A cloud platform-based home environment monitoring method and system

Abstract

The application provides a kind of cloud platform-based home environment supervision method and system, method includes: setting the safety period of home environment, obtains the safety data of each first equipment in safety period;Through cloud platform, real-time record instruction set and construction information;Obtain the environmental data recorded in each supervision period by each first equipment, respectively, compare whether there is difference between the environmental data of each supervision period and safety data;When there is difference in a certain period, then the difference is classified, and the reason is analyzed based on the change attribute;Analysis result is sent to user together with the environmental data corresponding to the difference of this supervision period.The application realizes the intelligent supervision of home environment by combining cloud platform and home equipment with monitoring function, analyzes the possible abnormal phenomena, combines external environmental factors and user personal factors, and ensures that the abnormality in home environment can be accurately and reasonably solved.

Description

Technical Field

[0001] This invention relates to the field of smart homes, and in particular to a method and system for monitoring the home environment based on a cloud platform. Background Technology

[0002] As living standards improve, people are moving from simply having a place to live to having a comfortable place to live, and smart living spaces are gradually coming into focus. Supported by innovative technologies related to the Internet of Things and artificial intelligence, the wave of smart technology has permeated every corner of daily life, and whole-house smart technology is gradually evolving from a technological term into a consumer trend.

[0003] Smart home technology is a product of integrating Internet of Things (IoT) technology into home design. Based on the IoT concept, smart home technology aims to activate various devices in home life, such as video and audio systems, lighting systems, air conditioning systems, security systems, computer equipment, security systems, heating and cooling systems, etc. These devices are also called smart home devices. With the help of sensors and communication networks, smart home devices are connected to each other, thereby combining smart home devices with the home environment to form a smart home system for people to use.

[0004] In a smart home environment, monitoring the home environment is essential. Smart home devices can automate many household tasks, but this doesn't mean they are immune to malfunctions or errors. For example, if a smart light bulb malfunctions, it may continue to emit incorrect signals, causing the room to remain on or excessively bright. Furthermore, many smart home devices rely on internet connectivity, making it difficult to rule out the possibility of hacking or other security threats. For instance, if a smart camera is hacked, hackers could control it via the network and steal sensitive information.

[0005] Therefore, in a smart home environment, it is necessary to monitor the home environment to ensure that the devices operate normally. Summary of the Invention

[0006] In view of this, the present invention proposes a method and system for monitoring the home environment based on a cloud platform, the specific solution of which is as follows:

[0007] A cloud-based method for monitoring the home environment includes the following:

[0008] In a smart home environment, a communication mechanism is established between the cloud platform and home devices;

[0009] Home appliances that can record environmental data are selected and designated as the first type of appliance. The environmental data includes image data, audio data, and temperature data.

[0010] Set a safe time period for the home environment, and acquire safety data, including safe images, safe audio, and safe temperature, recorded by each of the first devices during the safe time period;

[0011] The cloud platform records users' commands about home appliances in real time, and combines user input with real-time updates of construction information about the surrounding home environment retrieved from the Internet.

[0012] The cloud platform is used to obtain environmental data recorded by each of the first devices during each monitoring period, and the differences between the image data and the safety image, the audio data and the safety audio, and the temperature data and the safety temperature during each monitoring period are compared to see if there are any discrepancies.

[0013] When there are differences in a certain period of time, the differences are classified into four categories of change attributes: color, temperature, sound, and brightness. Based on the change attributes, the analysis is combined with the instruction set to determine whether the differences are caused by user instructions, and combined with the construction information to determine whether the differences are caused by the construction environment.

[0014] The analysis results, along with the environmental data corresponding to the differences in the regulatory period, will be sent to the user.

[0015] In one specific embodiment, home appliances that can cause changes in such change attributes are selected based on the difference in change attributes and the region where they are located, and these are used as second appliances;

[0016] The relevant instructions for the second device are found in the instruction set, the causal relationship between the relevant instructions and the difference is analyzed, and then it is determined whether the difference is caused by the user instruction.

[0017] In one specific embodiment, when the variation attribute of the difference is classified as sound, abnormal audio is extracted from the audio data;

[0018] When the monitoring period of the discrepancy falls within the construction time recorded in the construction information, the abnormal audio is compared with a preset noise database to determine if the same type of sound exists.

