilization, and effectively optimize the sleep quality.

Description

Technical Field

[0001] The present invention relates to the technical field of sleep systems, and in particular to a sleep ecosystem and a control method thereof. Background Art

[0002] In today's hotel service industry, hotel room accommodation still focuses on providing guests with basic bedding functions. The traditional hotel accommodation model has long formed a pattern, that is, bedding only meets the most basic needs of sleep support and warmth, and lacks innovation and personalized considerations from the softness and hardness of the mattress to the material and design of the bedding.

[0003] However, with the rapid development of the times, consumers' consumption concepts have undergone profound changes. Among them, the demand for sustainable consumption is showing a strong and growing trend. Today's consumers are no longer just concerned about the experience brought by products or services at the moment, they pay more attention to the impact of these products or services on the environment, society and long-term development. In the field of hotel accommodation, this change in concept means that consumers expect hotels to actively fulfill their social responsibilities while providing a comfortable sleeping environment, and adopt environmentally friendly and sustainable business methods and product supply.

[0004] At the same time, the advancement of science and technology, especially the booming development of artificial intelligence technology, has brought unprecedented opportunities to the hotel industry. In the B2B (for the hotel industry) field, hotel suppliers and partners are seeking innovative solutions to enhance the competitiveness and operational efficiency of hotels; in the B2C (for households) field, consumers' requirements for accommodation experience are also increasing, and they are eager to enjoy unique and personalized services that meet their needs in hotels.

[0005] In this context, the hotel industry is facing tremendous pressure for change and innovation challenges. There is an urgent need to build a personalized sleep system based on ESG (environment, society and corporate governance) and artificial intelligence technology. This system will not only be a simple upgrade of traditional bedding, but also integrate the application of environmentally friendly materials, the consideration of social value, and the analysis of sleep data by intelligent technology and the customization of personalized sleep patterns. Through such a system, hotels are expected to meet the market demand in the B2B and B2C fields and enhance their competitiveness and sustainable development capabilities in the market. Summary of the invention

[0006] In order to solve the problems existing in the prior art, the present invention provides a sleep ecosystem and a control method thereof, which can be personalized and customized and a variety of sleep-related modules work together to achieve a dynamically adjusted sleep ecosystem, an integrated sleep program tailored for users, and promote a full night of sleep.

[0007] The technical solution of the present invention is a sleep ecosystem, comprising a bed, a cloud computing system, and a remote control terminal connected to the cloud computing system, an environmental detection device for collecting indoor environmental data, and an indoor environmental device, wherein the bed is provided with a micro-sensor module for collecting human sleep parameters, the micro-sensor module is connected to the cloud computing system and transmits the collected parameters; the remote control terminal comprises a display screen, an operation button and a processor, the remote control terminal is used to receive sleep parameters and environmental parameters input by a guest before going to bed, and transmit the parameters to the cloud computing system; the cloud computing system comprises a server, a data storage unit and a sleep function calculation module, the server is used to run an algorithm to process the received data, the data storage unit is used to store data, the sleep function calculation module analyzes and processes the received sleep parameters, environmental parameters, human sleep parameters transmitted by the micro-sensor module, and indoor environmental data transmitted by the environmental detection device to obtain an evaluation result, and the cloud computing system issues a control instruction to the indoor environmental device according to the evaluation result to dynamically adjust the sleep mode to optimize the guest's sleep experience.

[0008] Preferably, the sleep function calculation module is provided with a sleep parameter analysis submodule, and the sleep parameter analysis submodule includes a data preprocessing unit, a preference extraction unit and a personalized model construction unit; The data preprocessing unit is used to perform format conversion and preliminary screening of the sleep and environmental parameters input by the guest through the remote control terminal, remove invalid data, and ensure the accuracy and availability of the data; The preference extraction unit extracts the guest's preferences for temperature, humidity, and noise environment factors, as well as requirements for mattress hardness and music type sleep factors by analyzing the preprocessed parameters by the data preprocessing unit; The personalized model building unit builds a personalized sleep parameter model based on the preference and requirement information extracted by the preference extraction unit and the basic information of the guest, thereby providing a basis for the subsequent generation of a customized sleep mode.

[0009] Preferably, the sleep function calculation module also includes a sleep mode generation submodule, and the sleep mode generation submodule includes an environmental parameter optimization unit. The environmental parameter optimization unit calculates the ideal indoor temperature curve, air humidity adjustment plan and air quality improvement measures based on the personalized model constructed by the sleep parameter analysis submodule and the real-time data of the indoor environment obtained by the environmental detection equipment to create a comfortable sleeping environment; the real-time data of the indoor environment includes the current temperature, humidity and air quality.

