Food odor detection method and food online sales method

Abstract

This disclosure relates to a method for detecting food odors and a method for online food sales. It involves collecting odor data that characterizes the odor features of food; obtaining odor analysis results from analyzing the odor data; and outputting the odor analysis results. Thus, even people with impaired olfactory function or online users can perceive the odor of food.

Description

Technical Field

[0001] The present disclosure relates to the technical field of gas sensors, and in particular to a method for detecting food odor and a method for online food sales. Background Art

[0002] Some people (such as the elderly or patients) have impaired or even absent sense of smell, which leads to insensitivity to smells. Such people cannot distinguish the smell of food when eating, and the food tastes bland.

[0003] When users buy food online (such as ordering takeout), they can only learn about the food through pictures posted by the merchant or reviews from other users, but cannot obtain information about the actual smell of the food.

[0004] Therefore, a solution is needed that enables users to know the smell of food. Summary of the invention

[0005] A technical problem to be solved by the present disclosure is to provide a solution that enables a user to know the smell of food.

[0006] According to a first aspect of the present disclosure, a method for detecting food odor is provided, comprising: collecting odor data capable of characterizing odor characteristics of food; acquiring an odor analysis result obtained by analyzing the odor data; and outputting the odor analysis result.

[0007] Optionally, the odor analysis results are used to characterize the type and / or odor of the food.

[0008] Optionally, the step of outputting the odor analysis result includes: outputting the odor analysis result and the description information of the food in association.

[0009] Optionally, the step of obtaining an odor analysis result obtained by analyzing the odor data includes: analyzing the odor data locally to obtain the odor analysis result; or sending the odor data to a server, and obtaining from the server the odor analysis result obtained by analyzing the odor data by the server.

[0010] Optionally, the step of collecting odor data that can characterize the odor characteristics of the object to be detected includes: setting a first scanning temperature or a scanning temperature range corresponding to the gas sensor based on environmental information; generating multiple second scanning temperatures through the first scanning temperature, the first scanning temperature and the multiple second scanning temperatures form multiple scanning temperatures, or generating multiple scanning temperatures through the scanning temperature range; forming a temperature adjustment model based on the multiple scanning temperatures, adjusting the active material in the gas sensor to the corresponding scanning temperature based on the temperature adjustment model, and collecting the response signal of the gas sensor at different scanning temperatures.

[0011] According to a second aspect of the present disclosure, a method for online food sales is provided, comprising: obtaining odor data that can characterize the odor characteristics of food produced by a merchant; obtaining an odor analysis result obtained by analyzing the odor data; and in response to a user's operation on a food displayed by an online merchant through a client, sending the odor analysis result of the food selected by the user to the client.

[0012] Optionally, the step of acquiring odor data that can characterize the odor characteristics of food produced by the merchant includes: using a gas sensor in a terminal device used by a user who purchased the food to collect odor data that can characterize the odor characteristics of the food produced by the merchant.

[0013] According to a third aspect of the present disclosure, a method for detecting food odor is provided, comprising: acquiring odor data capable of characterizing odor characteristics of food; acquiring odor analysis results obtained by analyzing the odor data; and outputting the odor analysis results.

[0014] According to a fourth aspect of the present disclosure, a computing device is provided, comprising: a processor; and a memory on which executable code is stored, and when the executable code is executed by the processor, the processor executes the method described in the second aspect or the third aspect above.

[0015] According to a fifth aspect of the present disclosure, a computer program product is provided, comprising an executable code, which, when executed by a processor of an electronic device, causes the processor to execute the method described in the second or third aspect above.

[0016] According to a sixth aspect of the present disclosure, a non-temporary machine-readable storage medium is provided, on which executable code is stored. When the executable code is executed by a processor of an electronic device, the processor executes the method described in the second or third aspect above.

[0017] Therefore, the present invention collects odor data that can characterize the odor characteristics of food, obtains odor analysis results obtained by analyzing the odor data, and outputs the odor analysis results, so that people with diminished olfactory function or online users can also know the smell of food. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] The above and other objects, features and advantages of the present disclosure will become more apparent through a more detailed description of exemplary embodiments of the present disclosure in conjunction with the accompanying drawings, wherein like reference numerals generally represent like components in the exemplary embodiments of the present disclosure.

[0019] Figure 1 A schematic flow chart of a food odor detection method according to an embodiment of the present disclosure is shown.

[0020] Figure 2 Schematic diagram showing odor data for several different types of analytes exposed to different MOS active materials.

[0021] Figure 3 A schematic diagram of a data collection process according to an embodiment of the present disclosure is shown.

[0022] Figure 4 A schematic diagram of the structure of a computing device according to an embodiment of the present disclosure is shown. DETAILED DESCRIPTION

[0023] The preferred embodiments of the present disclosure will be described in more detail below with reference to the accompanying drawings. Although the preferred embodiments of the present disclosure are shown in the accompanying drawings, it should be understood that the present disclosure can be implemented in various forms and should not be limited by the embodiments described herein. On the contrary, these embodiments are provided to make the present disclosure more thorough and complete, and to fully convey the scope of the present disclosure to those skilled in the art.