[0019] If it exists, then the difference is determined to be caused by the external environment;

[0020] If not, the environmental data and abnormal audio for that monitoring period will be sent to the user for confirmation.

[0021] In one specific embodiment, if the analysis results show that the difference is not caused by user instructions or the construction environment, the difference is determined to be an abnormal difference;

[0022] When discrepancies are reflected in image data, facial recognition is performed through the cloud platform, and an alert is issued to the user if a stranger is found among the discrepancies.

[0023] When the difference is reflected in the audio data, the cloud platform performs sound recognition and issues an alarm to the user if a preset danger sound is present in the difference.

[0024] When the difference is reflected in the temperature data, the cloud platform determines whether the temperature corresponding to the difference exceeds the preset temperature, and issues an alarm to the user if it does.

[0025] In one specific embodiment, when a difference in a certain monitoring period is simultaneously reflected in image data, audio data, and temperature data, and the time interval between the occurrence of the difference in image data, audio data, and temperature data is less than a preset time interval, an alarm is immediately issued to the user.

[0026] In one specific embodiment, a deep neural network model is used to compare whether there are differences between environmental data and security data, and the differences are categorized and analyzed. The differences and the corresponding analysis results are used as training data to train the deep neural network model.

[0027] In one specific embodiment, the first device includes a smart camera capable of capturing image and audio data, a smart light bulb capable of measuring temperature data, a smart air conditioner capable of measuring temperature data, and a smart mirror capable of capturing image data.

[0028] In one specific embodiment, in the security data, regions that change during a security period are selected as change regions, and the pattern of change of these change regions during the security period is recorded;

[0029] If the changes in environmental data within the monitored area do not conform to this pattern, then it is considered a discrepancy.

[0030] In one specific embodiment, the duration of the monitoring period is an integer multiple of the duration of the safety period.

[0031] A cloud-based home environment monitoring system includes the following:

[0032] A communication unit is used to establish a communication mechanism between the cloud platform and home devices in a smart home environment.

[0033] A filtering unit is used to filter out home appliances that can record environmental data and designate them as the first appliances. The environmental data includes image data, audio data, and temperature data.

[0034] The safety data unit is used to set a safe period for the home environment and acquire safety data, including safety images, safety audio, and safety temperature, recorded by each of the first devices during the safe period.

[0035] The external factors unit is used to record the user's set of instructions about home appliances in real time through the cloud platform, and to integrate user input and real-time updated construction information of the surrounding home environment captured from the Internet;

[0036] The difference comparison unit is used to obtain environmental data recorded by each of the first devices in each monitoring period through the cloud platform, and compare whether there are differences between the image data and the safety image, the audio data and the safety audio, and the temperature data and the safety temperature in each monitoring period.

[0037] The difference analysis unit is used to classify differences according to four categories of change attributes: color, temperature, sound, and brightness when differences exist in a certain period of time. Based on the change attributes, it analyzes whether the differences are caused by user commands in combination with the instruction set, and analyzes whether the differences are caused by the construction environment in combination with the construction information.

[0038] The sending unit is used to send the analysis results, along with the environmental data corresponding to the differences in the regulatory period, to the user.

[0039] Beneficial Effects: This invention proposes a cloud-based method and system for monitoring the home environment. By combining a cloud platform with home appliances equipped with monitoring functions, it achieves intelligent monitoring of the home environment and implements corresponding response mechanisms upon detecting anomalies, ensuring the normal operation of the smart home environment. Based on the stability of the home environment, it monitors the home environment in real time to ensure the normal operation of devices. It analyzes potential anomalies, combining external environmental factors and user-related factors, to ensure that anomalies occurring in the home environment can be accurately and reasonably resolved. Attached Figure Description

[0040] To more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings used in the embodiments will be briefly introduced below. It should be understood that the following drawings only show some embodiments of the present invention and should not be regarded as a limitation on the scope. For those skilled in the art, other related drawings can be obtained based on these drawings without creative effort.