[0010] Preferably, the sleep function calculation module further includes a sleep effect evaluation submodule, and the sleep effect evaluation submodule includes a data acquisition unit, a feature extraction unit, an evaluation index calculation unit and a feedback adjustment unit; The data collection unit collects the sleep data of the guest in real time during the guest's sleep by connecting with the micro-sensing module and the environmental monitoring device. The sleep data includes sleep depth, sleep duration, number of tossing and turning, breathing frequency, and environmental data. The environmental data includes indoor temperature, humidity, and noise. The feature extraction unit performs feature extraction on the data collected by the data collection unit to extract features that can reflect the guest's sleep quality and environmental comfort, wherein the features include the frequency of sleep stage transitions and the stability of respiratory rhythm; The evaluation index calculation unit calculates the guest's sleep quality evaluation index according to the features extracted by the feature extraction unit, and the sleep quality evaluation index includes sleep efficiency and sleep satisfaction; The feedback adjustment unit compares the calculation result of the evaluation index by the evaluation index calculation unit with the preset sleep quality standard. If the standard is not met, an adjustment instruction is sent to the sleep mode generation submodule through the task scheduling module to dynamically adjust the sleep mode to optimize the guest's sleep experience.

[0011] Preferably, the device further includes a music control module which is connected to the cloud computing system via a data transmission line to obtain relevant instructions and information. The music control module is provided with a music player, an audio processing chip and a memory storing a personalized music therapy program. By receiving control instructions issued by the cloud computing system and / or personal preference information directly set by the guest, the personalized music therapy program is run to intelligently control the music player.

[0012] Preferably, the module further includes an aromatherapy control module which is connected to the cloud computing system via a data transmission line to realize information exchange. The aromatherapy control module is provided with an odor releasing device and a control chip. By receiving control instructions issued by the cloud computing system and / or the personal preference information of the guest, the odor releasing device is operated and controlled to release odors for aromatherapy.

[0013] Preferably, the micro-sensor module is any one of a microwave radar sensor, a capacitive sensor, a piezoelectric sensor or an RFID sensor, and the micro-sensor modules are evenly arranged laterally in the bed, and these micro-sensor modules transmit the collected information to the cloud computing system.

[0014] A method for controlling a sleep ecosystem includes the following control steps: inputting a guest's sleep and environment parameters before going to bed through a remote control terminal, operating an input interface on a display screen of the remote control terminal, and sending the input information to a cloud computing system through wireless communication after the input information is processed by a processor; The server in the cloud computing system extracts relevant data from the data storage unit according to the received parameter information and generates a customized sleep program; The cloud computing system is connected to the indoor environment control system to send the control instructions in the generated customized sleep program to the indoor environment control system to control the temperature, humidity, light and air;.

[0015] Preferably, the music control module includes the following control steps: The cloud computing system generates music control instructions based on the personal preference information directly set by the guest or the current sleep mode related information, and transmits them to the music control module. After receiving the instructions, the music control module controls the music player and adjusts the rhythm, volume, and track sequence parameters of the music playback according to the predetermined music playback logic to realize personalized music therapy program control.

[0016] Preferably, the aromatherapy control module includes the following control steps: According to personal preferences, the aromatherapy control module performs customizable aromatherapy control. The cloud computing system generates aromatherapy control instructions based on the personal preferences set by the guest and the current sleeping environment and mode information, and transmits them to the aromatherapy control module; after receiving the instructions, the aromatherapy control module controls the odor release device to release the corresponding odor, and adjusts the concentration and release frequency parameters of the odor to meet the guest's personalized needs for aromatherapy.

[0017] The present invention has the following beneficial effects: Through the remote control terminal and the sleep parameter analysis submodule, a personalized model can be built based on guest input and historical data to customize the sleeping environment, including temperature, humidity, mattress hardness, music type and smell, etc., to improve comfort and satisfaction. The sleep effect evaluation submodule monitors data in real time, calculates quality indicators and compares them with preset standards, dynamically adjusts the sleep mode, ensures that the sleeping environment is always suitable, and continuously optimizes the experience.

[0018] The environment detection and control module cooperates with the cloud computing system to adjust the indoor temperature, humidity, and air quality in real time based on the calculation results of the environmental parameter optimization unit to create a comfortable environment and reduce sleep interruptions caused by environmental discomfort. The music control and aromatherapy control modules help sleep from multiple senses. Personalized music and customized aromatherapy relieve stress, relax the body and mind, and help guests fall asleep and maintain a good sleep.