[0024] For scenarios where users are unable to detect the smell of food due to a decline in their sense of smell or other reasons (such as online purchases), the present disclosure proposes that food can be actively detected for odor and the detection results can be sent to users in a way that they can understand, so that people with a decline in their sense of smell or online users can also know the smell of food.

[0025] Figure 1 A schematic flow chart of a food odor detection method according to an embodiment of the present disclosure is shown. Figure 1 The method shown can be performed by an electronic nose (also known as an artificial olfactory system) or by an electronic device with integrated electronic nose function (such as a portable electronic device such as a smart phone or a smart watch).

[0026] like Figure 1 As shown, in step S110, odor data capable of representing the odor characteristics of food is collected.

[0027] One or more gas sensors may be arranged in the space where the food is located, and the gas sensors may be used to collect odor data by exposing the odor of the food to the gas sensors.

[0028] In the present disclosure, odor may refer to any gaseous or vaporized compound or volatile, which are gas-phase molecules that can diffuse in the air and can be sensed by biological or artificial sensors.

[0029] A gas sensor is a sensor that converts the physical or chemical quantity changes caused by the physical or chemical reaction between the detected gas molecules and the gas-sensitive material (i.e., the active sensing material described below) into effectively measurable electrical signals, optical signals, acoustic signals, etc., thereby measuring the type and concentration of the gas.

[0030] In step S120, an odor analysis result obtained by analyzing the odor data is obtained.

[0031] The odor data may be analyzed locally to obtain an odor analysis result, or the odor data may be sent to a server to obtain an odor analysis result obtained by analyzing the odor data from the server.

[0032] When analyzing the odor data, the odor data can be compared with the standard odor data of the analyte whose identity and concentration are known in the database to obtain the odor analysis result. The odor analysis result can characterize the type and / or odor of the food. The odor mentioned here can refer to the type of gas and its concentration, or it can be the food odor evaluation information determined according to the type of gas and its concentration, such as the fragrance degree, pungent degree, freshness, etc.

[0033] In step S130, the odor analysis result is output.

[0034] The output method of the odor analysis result may include but is not limited to text, image, and audio. The odor analysis result and the description information of the food may be output in association. The description information of the food may refer to the description information in the form of image, audio, or text. For example, a picture of food may be displayed on the screen of an electronic device, and the smell of the food may be announced by voice broadcast. After the user (a person with reduced sense of smell) knows the smell of the food, he or she may associate the corresponding scene to increase appetite.

[0035] As an example, an odor simulator can be used to output the same odor as the detected odor analysis result, so that users (such as online users) can smell the food without touching the food. The odor simulator is set on the user side. The odor simulator can contain multiple odor element substances. According to the odor analysis result, the odor simulator can be controlled to simulate a mixed gas with the same odor as the food on the user side.

[0036] Data collection process of step S110

[0037] In order to collect enough data based on limited sensing materials, the temperature scanning method can be used for collection.

[0038] The temperature scanning method refers to setting the gas sensor (ie, the active sensing material in the gas sensor) at a series of temperature values ​​within a certain temperature range and maintaining them for a certain period of time to collect a set of response signals corresponding to different temperature values.

[0039] The gas sensor used in the temperature scanning method is sensitive to temperature (i.e., has different responses at different temperatures), such as a metal oxide semiconductor (MOS) sensor using metal oxide as an active sensing material. The active sensing material (i.e., metal oxide) of the gas sensor can be selected from any one or more of the following combinations: SnO2, V2O5, WO3, ZnO, TeO2, TiO2, CuO, CeO2, Al2O3, ZrO2, V2O3, Fe2O3, Mo2O3, Nd2O3, La2O3, Nb2O5, Ta2O5, In2O3, GeO2, ITO. Active sensing material can also be called active material.

[0040] The active sensing material of the gas sensor can be a metal oxide heterostructure. A metal oxide heterostructure is a metal oxide as the main material, with a second phase material added to form a heterojunction at the physical interface between the two different materials, and the gas sensing performance of the metal oxide is effectively improved by utilizing the synergistic effect between different components.

[0041] According to the type of the second phase material, metal oxide heterostructures can be divided into metal-metal oxide heterostructures, metal oxide composite structures and functional material composite structures.