[0041] Figure 1 This is a schematic diagram of the home environment monitoring method according to an embodiment of the present invention;

[0042] Figure 2 This is a schematic diagram of a home environment monitoring system module according to an embodiment of the present invention.

[0043] Reference numerals in the attached figures: 1-Communication unit; 2-Filtering unit; 3-Security data unit; 4-External factor unit; 5-Difference comparison unit; 6-Difference analysis unit; 7-Sending unit. Detailed Implementation

[0044] In the following, various embodiments of the invention will be described more fully. The invention may have various embodiments, and adjustments and changes may be made therein. However, it should be understood that there is no intention to limit the various embodiments of the invention to the specific embodiments disclosed herein, but rather the invention should be understood to cover all adjustments, equivalents, and / or alternatives falling within the spirit and scope of the various embodiments disclosed herein.

[0045] The terminology used in the various embodiments disclosed herein is for the purpose of describing particular embodiments only and is not intended to limit the various embodiments disclosed herein. As used herein, the singular form is intended to include the plural form as well, unless the context clearly indicates otherwise. Unless otherwise defined, all terms used herein (including technical and scientific terms) have the same meaning as commonly understood by one of ordinary skill in the art to which the various embodiments disclosed herein pertain. The terms (such as those defined in commonly used dictionaries) are to be interpreted as having the same meaning as in the context of the relevant technical field and are not to be interpreted as having an idealized or overly formal meaning, unless clearly defined in the various embodiments disclosed herein.

[0046] Example 1

[0047] Embodiment 1 of this invention discloses a cloud-based method for monitoring the home environment. This method enables the cloud platform to work with home devices equipped with monitoring functions to monitor the home environment and take corresponding response mechanisms upon detecting anomalies, ensuring the normal operation of the smart home environment. A flowchart of the home environment monitoring method is attached. Figure 1 As shown, the specific solution is as follows:

[0048] A cloud-based method for monitoring the home environment includes the following:

[0049] 101. In a smart home environment, establish a communication mechanism between the cloud platform and home devices;

[0050] 102. Select home appliances that can record environmental data and use them as the first choice. Environmental data includes image data, audio data, and temperature data.

[0051] 103. Set safe time periods for the home environment and acquire safety data, including safe images, safe audio, and safe temperature, recorded by each primary device during the safe time period;

[0052] 104. Record user commands about home appliances in real time through the cloud platform, and update construction information around the home environment in real time by combining user input and data captured from the Internet;

[0053] 105. Obtain environmental data recorded by each first device during each monitoring period through the cloud platform, and compare the differences between the image data and the safe image, the audio data and the safe audio, and the temperature data and the safe temperature during each monitoring period;

[0054] 106. When there are differences in a certain period of time, the differences are classified into four categories of change attributes: color, temperature, sound, and brightness. Based on the change attributes, the difference is analyzed in combination with the instruction set to determine whether it is caused by user instructions, and in combination with construction information to determine whether it is caused by the construction environment.

[0055] 107. Send the analysis results, along with the environmental data corresponding to the differences in the regulatory period, to the user.

[0056] The home environment monitoring method provided in this embodiment monitors the home environment in real time based on its stability to ensure the normal operation of equipment. It analyzes potential anomalies, combining external environmental factors with personal user factors, to ensure that anomalies occurring in the home environment can be accurately and reasonably resolved.

[0057] The home environment monitoring method in this embodiment requires data analysis and processing via a cloud platform within a smart home environment. Therefore, it is necessary to pre-establish communication between the cloud platform and smart home devices, and to grant the cloud platform certain permissions to read data from the first device.

[0058] This embodiment leverages the intelligence of home devices within a home environment to monitor the environment from three dimensions: sound, light, and heat. The cloud platform itself lacks data measurement capabilities and must rely on a first device for monitoring the home environment. Specifically, the first device is defined as the home device capable of acquiring and recording environmental data; this first device must be able to communicate with the cloud platform. Preferably, the first device includes a smart camera capable of capturing image and audio data, a smart light bulb capable of measuring temperature data, a smart air conditioner capable of measuring temperature data, and a smart mirror capable of capturing image data.