[0019] The data pre-processing unit of the cloud computing system ensures that data is accurate and available, the server processes data efficiently, and the data storage unit stores data effectively, laying the foundation for the stable operation and long-term optimization of the system. Each module is closely connected through the cloud computing system, and data flows effectively and instructions are accurately transmitted, making the system run efficiently and intelligently, providing guests with a one-stop sleep optimization solution. BRIEF DESCRIPTION OF THE DRAWINGS

[0020] Figure 1 It is a schematic diagram of the system framework of the present invention; Figure 2 is a flow chart of the system control method of the present invention; Figure 3 is a flow chart of the personalized music therapy program control method of the present invention; Figure 4 It is a flow chart of the control method of the aromatherapy control module of the present invention. DETAILED DESCRIPTION

[0021] The following will be combined with the embodiments and drawings to clearly and completely describe the concept, specific structure and technical effects of the present invention, so as to fully understand the purpose, scheme and effect of the present invention. It should be noted that the embodiments and features in the embodiments of this application can be combined with each other without conflict.

[0022] It should be noted that, unless otherwise specified, when a feature is referred to as being "fixed" or "connected" to another feature, it may be directly fixed or connected to the other feature, or it may be indirectly fixed or connected to the other feature. In addition, the descriptions of up, down, left, right, top, bottom, etc. used in the present invention are only relative to the relative positional relationship of the components of the present invention in the drawings.

[0023] In addition, unless otherwise defined, all technical and scientific terms used herein have the same meaning as those commonly understood by those skilled in the art. The terms used in this specification are only for describing specific embodiments and are not intended to limit the present invention. The term "and / or" used herein includes any combination of one or more related listed items.

[0024] It should be understood that, although the terms first, second, third, etc. may be used to describe various elements in the present disclosure, these elements should not be limited to these terms. These terms are only used to distinguish elements of the same type from each other. For example, without departing from the scope of the present disclosure, the first element may also be referred to as the second element, and similarly, the second element may also be referred to as the first element.

[0025] like Figure 1As shown, the technical solution according to the present invention is a sleep ecosystem, including a bed, a cloud computing system, and a remote control terminal connected to the cloud computing system, an environmental detection device for collecting indoor environmental data, and an indoor environmental device, wherein the bed is provided with a micro-sensor module for collecting human sleep parameters, the micro-sensor module is connected to the cloud computing system and transmits the collected parameters; the remote control terminal includes a display screen, an operation button and a processor, the remote control terminal is used to receive the sleep parameters and environmental parameters input by the guest before going to bed, and transmit the parameters to the cloud computing system; the cloud computing system includes a server, a data storage unit and a sleep function calculation module, the server is used to run an algorithm to process the received data, the data storage unit is used to store data, the sleep function calculation module analyzes and processes the received sleep parameters, environmental parameters, human sleep parameters transmitted by the micro-sensor module and indoor environmental data transmitted by the environmental detection device to obtain an evaluation result, and the cloud computing system sends a control instruction to the indoor environmental device according to the evaluation result to dynamically adjust the sleep mode to optimize the guest's sleep experience.

[0026] The environmental detection equipment includes: temperature sensors, humidity sensors, air quality sensors, sensors for detecting volatile organic compounds (VOCs), light sensors, noise sensors and other sensors.

[0027] The temperature sensor is used to measure the indoor temperature. The principle of the traditional thermistor temperature sensor is to measure the temperature by using the characteristic that the resistance of the thermistor changes with the temperature. For example, when the indoor temperature rises, the resistance of the thermistor will decrease. By measuring the current or voltage change in the circuit, the temperature value can be obtained. There are also digital temperature sensors, such as DS18B20, which can directly convert temperature signals into digital signals, communicate with microcontrollers or other devices through a data line, and conveniently transmit temperature data to the cloud computing system.

[0028] Among them, the common humidity sensor is a capacitive humidity sensor. Its working principle is based on the fact that humidity changes will cause changes in capacitance. When the hygroscopic medium of the sensor absorbs or releases moisture, the capacitance value changes accordingly, and the humidity is measured by detecting the change in capacitance. This sensor can accurately measure the relative humidity of indoor air and provide humidity data for creating a comfortable sleeping environment.

[0029] The air quality sensor includes a gas sensor, such as a sensor for detecting carbon dioxide concentration. In a sleeping environment, a high carbon dioxide concentration may affect sleep quality. Such sensors usually use carbon dioxide to react with chemicals in the sensor to generate electrical signal changes to detect carbon dioxide concentration.