[0042] The second phase material in the metal-metal oxide heterostructure is generally located on the surface of the main material of the metal oxide in the form of metal nanoparticles, including metal oxides doped with noble metals (such as Au, Ag, Pt, Pd, etc.) and metal oxides doped with transition metals (such as Cu, Ni, Co, etc.). The sensitization mechanism of noble metal-doped metal oxide gas-sensitive materials (depending on whether the work function of the main metal oxide is changed) is divided into chemical sensitization effect and electronic sensitization effect. Transition metal doping is to introduce impurity ions into the lattice of oxide semiconductors, change the original crystal parameters and introduce impurity energy levels, and at the same time, it can also produce a large number of surface defects to increase the activity of the oxide surface, which is conducive to the adsorption or reaction of the target gas.

[0043] Metal oxide composite structure refers to the composite of different types of metal oxide semiconductor materials to form a heterogeneous structure at the interface. Due to the different Fermi levels of different semiconductor materials, carriers will migrate at the interface to form a space charge layer, causing the energy band bending of the semiconductor. At the same time, the surface of the metal oxide will also undergo certain changes, such as the generation of surface defects and active sites. The synergistic effect between different metal oxides can promote the reaction between the target gas and the adsorbed oxygen ions on the surface of the metal oxide, thereby improving the gas sensing performance of the composite metal oxide.

[0044] Functional material composite structure refers to the composite of metal oxide semiconductor materials with graphene, carbon nanotubes, conductive polymers, porous silicon and other functional materials, which helps to improve its electrical conductivity and gas adsorption capacity, and can effectively reduce the operating temperature of the sensor while enhancing the sensitive properties of the semiconductor material.

[0045] The active sensing material of the gas sensor can also be a light-assisted gas-sensitive material. Light-assisted gas-sensitive materials refer to the addition of external light sources to stimulate gas-sensitive materials (metal oxides). When the energy of the light source is greater than or equal to the band gap of the metal oxide, the photogenerated electron-hole pairs generated by illumination can effectively improve the conductivity of the material. Studies have shown that light excitation can not only improve the sensitivity of the sensing material, but also significantly improve the response-recovery speed. By further exploring the mechanism of light-excited gas-sensitive materials, it is proved that the improvement of the gas-sensitive performance of the material under illumination is attributed to the enhanced activity of oxygen anions on the surface of the material under illumination and the reduction of the activation energy of the gas-sensitive reaction after illumination. However, light-assisted sensing also means that the sensor needs to integrate light source components and additional energy input, which also has certain limitations in practical applications.

[0046] A gas sensor can be a sensor unit, i.e. a sensor pixel, in a sensor array. In general, a sensor is a device comprising a sensing unit (e.g. a sensor array) and a control circuit or an electronic processing unit (processor). A sensor array refers to a sensing unit having different sensing elements or pixels in a single substrate or a single device. A sensor pixel refers to an element of a sensor or a sensor array. Since a sensor pixel is the basic element of a sensor, the terms "sensor" and "sensor pixel" are interchangeable, and their exact meaning depends on the context.

[0047] The temperature scanning method can be used to generate odor data that can characterize the odor characteristics of analytes with known identities and concentrations, and store them in a standard database. The temperature scanning method can also be used to generate odor data that can characterize the odor characteristics of analytes with unknown identities or concentrations, and compare the odor data with the odor data in the standard database to identify the identity or concentration of the analyte.

[0048] Analyte refers to any molecule, compound, substance, reagent, material, etc. that is sought to be detected. On the one hand, the analyte may be capable of being detected by a gas sensor. On the other hand, the analyte can react with the active material of the gas sensor, thereby producing a detectable change in the active material. In some cases, the "analyte" may be present in a gas phase environment. Non-limiting examples may include gases, inorganic molecules in the air, organic molecules in the air, volatile organic compounds, particulate matter in the air, smoke, gasified or vaporized solids or liquids, etc., and also include combinations thereof.

[0049] The response signal is the measurable response of the sensing element or MOS pixel in the sensor, including changes in electrical properties (resistance or impedance). It is an analog signal that can be converted and recorded in digital form. The unit of the response signal is usually the ratio of resistance (R). For example, Rg / Ra, where "R" is the resistance of the active material at a given temperature; "Rg" represents the resistance of the sensor when exposed to the target gas (such as VOC); and "Ra" is the resistance of the sensor pixel when exposed to air (as baseline information). Depending on the MOS material type (N-type or P-type), Ra / Rg can also be used.

[0050] Odor data refers to data that can reflect the odor characteristics of food. One or more gas sensors of different active materials can be exposed to the same food, and one or more groups of response signals obtained by temperature scanning method can be used as odor data. Data after further processing of the one or more groups of response signals can also be used as odor data. For example, odor data can refer to Figure 2 The data shown are in the form of one or more curves with at least one peak, wherein different groups of response signals are obtained by performing temperature scanning on gas sensors made of different active materials.

[0051] Figure 2 Schematic diagram showing odor data for several different types of analytes exposed to different MOS active materials.

[0052] Figure 2 Four MOS active materials are shown, namely, indium oxide (In2O3), tin dioxide (SnO2), zinc oxide (ZnO) and tungsten oxide (WO3), wherein each of the four MOS active materials can be included in a gas sensor, such as in different sensor cells in a MOS sensor array.