[0059] Environmental data includes image data, audio data, and temperature data. Image data can be acquired through smart cameras, smart mirrors, etc., and can be extracted from video data to extract frames or taken at specific times to capture images of a specific area. Image data is typically taken by a fixed device over a fixed area. When certain parts of that area change, the changed areas can be easily identified through image comparison on the cloud platform. For example, a smart camera can be fixed to capture the location of a door. The door is closed during safe times, and if it is opened during monitoring, it can be detected immediately through image comparison. Audio data can also be acquired through smart cameras, smart speakers, smart voice assistants, etc. Temperature data can be acquired through thermometers, smart refrigerators, etc. In short, the cloud platform uses home devices to monitor the home environment. In certain special scenarios, other data can also be added as environmental data, such as brightness data and circuit parameters.

[0060] This embodiment defines safe periods and monitoring periods. A safe period represents the time when the home environment is in a normal state; the environmental data of the first device during the safe period is the safe data, such as safe images, safe audio, and safe temperature. The safe period can be selected by the user. The monitoring period is the time during which home devices need to be monitored, such as when the user is not home. Difference comparisons and analyses are performed within each monitoring period. Preferably, the monitoring period is an integer multiple of the safe period to facilitate the splitting and comparison of data within the monitoring period. Users can set the monitoring and safe periods as needed. For example, monitoring periods can be continuous or spaced out. For instance, a monitoring period can begin after a certain period of time.

[0061] Once the differences are identified, this embodiment defines four categories of change attributes to facilitate subsequent analysis. When differences exist, they are categorized into four types of change attributes: color, temperature, sound, and brightness. Setting these change attributes facilitates quick identification of the causes of the differences. For example, if the difference is categorized as temperature, instructions and devices that cause temperature changes, such as a user switching the air conditioner on or off, can be prioritized. If the difference is categorized as brightness, instructions and devices that cause brightness changes, such as a user switching lights on or off, can be prioritized. Color and brightness are relatively similar and can be flexibly selected based on the actual situation. Based on the change attributes of the differences and the surrounding area, home appliances that can cause changes in that type of change attribute are selected and designated as secondary devices. Secondary devices are given priority consideration.

[0062] The home environment monitoring method in this embodiment fully considers the impact of external environmental factors and user operation factors on the home environment. Specifically, it establishes construction information and a set of instructions. The instruction set records the user's operations on various home appliances, allowing the cloud platform to trace the source of environmental changes and determine whether they are caused by the user. The construction information takes into account the impact of audio data.

[0063] The instruction set is also designed to analyze the causes of discrepancies. Specifically, based on the changing attributes of the discrepancy and its location, home appliances that can cause such changes are selected and designated as secondary devices. The instruction set is then used to find relevant instructions for these secondary devices, analyze the causal relationship between these instructions and the discrepancy, and determine whether the discrepancy was caused by a user instruction. User actions may have subsequent chain reactions in the home environment. For example, if a user forgets to turn off the air conditioner when leaving the house, and the air conditioner remains in cooling mode, the room temperature may be too low. In this case, the cloud platform will report the temperature difference to the user, who can then remotely control the air conditioner to turn off. The purpose of the instruction set is to determine whether the discrepancy was caused by the user.

[0064] Within urban built-up areas, construction companies must adhere to legally mandated construction hours, prohibiting noisy construction work during midday (12:00-14:00) and nighttime (23:00-07:00 the next day). Therefore, users are typically not at home during construction. At this time, devices such as smart speakers may record construction noise, while there may be no construction noise during safe periods. Based on this, this embodiment incorporates the feature of construction information to minimize the impact of construction on the home environment through the cloud platform. Construction information is usually published on relevant online platforms, which can be retrieved using the cloud platform. The construction information typically records the construction time. When discrepancies are detected in the audio data, it can be determined whether the time period falls within construction time; if so, the discrepancy can be ignored. For some construction information, such as when a neighbor in the same building is carrying out construction, users can manually input the relevant construction information.