[0030] Among them, the sensor for detecting volatile organic compounds (VOCs). Indoor furniture, decoration materials, etc. may release VOCs, and air quality sensors can detect the concentration of these harmful substances and provide data support for improving air quality.

[0031] The light sensor can detect the light intensity in the room. For example, the resistance of a photoresistor light sensor changes with the light intensity. During the day or when there is strong light in the room, the light sensor can detect strong light and transmit data to the system. The system can determine whether it is necessary to adjust shading devices such as curtains based on these data to create a darker environment that is more suitable for sleeping.

[0032] Noise sensors are used to detect indoor noise levels. Their working principle is to convert sound signals into electrical signals. When there is noise indoors, such as traffic noise from the outside or the sound of indoor electrical appliances, the noise sensor can detect information such as the intensity and frequency of the sound and transmit this data to the cloud computing system. The system can take corresponding measures based on the noise situation, such as adjusting the sound insulation equipment or covering up the noise by playing soothing music.

[0033] Furthermore, the cloud computing system also includes a network interface module, a security module and a task scheduling module. The network interface module is responsible for the communication connection between the cloud computing system and external devices, including the connection with the remote control terminal (such as a smart phone), indoor environmental equipment (such as lighting equipment, electric curtains, air conditioners, fans, dehumidifiers and humidifiers, etc., which can change the indoor environment), audio playback equipment, etc. It has a variety of network interface protocols, such as Ethernet, WiFi, Bluetooth, etc., to meet the communication needs of different devices. The security module is responsible for the security protection of the cloud computing system, including data encryption, user authentication, access control and other functions. It uses advanced encryption algorithms and security technologies to ensure that the guest's privacy data is not leaked and the system is not attacked maliciously. The task scheduling module is used to coordinate the work of various modules within the cloud computing system, and reasonably arrange computing resources and task execution order according to the priority and resource requirements of the task to ensure the efficient operation of the system.

[0034] The cloud computing system is connected to the remote control terminal via wireless communication to receive parameter information from the remote control terminal. The indoor environment equipment includes: (1) air conditioner: receiving control instructions from the cloud computing system, adjusting the indoor temperature, and realizing cooling or heating functions to meet the temperature requirements of the personalized sleep model. It can be precisely controlled according to the ideal indoor temperature curve calculated by the environmental parameter optimization unit. (2) fan: adjusting the wind speed and wind direction according to the instructions of the cloud computing system, cooperating with the air conditioner to achieve better air flow and temperature regulation effects, and at the same time, it can be used as an air circulation device alone at a suitable temperature to improve the comfort of the sleeping environment. (3) dehumidifier: working according to the instructions of the cloud computing system, when the indoor humidity is higher than the set value of the personalized model or the upper limit of the humidity determined by the environmental parameter optimization unit, the dehumidification function is activated to reduce the indoor humidity. (4) humidifier: when the indoor humidity is lower than the set value, it is turned on according to the instructions of the cloud computing system, increasing the air humidity, maintaining it within the humidity range suitable for sleep, and ensuring the comfort of the sleeping environment. (5) electric curtain: automatically adjusting the opening and closing degree by receiving instructions from the cloud computing system. For example, it can automatically close at night to create a quiet and dark sleeping environment; during the day, it can adjust the opening and closing degree appropriately according to the light intensity and the sleep mode set by the guest to ensure that the indoor light is appropriate; (6) Intelligent lighting equipment, connected to the cloud computing system, can make different lighting adjustments according to the sleep mode. Before going to bed, the light gradually dims to create a relaxing atmosphere; during sleep, it keeps a very low brightness or completely turns off to avoid disturbing sleep; in the early morning, it can simulate natural light and gradually brighten to gently wake the user; (7) Air purifiers, receiving instructions from the cloud computing system, purify indoor air in real time, remove pollutants such as dust, pollen, and bacteria, improve air quality, and create a healthier sleeping environment for users. (8) Smart speakers, linked to the cloud computing system, can play soothing music and natural sounds (such as the sound of waves and rain) before going to bed to help sleep, and can also make voice reminders or broadcast environmental parameters and other information at the set time. (9) Intelligent floor heating equipment, in cold seasons, adjusts the indoor floor temperature according to the control instructions of the cloud computing system, provides comfortable foot warmth, promotes blood circulation, and improves sleep quality. (10) The fresh air system continuously introduces fresh air and exhausts polluted air in the room, ensuring that the freshness and oxygen content of the air are always at an appropriate level during sleep. At the same time, the fresh air volume and wind speed can be adjusted according to the sleep pattern.