[0053] Four sensors each containing one of the four MOS active materials can be exposed to seven different foods, and then each MOS active material is controlled to be temperature scanned in the range of 200°C-400°C to generate four sets of response signals. These four sets of response signals are then combined into Figure 2 The data format displayed in .

[0054] It can be seen that the seven different foods react differently with the four different MOS active materials. For example, the seven different foods reacted not violently with the active material ZnO, and the odor data curves of the seven different foods were not very different from each other. On the contrary, the seven different foods reacted violently with the active material SnO2, and the odor data curves of different foods were completely different.

[0055] Therefore, it can be inferred that SnO2 is a better MOS active material for the foods shown in the figure than ZnO. Moreover, the odor data curve formed by a set of response signals obtained by temperature scanning for each food has at least one peak shape and / or an overall curve over the entire temperature range. The peak shape or curve of each unique food is unique. Therefore, a database or standard database can be established to identify food. The standard database can be stored in a memory associated with the MOS sensor, or in a remote memory, such as in the cloud, and accessed by a component associated with the MOS sensor. In practice, the MOS sensor pixels can be exposed to the food, and then the MOS sensor pixels scan a series of predetermined temperatures to generate response signals. The response signals are then combined into odor data that can characterize the odor characteristics of the food, such as the data form depicted in the figure. The odor data is then compared with the standard database to determine the identity and concentration of the food.

[0056] In some embodiments, the peak shape or curve of each specific MOS active material can be considered in combination with the peak shape or curve produced by one or more other MOS active materials in the same or different temperature range. This combination can generate an overall feature or curve that can be compared with the same combination in a standard database. In some embodiments, such processing can provide higher analysis accuracy, sensitivity or complexity.

[0057] In the existing temperature scanning method, the temperature range and specific scanning temperature used for temperature scanning are pre-set fixed values, and the changes in environmental conditions and the active sensing materials of the gas sensor are not taken into account at the beginning of the setting. In other words, the setting of the temperature range and scanning temperature has nothing to do with the environmental conditions and the active sensing materials of the gas sensor.

[0058] If the changes in environmental conditions and the active sensing materials of the gas sensor are not taken into account, in all environmental conditions, for gas sensors with different active sensing materials, the series of scanning temperatures (or the temperature range formed by a series of scanning temperatures) used to perform the temperature scanning method are the same and fixed. Then, due to the influence of environmental conditions on the gas sensor, the response signal obtained by the temperature scanning method will be different from the response signal collected under the standard environment, which will require the collected data to be calibrated to eliminate the influence of the environment on the gas sensor readings and ensure the availability of the data, which will inevitably increase unnecessary performance consumption.

[0059] In addition, due to the influence of the environment on the gas sensor readings, if the same scanning temperature range is used for temperature scanning in different environments, the resulting set of response signals may not be representative and is not suitable as odor data or odor fingerprints. Figure 2Under the environmental conditions shown, for a gas sensor whose active material is SnO2, the scanning temperature range that can form the most representative (i.e., the most identifiable or distinguishing) response signal is 200°C-400°C. If the environmental conditions change and the scanning is still performed in the range of 200°C-400°C, the resulting response signal may no longer be representative, that is, the resulting response signal is no longer suitable for use as odor data or odor fingerprint.

[0060] In order to improve the accuracy and availability of the collected data from the source, the present disclosure proposes a data collection scheme based on a conditional temperature scanning method. The present disclosure proposes that multiple scanning temperatures corresponding to the gas sensor can be set based on environmental information; the response signal of the gas sensor at each scanning temperature is collected to obtain a group of response signals; based on one or more groups of response signals, odor data that can characterize the odor characteristics of the food is obtained.

[0061] Setting multiple scanning temperatures corresponding to the gas sensor based on environmental information means that multiple scanning temperatures can be set for the gas sensor according to the influence of the environmental information at the time of collection (i.e., current environmental information) on the gas sensor reading (i.e., response signal), so that the reading of the gas sensor at the set scanning temperature can eliminate the environmental influence or compensate for the environmental influence.

[0062] The sensing of the gas sensor will be affected by environmental conditions such as humidity, pressure, temperature, air pressure, air flow speed, light, time, etc. The existing solution is to calibrate the sensor readings according to these environmental conditions. In order to save the calibration process, the technical concept of the present disclosure is to use these environmental conditions (i.e., environmental information) before the gas sensor collects data. That is, before collecting data, a series of temperature points (i.e., scanning temperatures) for temperature scanning are set according to these environmental conditions.

[0063] In other words, the present disclosure is to control the operation of the gas sensor according to the environmental conditions, rather than to correct the operation results.