[0065] Specifically, when the variation in the audio signal is categorized as sound, abnormal audio is extracted from the audio data. This can be achieved using audio processing libraries (such as librosa in Python) to extract noise from the audio data, and then automatically detecting noise using thresholding or other methods. When the monitored period for the variation falls within the construction time recorded in the construction information, the abnormal audio is compared with a pre-defined noise database to determine if the same type of sound exists. If it does, the variation is determined to be caused by the external environment; if not, the environmental data for that monitored period and the abnormal audio are sent to the user for confirmation of whether it is construction noise, thus determining whether the variation is caused by the external environment. Furthermore, the abnormal audio can be analyzed by examining the audio signal's spectrum, equalizer, and other parameters to understand the noise's characteristics and add it to the noise database.

[0066] In this embodiment, differences can be simultaneously reflected in multiple types of environmental data. When differences are simultaneously reflected in image data, audio data, and temperature data during a certain monitoring period, and the time interval between the occurrence of these differences is less than a preset time interval, an alarm is immediately issued to the user. The preset time interval can be flexibly set according to specific circumstances, such as not less than 5 seconds. In practical applications, when an explosion occurs, anomalies will be reflected in image data, temperature data, and audio data. Therefore, when differences are simultaneously reflected in image data, audio data, and temperature data, regardless of whether an explosion has occurred, attention is required. To avoid unnecessary misjudgments, this embodiment specifically limits the time points when differences appear in the three types of data to minimize misjudgments and improve the reliability of the analysis.

[0067] In this embodiment, the discrepancy specifically refers to the inconsistencies between environmental data and safety data. The comparison is performed by comparing data within a specific time period with safety data within a safe time period, rather than comparing data moment-by-moment. This is because some home appliances change during normal operation; the most obvious example is indicator lights on home appliances, which may exhibit changing effects. Therefore, the safety data in this embodiment is environmental data within a safe time period, not just environmental data within a single moment.

[0068] The instruction set corresponds to the differences caused by user instructions, and the construction information corresponds to the unavoidable environmental impacts. Differences caused by other factors besides these two types of factors may also have an adverse effect on the home environment.

[0069] Specifically, if the analysis results show that the difference is not caused by user instructions or the construction environment, then the difference needs to be taken seriously and is judged as an abnormal difference. When the difference is reflected in image data, facial recognition is performed through the cloud platform. Facial recognition can determine whether someone is involved in the difference and whether they are a stranger. If a stranger is present in the difference, an alarm is issued to the user. When the difference is reflected in audio data, sound recognition is performed through the cloud platform, and an alarm is issued to the user if a preset danger sound is present in the difference. When the difference is reflected in temperature data, the cloud platform determines whether the temperature corresponding to the difference exceeds a preset temperature, and an alarm is issued to the user if it does. The preset temperature should also be set according to the actual situation.

[0070] Preferably, the home environment monitoring method of this embodiment compares environmental data and safety data using a deep neural network model to identify and analyze the differences. The differences and their corresponding analysis results are used as training data to train the deep neural network model. The dataset is divided into mini-batches, and an optimizer is used to train the model on each mini-batch. During training, a validation set can be used to adjust the model parameters to improve the model's generalization ability. A suitable loss function is selected to measure the difference between the model's predictions and the true values. The loss function should reflect the model's prediction error and should be easy to calculate.

[0071] For home appliances that may change during safe periods, the home environment monitoring method in this embodiment defines change areas and corresponding patterns to monitor such changes and reduce misjudgments. Specifically, in the safety data, areas that change during safe periods are selected as change areas, and the patterns of change in these areas during the safe periods are recorded. If the changes in the environmental data during the monitoring period do not conform to this pattern, it is considered a discrepancy. For example, in image data, the indicator lights of a smart router may change. By analyzing the patterns of change areas, misjudgments about the router can be reduced.

[0072] This embodiment provides a cloud-based home environment monitoring method. This method enables the cloud platform to monitor the home environment using home devices with monitoring capabilities, and to take corresponding response mechanisms upon detecting anomalies to ensure the normal operation of the smart home environment. Based on the stability of the home environment, real-time monitoring ensures the normal operation of devices. It analyzes potential anomalies, combining external environmental factors and user-related factors, to ensure that anomalies occurring in the home environment can be accurately and reasonably resolved.