[0035] The sleep function calculation module is provided with a sleep parameter analysis submodule, and the sleep parameter analysis submodule includes a data preprocessing unit, a preference extraction unit and a personalized model construction unit; The data preprocessing unit is used to perform format conversion and preliminary screening of the sleep and environmental parameters input by the guest through the remote control terminal, remove invalid data, and ensure the accuracy and availability of the data; The preference extraction unit analyzes the preprocessed parameters by the data preprocessing unit and uses machine learning algorithms, such as decision trees and neural networks, to extract the guest's preferences for temperature, humidity, and noise environment factors, as well as requirements for mattress hardness and music type sleep factors; The personalized model building unit builds a personalized sleep parameter model based on the preference and requirement information extracted by the preference extraction unit and the basic information of the guest (such as age, gender, physical condition, etc.), thereby providing a basis for the subsequent generation of a customized sleep mode.

[0036] The sleep function calculation module also includes a sleep mode generation submodule, and the sleep mode generation submodule includes an environmental parameter optimization unit. The environmental parameter optimization unit, based on the personalized model constructed by the sleep parameter analysis submodule, combines the real-time data of the indoor environment obtained by the environmental detection equipment, such as the current temperature, humidity, air quality, etc., and uses the thermal comfort model, air quality model, etc. to calculate the ideal indoor temperature curve, air humidity adjustment plan and air quality improvement measures to create a comfortable sleeping environment; the real-time data of the indoor environment includes the current temperature, humidity, and air quality.

[0037] The sleep function calculation module also includes a sleep effect evaluation submodule, which includes a data acquisition unit, a feature extraction unit, an evaluation index calculation unit, and a feedback adjustment unit; The data collection unit collects the sleep data of the guest in real time during the guest's sleep by connecting with the micro-sensing module and the environmental monitoring device. The sleep data includes sleep depth, sleep duration, number of tossing and turning, breathing frequency, and environmental data. The environmental data includes indoor temperature, humidity, and noise. The feature extraction unit extracts features from the data collected by the data collection unit, and uses signal processing technology and statistical methods to extract features that can reflect the guest's sleep quality and environmental comfort, wherein the features include the frequency of sleep stage transitions and the stability of respiratory rhythm; The evaluation index calculation unit calculates the guest's sleep quality evaluation index based on the features extracted by the feature extraction unit and using a sleep quality evaluation model (pre-established and stored in the data storage unit), wherein the sleep quality evaluation index includes sleep efficiency and sleep satisfaction; The feedback adjustment unit compares the calculation result of the evaluation index by the evaluation index calculation unit with the preset sleep quality standard. If the standard is not met, an adjustment instruction is sent to the sleep mode generation submodule through the task scheduling module to dynamically adjust the sleep mode to optimize the guest's sleep experience.

[0038] like Figure 1As shown, it also includes a music control module that is connected to the cloud computing system through a data transmission line to obtain relevant instructions and information. The music control module is equipped with a music player, an audio processing chip, and a memory storing a personalized music therapy program. By receiving control instructions issued by the cloud computing system and / or personal preference information directly set by the guest, the personalized music therapy program is run to intelligently control the music player. Figure 3 The music control module shown includes the following control steps: the cloud computing system generates music control instructions based on the personal preference information directly set by the guest or the current sleep mode related information, and transmits them to the music control module; after receiving the instructions, the music control module controls the music player, and adjusts the rhythm, volume, and track sequence parameters of the music playback according to the predetermined music playback logic to realize personalized music therapy program control.

[0039] like Figure 1 As shown, it also includes an aromatherapy control module that is connected to the cloud computing system through a data transmission line to realize information exchange. The aromatherapy control module is equipped with an odor release device and a control chip. By receiving control instructions from the cloud computing system and / or the guest's personal preference information, the odor release device is operated and controlled to release odors for aromatherapy. Figure 3 The aromatherapy control module shown includes the following control steps: according to personal preferences, the aromatherapy control module performs customizable aromatherapy control, and the cloud computing system generates aromatherapy control instructions according to the personal preferences set by the guest and the current sleeping environment and mode information, and transmits them to the aromatherapy control module; after receiving the instructions, the aromatherapy control module controls the odor release device to release the corresponding odor, and adjusts the concentration and release frequency parameters of the odor to meet the guest's personalized needs for aromatherapy.