[0064] By setting multiple scanning temperatures corresponding to the gas sensor based on environmental information, the impact of environmental changes on the gas sensor can be weakened or even eliminated from the source, so that in an ideal situation the collected data can be directly used for odor analysis or stored as standard odor data without the need to calibrate the collected data (or only require simple calibration).

[0065] The present disclosure enables the raw data collected by the gas sensor to accurately characterize the odor characteristics of food, and the improvement in its performance makes the concept of electronic nose a reality.

[0066] The present disclosure can set the scanning temperature based on environmental information to solve the drift problem.

[0067] The present disclosure may also set the scanning temperature based on environmental information to collect a representative set of response signals, so that the set of response signals is suitable as odor data or odor fingerprints.

[0068] Embodiment 1: Setting multiple scanning temperatures based on environmental information to solve the drift problem

[0069] When multiple scanning temperatures corresponding to the gas sensor are set based on environmental information, a reference environmental information can be pre-set, and then the scanning temperature can be set based on the difference between the current environmental information and the reference environmental information, and the effect on the reading (i.e., the response signal) of the gas sensor, so that the response signal obtained by performing temperature scanning based on the set scanning temperature is a reading after eliminating or substantially eliminating the effect. Taking the reference environmental information including temperature and humidity as an example, the reference environmental information can be a temperature (ambient temperature) of 25°C and a humidity (ambient humidity) of 50%.

[0070] The inventors of the present disclosure discovered during the use of the temperature scanning method that changes in environmental conditions (especially humidity) can cause a drift in the scanning temperature corresponding to the peak value of a response signal in a set of response signals obtained by temperature scanning, that is, Figure 2 The shift in the peak position in the curve shown.

[0071] To this end, the present disclosure proposes that when setting multiple scanning temperatures corresponding to the gas sensor based on environmental information, the first scanning temperature can be set based on the drift of the scanning temperature corresponding to the peak value of the response signal of the gas sensor caused by the difference between the current environmental information and the reference environmental information, and the reference starting scanning temperature. The difference between the reference starting scanning temperature and the first scanning temperature is equal to or substantially equal to the drift, and the reference starting scanning temperature is the starting scanning temperature of the gas sensor under the reference environmental information. Then, the first scanning temperature is used as the starting scanning temperature, and multiple second scanning temperatures are set. The multiple scanning temperatures finally set include the first scanning temperature and multiple second scanning temperatures.

[0072] For example, taking 50% humidity as the benchmark, the scanning starting point (i.e., the benchmark starting scanning temperature) is 200°C. If every 10% increase in humidity above the benchmark humidity causes the peak position to drift (drift to the right) by 5°C, then when the current acquisition environment is 60% humidity, compared with the benchmark humidity, an increase of 20% in humidity will cause a 10°C peak position drift. At this time, based on the benchmark starting scanning temperature, the peak position can be moved 10°C in the direction of the drift, that is, the scanning starting point can be set to 210°C.

[0073] The range of the temperature scanning interval formed by the first scanning temperature and the plurality of second scanning temperatures may be the same or substantially the same as the preset temperature scanning range. The preset temperature scanning range may refer to a predefined temperature range, such as a temperature range of 200°C-400°C.

[0074] The number of the second scanning temperatures may also be the same as or substantially the same as a preset number. The preset number may also be a predefined value. It should be noted that, in theory, the larger the preset number, the more data obtained by the temperature scanning, the better the scanning performance, but the more time-consuming the scanning. Therefore, the number of the second scanning temperatures may be set according to actual conditions.

[0075] The present disclosure proposes that a first scanning temperature interval can also be set based on the drift of the scanning temperature corresponding to the peak value of the response signal of the gas sensor caused by the difference between the current environmental information and the reference environmental information, and the reference scanning temperature interval of the gas sensor under the reference environmental information, the temperature range of the first scanning temperature interval is equal to or substantially equal to the temperature range of the reference scanning temperature interval, and the difference between the starting temperature value of the first scanning temperature interval and the starting temperature value of the reference scanning temperature interval is equal to or substantially equal to the drift amount. Based on the first scanning temperature interval, multiple scanning temperatures are generated. For example, multiple scanning temperatures can be generated (such as randomly generated) within the temperature range represented by the first scanning temperature interval.

[0076] For example, taking 50% humidity as the benchmark, the benchmark scanning temperature range corresponding to the benchmark is 200℃-400℃. Every 10% increase in humidity above the benchmark humidity will cause the peak position to drift (drift to the right) by 5℃. When the current collection environment is 60% humidity, compared with the benchmark humidity, an increase of 20% in humidity will cause a 10℃ peak position drift. At this time, the scanning temperature range can be moved 10℃ in the direction of the peak position drift, and a new scanning temperature range of 210℃-410℃ can be obtained.

[0077] Embodiment 2: To obtain a set of representative response signals, multiple scanning temperatures are set based on environmental information

[0078] Based on the influence of current environmental information on the response signal of the gas sensor at different scanning temperatures, a second scanning temperature interval corresponding to the gas sensor can be set so that the response signal of the gas sensor at different scanning temperatures in the second scanning temperature interval is a set of representative response signals.