[0073] Example 2

[0074] Embodiment 2 of this invention discloses a cloud-based home environment monitoring system, which can implement the cloud-based home environment monitoring method of Embodiment 1. The system's module diagram is shown in the attached specification. Figure 2 As shown, the specific solution is as follows:

[0075] A cloud-based home environment monitoring system includes the following:

[0076] Communication unit 1 is used to establish a communication mechanism between the cloud platform and home devices in a smart home environment;

[0077] The filtering unit 2 is used to filter out home appliances that can record environmental data and use them as the first appliances. The environmental data includes image data, audio data and temperature data.

[0078] Safety data unit 3 is used to set the safe time period of the home environment and acquire safety data, including safety images, safety audio and safety temperature, recorded by each first device during the safe time period;

[0079] External Factors Unit 4 is used to record the user's set of instructions about home appliances in real time through the cloud platform, and to combine user input and real-time updated construction information of the surrounding home environment captured from the Internet;

[0080] The difference comparison unit 5 is used to obtain environmental data recorded by each first device in each monitoring period through the cloud platform, and compare whether there are differences between the image data and the safety image, the audio data and the safety audio, and the temperature data and the safety temperature in each monitoring period.

[0081] The difference analysis unit 6 is used to classify the differences according to four categories of change attributes: color, temperature, sound, and brightness when there are differences in a certain period of time. Based on the change attributes, it analyzes whether the differences are caused by user commands in combination with the instruction set, and analyzes whether the differences are caused by the construction environment in combination with construction information.

[0082] Sending unit 7 is used to send the analysis results, along with the environmental data corresponding to the differences in the regulatory period, to the user.

[0083] This embodiment provides a cloud-based home environment monitoring system, which can realize the cloud-based home environment monitoring method of Embodiment 1, making it more practical.

[0084] This invention proposes a cloud-based method and system for monitoring the home environment. It combines a cloud platform with home appliances equipped with monitoring functions to achieve intelligent monitoring of the home environment and implements corresponding response mechanisms upon detecting anomalies, ensuring the normal operation of the smart home environment. Based on the stability of the home environment, it monitors the home environment in real time to ensure the normal operation of the devices. It analyzes potential anomalies, combining external environmental factors and user-related factors, to ensure that anomalies occurring in the home environment can be accurately and reasonably resolved.

[0085] Those skilled in the art will understand that the accompanying drawings are merely schematic diagrams of a preferred embodiment, and the modules or processes shown in the drawings are not necessarily essential for implementing the present invention. Those skilled in the art will understand that the modules in the apparatus of the embodiment can be distributed within the apparatus of the embodiment as described, or can be located in one or more apparatuses different from this embodiment, with corresponding changes. The modules of the above-described embodiment can be combined into one module, or further divided into multiple sub-modules. The above-described serial numbers are for descriptive purposes only and do not represent the superiority or inferiority of the embodiment. The above disclosures are only a few specific embodiments of the present invention; however, the present invention is not limited thereto, and any variations conceived by those skilled in the art should fall within the protection scope of the present invention.

Claims

1. A method for monitoring home environment based on a cloud platform, characterized in that, Including the following: In a smart home environment, a communication mechanism is established between the cloud platform and home devices; Home appliances that can record environmental data are selected and designated as the first device. The environmental data includes image data, audio data, and temperature data. The first device includes a smart camera that can capture image and audio data, a smart light bulb that can measure temperature data, a smart air conditioner that can measure temperature data, and a smart mirror that can capture image data. Set a safe time period for the home environment, and acquire safety data, including safe images, safe audio, and safe temperature, recorded by each of the first devices during the safe time period; The cloud platform records users' commands about home appliances in real time, and combines user input with real-time updates of construction information about the surrounding home environment retrieved from the Internet. The cloud platform acquires environmental data recorded by each of the first devices during each monitoring period, and compares the image data with the safety image, the audio data with the safety audio, and the temperature data with the safety temperature during each monitoring period to see if there are any differences. If a difference is simultaneously reflected in the image data, audio data, and temperature data during a certain monitoring period, and the time interval between the occurrence of the difference in the image data, audio data, and temperature data is less than a preset time interval, an alarm is immediately issued to the user. When there are differences in a certain period of time, the differences are classified into four categories of change attributes: color, temperature, sound, and brightness. Based on the change attributes, the analysis is combined with the instruction set to determine whether the differences are caused by user instructions, and combined with the construction information to determine whether the differences are caused by the construction environment. The analysis results, along with the environmental data corresponding to the differences in the regulatory period, will be sent to the user.