[0040] The micro-sensor module is any one of a microwave radar sensor, a capacitive sensor, a piezoelectric sensor or an RFID sensor. The micro-sensor modules are evenly arranged in a horizontal direction in the bed body. These micro-sensor modules transmit the collected information to the cloud computing system.

[0041] The microwave radar sensor is composed of a microwave transmitting and receiving antenna and a signal processing circuit, and adopts high-frequency microwave materials (such as ceramic-based microwave dielectric materials). The microwave transmitting and receiving antennas are connected through the principle of electromagnetic induction to realize the transmission and reception of microwave signals. The signal processing circuit is connected to the antenna through a line to process the received microwave signal and transmit the processed signal to the cloud computing system through the line.

[0042] The capacitive sensor is composed of electrodes and a capacitance detection circuit, and uses a conductive polymer (such as polyaniline) or a conductive fiber (such as carbon fiber). The electrodes and the capacitance detection circuit are connected through a line, and the capacitive sensor senses the presence and movement of the human body by detecting changes in capacitance, and the detected signal is transmitted to the cloud computing system through the line.

[0043] The piezoelectric sensor is composed of a piezoelectric ceramic sheet or a piezoelectric polymer sheet and an electrode, and adopts piezoelectric ceramics (such as barium titanate) or piezoelectric polymers (such as polyvinylidene fluoride). The piezoelectric ceramic sheet or piezoelectric polymer sheet is connected to the electrode through a line, and uses the piezoelectric effect to generate an electrical signal through pressure changes, and the electrical signal is transmitted to the cloud computing system through the line.

[0044] The RFID sensor is composed of an RFID tag, an antenna and a reader / writer, and uses a high-frequency RFID tag and antenna (such as an ultra-high frequency RFID tag and antenna). The RFID tag and antenna are connected to the reader / writer through the principle of radio frequency identification to detect the presence and movement of the human body, and the detected signal is transmitted to the cloud computing system through the line.

[0045] The different sensors have different detection functions. The microwave radar sensor uses microwave reflection to detect the movement and breathing of the human body, and can accurately detect the breathing frequency and the number of rolls without contacting the human body; the capacitive sensor can be embedded in the surface of the mattress, and can sense the presence and movement of the human body and detect changes in body temperature and humidity by detecting changes in capacitance; the piezoelectric sensor uses the piezoelectric effect to generate electrical signals through pressure changes, and can detect the number of rolls and breathing without an external power supply; the RFID sensor uses radio frequency identification technology to detect the presence and movement of the human body, and can transmit data to the receiver without a power supply. These sensors work together through their own structures and connection methods to transmit the collected human-related information to the cloud computing system, providing data support for customized sleep programs.

[0046] The mattress is made of biodegradable skin-friendly materials, and its structure is a multi-layer composite material. It includes an upper natural fiber layer (such as bamboo fiber or hemp fiber), which is connected by a textile process to form a flat surface for providing comfortable touch and breathability; a middle sponge layer (such as memory sponge or polyurethane sponge), which is connected to the upper natural fiber layer by gluing or hot pressing process for providing cushioning and support; and a lower biodegradable polymer base layer (such as polyhydroxyalkanoate (PHA)), which is connected to the middle sponge layer by gluing or hot pressing process for maintaining the shape and stability of the mattress.

[0047] like Figure 2As shown, a control method of a sleep ecosystem includes the following control steps: inputting the sleep and environment parameters of the guest through a remote control terminal before going to bed, operating the input interface on the display screen of the remote control terminal, and sending the input information to the cloud computing system through wireless communication after being processed by a processor; The server in the cloud computing system extracts relevant data from the data storage unit according to the received parameter information and generates a customized sleep program; The cloud computing system is connected to the indoor environment control system to send the control instructions in the generated customized sleep program to the indoor environment control system to control the temperature, humidity, light and air;.

[0048] The specific implementation process of this system is as follows: Build a sleep ecosystem, install the bed, and evenly arrange micro-sensor modules such as microwave radar sensors horizontally in the bed to ensure that they are properly connected to the cloud computing system.

[0049] Deploy a cloud computing system, including a server, a data storage unit, and a sleep function computing module, and start and initialize it.

[0050] Install the remote control terminal and check the display screen, operation buttons and processor functions to ensure that it can communicate with the cloud computing system. At the same time, install the environmental detection equipment and environmental control module and ensure that they are connected to the cloud computing system.

[0051] Before going to bed, guests use the remote control terminal to input sleep parameters (such as the desired mattress hardness) and environmental parameters (such as the ideal temperature range) on the input interface of the display screen by operating buttons. After processing, the processor sends the data to the cloud computing system via wireless communication.