[0079] The "representativeness" mentioned here refers to a set of response signals collected by the gas sensor at different scanning temperatures in the second scanning temperature range, which have distinction or recognition in terms of value, rather than a series of response signals with very small numerical differences and no recognition or poor recognition. Whether a set of response signals is representative can be determined based on the distribution of the numerical values ​​of the set of response signals. For example, a representative set of response signals may refer to a set of response signals whose difference between the maximum value and the minimum value of the response signal is greater than a predetermined threshold.

[0080] The second scanning temperature interval may be regarded as a scanning temperature interval determined based on the current environmental information and capable of forming a group of representative response signals.

[0081] Based on the second scanning temperature interval, multiple scanning temperatures required for use in the temperature scanning process can be generated. For example, multiple scanning temperatures can be generated (such as randomly generated) within the second scanning temperature interval. The multiple scanning temperatures can be increased step by step, decreased step by step, or randomly selected. Therefore, during the temperature scanning process, the temperature can be raised step by step or heated to the highest temperature and then lowered step by step. It can also be randomly selected, or the starting scanning temperature can be determined based on the second scanning temperature interval, and then the subsequent scanning temperatures can be determined sequentially around the starting scanning temperature.

[0082] The scanning temperature (or scanning temperature range) in the prior art is predetermined, that is, the same temperature scanning strategy is executed under different environmental conditions. However, the actual situation is that different environmental conditions acting on the same scanning temperature (or scanning temperature range) will cause drift in the response signal of the odor fingerprint. If the sensor is heated to a predetermined temperature before calibrating the response signal value, it will cause energy / energy waste, and it is difficult to ensure that the most representative response signal (or response signal set) is quickly obtained within the predetermined scanning temperature (or scanning temperature range).

[0083] Humidity, as a kind of environmental information that can be obtained in environmental conditions, will cause response drift to the metal oxide sensor array, and the response drift can be compensated by an algorithm. In fact, other environmental information also has this characteristic. Based on this premise, if the scanning temperature range can be pre-calibrated based on environmental information, instead of compensating for the response drift after the temperature scan, the best scanning temperature starting point, subsequent scanning temperature points or scanning temperature range under the current environmental conditions can be dynamically obtained, saving performance consumption and improving scanning efficiency.

[0084] The difference between this embodiment and setting the scanning temperature to solve the drift problem (i.e., embodiment 1) is that this embodiment sets the scanning temperature range based on environmental information in order to efficiently obtain the scanning temperature range that is most conducive to identifying odor information under current environmental conditions, so as to facilitate obtaining the most representative response signal characteristic spectrum, improve the validity of the data, and subsequently use it for comparison with the odor database for rapid comparison, saving energy consumption and improving efficiency.

[0085] For example, the scanning temperature range set in the prior art is 200℃-500℃, and this scanning task is performed regardless of the conditions. However, based on the current environmental information, it can be known (through the processing of environmental information and some algorithms) that under such environmental conditions, the scanning temperature interval (i.e., the second scanning temperature interval) that can form the most representative response signal (or odor fingerprint) is 300℃-600℃, so the instruction to the sensor will be to perform a temperature scan in the temperature interval of 300℃-600℃. When the environmental information changes, the scanning temperature interval can be re-determined, such as the scanning temperature interval can be reset to 200℃-450℃.

[0086] The impact of environmental information on the gas sensor reading is not only related to the environmental information, but also to the type of target gas to be detected and the sensing material of the gas sensor. Therefore, the second scanning temperature range can be set based on these three factors: current environmental information, target gas type and sensing material of the gas sensor.

[0087] In other words, in addition to determining the scanning temperature based on environmental information, the target gas or sensor material may also be additionally combined. For example, in one application scenario, after the target gas type to be detected and / or the sensing material of the gas sensor to be used are predetermined, the optimal scanning temperature may be found in combination with the current environmental information.

[0088] In order to save energy and reduce the loss of gas sensors, the present disclosure can also obtain (real-time acquisition or periodic acquisition) current environmental information, and determine the update frequency of the scanning temperature based on the current environmental information. For example, the rate of change of environmental information at different times of the day is different. The rate of change of the current environmental information can be determined based on the time information in the current environmental information, and the update frequency of the scanning temperature can be determined accordingly. For another example, the rate of change of environmental information can also be predicted based on the current environmental information, such as the rate of change of environmental information can be comprehensively predicted based on factors such as temperature, humidity, air pressure, air flow speed, light, time, etc. in the current environment, and the update frequency of the scanning temperature can be determined based on the prediction results. For another example, a day can be divided into multiple time periods (such as day and night), and different scanning temperature update frequencies can be set for different time periods. The current time period can be determined based on the time information in the current environmental information, and the scanning temperature can be updated according to the scanning temperature update frequency corresponding to the current time period. That is, after determining the update frequency, multiple scanning temperatures can be reset according to the update frequency. The setting process of multiple scanning temperatures can refer to the relevant description above. When the scanning temperature is updated, data collection can be performed again according to the updated multiple scanning temperatures.