2. The home environment monitoring method according to claim 1, characterized in that, Based on the differences in the change attributes and the region where they are located, home appliances that can cause changes in these change attributes are selected and used as secondary appliances. The relevant instructions for the second device are found in the instruction set, the causal relationship between the relevant instructions and the difference is analyzed, and then it is determined whether the difference is caused by the user instruction.

3. The home environment monitoring method according to claim 1, characterized in that, When the variation in the attribute of the difference is classified as sound, abnormal audio is extracted from the audio data. When the monitoring period of the discrepancy falls within the construction time recorded in the construction information, the abnormal audio is compared with a preset noise database to determine if the same type of sound exists. If it exists, then the difference is determined to be caused by the external environment; If not, the environmental data and abnormal audio for that monitoring period will be sent to the user for confirmation.

4. The home environment monitoring method according to claim 1, characterized in that, If the analysis results show that the difference is not caused by user instructions or the construction environment, the difference is judged as an abnormal difference. When discrepancies are reflected in image data, facial recognition is performed through the cloud platform, and an alert is issued to the user if a stranger is found among the discrepancies. When the difference is reflected in the audio data, the cloud platform performs sound recognition and issues an alarm to the user if a preset danger sound is present in the difference. When the difference is reflected in the temperature data, the cloud platform determines whether the temperature corresponding to the difference exceeds the preset temperature, and issues an alarm to the user if it does.

5. The home environment monitoring method according to claim 1, characterized in that, The deep neural network model is used to compare environmental data and safety data to identify any discrepancies, and these discrepancies are categorized and analyzed. The discrepancies and their corresponding analytical results are then used as training data to train the deep neural network model.

6. The home environment monitoring method according to claim 1, characterized in that, The first device includes a smart camera capable of capturing image and audio data, a smart light bulb capable of measuring temperature data, a smart air conditioner capable of measuring temperature data, and a smart mirror capable of capturing image data.

7. The home environment monitoring method according to claim 1, characterized in that, In the aforementioned safety data, regions that change during the safety period are selected as the change regions, and the patterns of change in these regions during the safety period are recorded. If the changes in environmental data within the monitored area do not conform to this pattern, then it is considered a discrepancy.

8. The home environment monitoring method according to claim 1, characterized in that, The duration of the monitoring period is an integer multiple of the duration of the safety period.

9. A cloud-based home environment monitoring system, characterized in that, Including the following: A communication unit is used to establish a communication mechanism between the cloud platform and home devices in a smart home environment. A filtering unit is used to filter out home appliances that can record environmental data and designate them as first devices. The environmental data includes image data, audio data, and temperature data. The first devices include a smart camera that can capture image data and audio data, a smart light bulb that can measure temperature data, a smart air conditioner that can measure temperature data, and a smart mirror that can capture image data. The safety data unit is used to set a safe period for the home environment and acquire safety data, including safety images, safety audio, and safety temperature, recorded by each of the first devices during the safe period. The external factors unit is used to record the user's set of instructions about home appliances in real time through the cloud platform, and to integrate user input and real-time updated construction information of the surrounding home environment captured from the Internet; The difference comparison unit is used to obtain environmental data recorded by each of the first devices in each monitoring period through the cloud platform, and compare whether there are differences between the image data and the safety image, the audio data and the safety audio, and the temperature data and the safety temperature in each monitoring period; when the difference in a certain monitoring period is simultaneously reflected in the image data, audio data and temperature data, and the time interval between the occurrence of the difference in the image data, audio data and temperature data is less than a preset time interval, an alarm is immediately issued to the user. The difference analysis unit is used to classify differences according to four categories of change attributes: color, temperature, sound, and brightness when differences exist in a certain period of time. Based on the change attributes, it analyzes whether the differences are caused by user commands in combination with the instruction set, and analyzes whether the differences are caused by the construction environment in combination with the construction information. The sending unit is used to send the analysis results, along with the environmental data corresponding to the differences in the regulatory period, to the user.

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