[0052] The data preprocessing unit in the cloud computing system performs format conversion and preliminary screening on the data, removing invalid temperature values ​​that are obviously beyond the normal range. The preference extraction unit analyzes the processed data to extract the guest's preferences for environmental factors such as temperature, humidity, and noise, as well as the requirements for sleep factors such as mattress hardness and music type. The personalized model construction unit combines the basic information of the guest to build a personalized sleep parameter model.

[0053] Environmental detection equipment collects indoor environmental data in real time (such as current temperature 25°C, humidity 60%, and good air quality) and transmits it to the cloud computing system.

[0054] The environmental parameter optimization unit in the sleep function calculation module calculates the adjustment plan based on the personalized model and real-time environmental data. For example, if the guest prefers a temperature of 22°C, the system calculates the corresponding temperature adjustment curve and sends instructions to the environmental control module through the cloud computing system to adjust the air conditioning temperature.

[0055] When the guest is sleeping, the micro-sensor module collects sleep data in real time (such as the depth of sleep is in the deep sleep stage, the number of turns per hour is 2 times, and the breathing rate is stable), and the environmental monitoring equipment continuously collects environmental data (such as noise of 30 decibels) and transmits these data to the data collection unit of the cloud computing system.

[0056] The feature extraction unit extracts features such as low frequency of sleep stage transitions and stable breathing rhythm from the collected data. The evaluation index calculation unit calculates the evaluation results of high sleep efficiency and high sleep satisfaction based on these features. If the evaluation result does not meet the preset standard, the feedback adjustment unit sends instructions to the sleep mode generation submodule through the task scheduling module, such as adjusting parameters such as temperature or air humidity to optimize the sleep mode.

[0057] The music control module is connected to the cloud computing system through a data transmission line. If the guest sets the soothing music preference he / she likes on the remote control terminal, or the cloud computing system determines that music is needed to assist sleep based on the current sleep pattern, the cloud computing system sends instructions to the music control module. The audio processing chip in the music control module runs the personalized music therapy program according to the instructions, controls the music player to play soothing music such as classical music, and adjusts parameters such as rhythm and volume.

[0058] The aromatherapy control module is also connected to the cloud computing system. When the guest prefers the scent of lavender or the system thinks that aromatherapy is needed, the cloud computing system sends instructions to the aromatherapy control module, and the control chip controls the scent release device to release the lavender scent and adjusts parameters such as concentration and release frequency to help the guest sleep.

[0059] The above is only a preferred embodiment of the present invention. The present invention is not limited to the above implementation. As long as the technical effect of the present invention is achieved by the same means, any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present disclosure shall be included in the scope of protection of the present disclosure. All should belong to the protection scope of the present invention. Within the protection scope of the present invention, its technical scheme and / or implementation method can have various modifications and changes.

Claims

1. A sleep ecosystem, characterized in that: The invention comprises a bed, a cloud computing system, a remote control terminal connected to the cloud computing system, an environmental detection device for collecting indoor environmental data, and an indoor environmental device, wherein the bed is provided with a micro-sensor module for collecting human sleep parameters, the micro-sensor module is connected to the cloud computing system and transmits the collected parameters; the remote control terminal comprises a display screen, operation buttons and a processor, the remote control terminal is used to receive sleep parameters and environmental parameters input by the guest before going to bed, and transmit the parameters to the cloud computing system; the cloud computing system comprises a server, a data storage unit and a sleep function calculation module, the server is used to run an algorithm to process the received data, the data storage unit is used to store data, the sleep function calculation module analyzes and processes the received sleep parameters, environmental parameters, human sleep parameters transmitted by the micro-sensor module and indoor environmental data transmitted by the environmental detection device to obtain an evaluation result, and the cloud computing system issues a control instruction to the indoor environmental device according to the evaluation result to dynamically adjust the sleep mode to optimize the guest's sleep experience.

2. A sleep ecosystem according to claim 1, characterized in that: The sleep function calculation module is provided with a sleep parameter analysis submodule, and the sleep parameter analysis submodule includes a data preprocessing unit, a preference extraction unit and a personalized model construction unit; The data preprocessing unit is used to perform format conversion and preliminary screening of the sleep and environmental parameters input by the guest through the remote control terminal, remove invalid data, and ensure the accuracy and availability of the data; The preference extraction unit extracts the guest's preferences for temperature, humidity, and noise environment factors, as well as requirements for mattress hardness and music type sleep factors by analyzing the preprocessed parameters by the data preprocessing unit; The personalized model building unit builds a personalized sleep parameter model based on the preference and requirement information extracted by the preference extraction unit and the basic information of the guest, thereby providing a basis for the subsequent generation of a customized sleep mode.