[0089] When determining multiple scanning temperatures, in order to avoid systematic errors that may occur when collecting data each time under predetermined temperature conditions, a random or conditional method can be used to generate a series of different second scanning temperatures. For example, the order between the generated multiple scanning temperatures can be set to at least one scanning temperature that is greater than two adjacent scanning temperatures, or less than two adjacent scanning temperatures, and / or at least some of the scanning temperatures in the multiple scanning temperatures are arranged in order of temperature value from small to large or from large to small.

[0090] When collecting the response signals of the gas sensor at various scanning temperatures, the active sensing material of the gas sensor may be heated to different scanning temperatures in sequence according to the order of the multiple scanning temperatures, and the response signals of the gas sensor at different scanning temperatures may be collected.

[0091] Taking the setting of the first scanning temperature first and then the second scanning temperature as an example, when setting multiple second scanning temperatures with the first scanning temperature as the starting scanning temperature, in order to avoid systematic errors that may occur when collecting data under predetermined temperature conditions each time, a random or conditional method can be used to generate a series of different second scanning temperatures. The generated multiple second scanning temperatures have a predetermined order, which can refer to the order in which the second scanning temperatures are generated, or can be the order in which the multiple second scanning temperatures are sorted using a certain arrangement method (such as a random arrangement method). The order between these multiple second scanning temperatures is set so that there is at least one second scanning temperature that is greater than the two adjacent scanning temperatures, or less than the two adjacent scanning temperatures. In other words, the second scanning temperatures are not arranged in a monotonically increasing or monotonically decreasing manner.

[0092] When collecting the response signals of the gas sensor at various scanning temperatures, the active sensing material of the gas sensor can be first heated to a first scanning temperature, and the response signal of the gas sensor at the first scanning temperature can be collected. Then, the active sensing material of the gas sensor can be heated to different second scanning temperatures in sequence and maintained for a predetermined period of time to collect the response signals of the gas sensor at different second scanning temperatures.

[0093] Since the order between the second scanning temperatures is not a monotonically increasing or monotonically decreasing order of temperature, when the temperature scan is performed in this order, compared with the temperature scan performed along a fixed temperature increasing or decreasing direction, the "directional" error caused by continuous heating or continuous cooling of the sensor can be reduced.

[0094] Furthermore, the intervals between adjacent scanning temperatures may also be non-fixed.

[0095] Figure 3 A schematic diagram of a data collection process according to an embodiment of the present disclosure is shown. Figure 3 The steps shown collect odor data that can characterize the odor characteristics of the food.

[0096] See also Figure 3 In step S310, a first scanning temperature or a scanning temperature interval corresponding to the gas sensor is set based on the environmental information. The first scanning temperature can be referred to the above related description, which will not be repeated here. The scanning temperature interval can be the first scanning temperature interval mentioned above, or the second scanning temperature interval mentioned above.

[0097] The specific implementation process of setting the first scanning temperature or the scanning temperature interval (the first scanning temperature interval or the second scanning temperature interval) based on the environmental information can be found in the above related description, which will not be repeated here.

[0098] In step S320, a plurality of second scanning temperatures are generated by the first scanning temperature, the first scanning temperature and the plurality of second scanning temperatures form a plurality of scanning temperatures, or a plurality of scanning temperatures are generated by a scanning temperature interval.

[0099] For the specific implementation process of generating multiple second scanning temperatures through the first scanning temperature, please refer to the relevant description above.

[0100] The scanning temperature interval may be the first scanning temperature interval mentioned above, or the second scanning temperature interval mentioned above. The process of generating multiple scanning temperatures through the first scanning temperature interval or the second scanning temperature interval may also refer to the relevant description above. It should be noted that the purpose of generating multiple scanning temperatures through the first scanning temperature interval is mainly to solve the drift problem, while the purpose of generating multiple scanning temperatures through the second scanning temperature interval is mainly to obtain a representative response signal.

[0101] In step S330, a temperature adjustment model is formed based on the multiple scanning temperatures, the active material in the gas sensor is adjusted to the corresponding scanning temperature based on the temperature adjustment model, and the response signal of the gas sensor at different scanning temperatures is collected.

[0102] The temperature adjustment model can be used to adjust the order between multiple scanning temperatures, so that the active materials (i.e., active sensing materials) in the gas sensor are sequentially adjusted to the corresponding scanning temperatures in the order indicated by the temperature adjustment model, and the response signals of the gas sensor at different scanning temperatures are collected to obtain a set of response signals corresponding to different scanning temperatures.