3. A sleep ecosystem according to claim 2, characterized in that: The sleep function calculation module also includes a sleep mode generation submodule, and the sleep mode generation submodule includes an environmental parameter optimization unit. The environmental parameter optimization unit calculates an ideal indoor temperature curve, air humidity adjustment plan and air quality improvement measures based on the personalized model constructed by the sleep parameter analysis submodule and the real-time data of the indoor environment obtained by the environmental detection equipment to create a comfortable sleeping environment; the real-time data of the indoor environment includes the current temperature, humidity and air quality.

4. A sleep ecosystem according to claim 3, characterized in that: The sleep function calculation module also includes a sleep effect evaluation submodule, which includes a data acquisition unit, a feature extraction unit, an evaluation index calculation unit, and a feedback adjustment unit; The data collection unit collects the sleep data of the guest in real time during the guest's sleep by connecting with the micro-sensing module and the environmental monitoring device. The sleep data includes sleep depth, sleep duration, number of tossing and turning, breathing frequency, and environmental data. The environmental data includes indoor temperature, humidity, and noise. The feature extraction unit performs feature extraction on the data collected by the data collection unit to extract features that can reflect the guest's sleep quality and environmental comfort, wherein the features include the frequency of sleep stage transitions and the stability of respiratory rhythm; The evaluation index calculation unit calculates the guest's sleep quality evaluation index according to the features extracted by the feature extraction unit, and the sleep quality evaluation index includes sleep efficiency and sleep satisfaction; The feedback adjustment unit compares the calculation result of the evaluation index by the evaluation index calculation unit with the preset sleep quality standard. If the standard is not met, an adjustment instruction is sent to the sleep mode generation submodule through the task scheduling module to dynamically adjust the sleep mode to optimize the guest's sleep experience.

5. A sleep ecosystem according to claim 1, characterized in that: It also includes a music control module that is connected to the cloud computing system through a data transmission line to obtain relevant instructions and information. The music control module is equipped with a music player, an audio processing chip and a memory storing a personalized music therapy program. By receiving control instructions issued by the cloud computing system and / or personal preference information directly set by the guest, the personalized music therapy program is run to intelligently control the music player.

6. A sleep ecosystem according to claim 1, characterized in that: It also includes an aromatherapy control module that is connected to the cloud computing system through a data transmission line to achieve information exchange. The aromatherapy control module is provided with an odor release device and a control chip. By receiving control instructions from the cloud computing system and / or the guest's personal preference information, the controlled odor release device is operated to release odors for aromatherapy.

7. The sleep ecosystem according to claim 1, characterized in that: The micro-sensor module is any one of a microwave radar sensor, a capacitive sensor, a piezoelectric sensor or an RFID sensor. The micro-sensor modules are evenly arranged in a horizontal direction in the bed body. These micro-sensor modules transmit the collected information to the cloud computing system.

8. The method for controlling a sleep ecosystem according to claim 1, characterized in that: The control method comprises the following steps: inputting the sleep and environment parameters of the guest before going to bed through the remote control terminal, operating the input interface on the display screen of the remote control terminal, and sending the input information to the cloud computing system through wireless communication after the processor processes the input information; The server in the cloud computing system extracts relevant data from the data storage unit according to the received parameter information and generates a customized sleep program; The cloud computing system is connected to the indoor environment control system to send the control instructions in the generated customized sleep program to the indoor environment control system to control the temperature, humidity, light and air.

9. The method for controlling a sleep ecosystem according to claim 5, characterized in that: The music control module includes the following control steps: The cloud computing system generates music control instructions based on the personal preference information directly set by the guest or the current sleep mode related information, and transmits them to the music control module. After receiving the instructions, the music control module controls the music player and adjusts the rhythm, volume, and track sequence parameters of the music playback according to the predetermined music playback logic to realize personalized music therapy program control.

10. A method for controlling a sleep ecosystem according to claim 6, characterized in that: The aromatherapy control module includes the following control steps: According to personal preferences, the aromatherapy control module performs customizable aromatherapy control. The cloud computing system generates aromatherapy control instructions based on the personal preferences set by the guest and the current sleeping environment and mode information, and transmits them to the aromatherapy control module; after receiving the instructions, the aromatherapy control module controls the odor release device to release the corresponding odor, and adjusts the concentration and release frequency parameters of the odor to meet the guest's personalized needs for aromatherapy.

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