[0103] The temperature adjustment model can set the order between multiple scanning temperatures as follows: there is at least one scanning temperature such that the scanning temperature is greater than the two adjacent scanning temperatures, or less than the two adjacent scanning temperatures; and / or there are at least some scanning temperatures, which are arranged in order from small to large or from large to small in temperature value.

[0104] Usually, the scanning temperature is generated by the power supply supplying power to the sensor to make the sensor heat up. However, under different environmental conditions, when the same electrical parameters (such as power supply voltage) are applied to the sensor, the obtained temperature value will drift. At this time, it is necessary to adjust the electrical parameters (such as power supply voltage) so that the sensor can still be heated to the required scanning temperature under different environmental conditions. Therefore, the present disclosure can also set the electrical parameters used to generate the scanning temperature in the gas sensor based on environmental information. When the environmental information changes, the electrical parameters are adjusted so that the adjusted electrical parameters can still generate the desired scanning temperature when acting on the gas sensor. The electrical parameters may include, but are not limited to, a combination of one or more of voltage values, current values, resistance values, impedance values, capacitance values, and inductance values.

[0105] As an example, based on environmental conditions, a starting scanning temperature (i.e., the first scanning temperature mentioned above) can be reset for the starting temperature reference value (i.e., the reference starting scanning temperature mentioned above) to solve the peak drift problem during the temperature scanning process. Then, based on the set starting scanning temperature, the scanning temperature for subsequent temperature scanning (i.e., the plurality of second scanning temperatures mentioned above) can be generated according to the temperature scanning range definition (i.e., the size of the defined temperature scanning range) and an increase or decrease reference amount.

[0106] The reference amount for increase or decrease can be a coefficient group including multiple coefficients, and the coefficient group can include multiple randomly generated coefficients containing positive and negative numbers, such as 1.0, -0.9, 2.0, -1.5, ... 1.5. The number of coefficients in the coefficient group can be greater than, equal to, or less than the number of scanning points other than the starting scanning point (i.e., the number of second scanning temperatures). If the number of coefficients in the coefficient group is greater than the number of scanning points other than the starting scanning point, some coefficients can be randomly selected from them to participate in generating the scanning temperature. If the number of coefficients in the coefficient group is less than the number of scanning points other than the starting scanning point, coefficients can be repeatedly selected from them to participate in generating the scanning temperature.

[0107] When using the coefficients in the coefficient group to generate subsequent scanning temperatures based on the initial scanning temperature, an increment can be pre-set, which can be a fixed value (such as 10°C) or a variable. When generating the first scanning temperature, a coefficient can be randomly selected from the coefficient group, and the temperature value of the first scanning temperature can be equal to the initial scanning temperature + increment × the selected coefficient. When generating the second scanning temperature, a coefficient can be randomly selected from the coefficient group again, and the temperature value of the second scanning temperature can be equal to the first scanning temperature + increment × the selected coefficient. Similarly, the temperature value of the next scanning temperature can be equal to the previous scanning temperature + increment × the selected coefficient.

[0108] In summary, the data acquisition solution disclosed in the present invention can be regarded as a method based on conditional temperature scanning.

[0109] The existing temperature scanning scheme is to pre-set the scanning temperature. Unlike the existing scheme, the present disclosure does not pre-set the scanning temperature, but can set the scanning temperature based on any conditions during data collection. For example, the scanning temperature can be set based on natural environmental conditions, or based on artificial environmental conditions (such as artificially set algorithms).

[0110] The present disclosure also proposes a data acquisition scheme, including: providing a computing processor functionally coupled to a gas sensor; setting a computing program in the computing processor so that the computing processor receives or generates one or more parameters; setting multiple scanning temperatures corresponding to the gas sensor based on the parameters; and collecting the response signals of the gas sensor at each scanning temperature to obtain a set of response signals. The parameters can be randomly generated by computing processing or environmental information.

[0111] As an example, the starting scanning temperature may be set based on environmental information, and a plurality of scanning temperatures (ie, the second scanning temperatures mentioned above) after the starting scanning temperature may be generated based on randomly generated values ​​(such as the coefficient group mentioned above).

[0112] Based on the data acquisition scheme disclosed in the present invention, one or more gas sensors can be exposed to food for conditioned temperature scanning to obtain one or more groups of response signals. Based on this group or multiple groups of signals, odor data that can characterize the odor characteristics of the food can be obtained.

[0113] Odor data refers to data that can reflect the odor characteristics of food. One or more groups of response signals obtained by data collection using a conditioned temperature scanning method can be used as odor data. Data after further processing of the one or more groups of response signals can also be used as odor data. For example, odor data can refer to Figure 2 The data shown are in the form of one or more curves with at least one peak, wherein different groups of response signals are obtained by performing temperature scanning on gas sensors made of different active materials.

[0114] Application Scenario

[0115] In view of the scenario of online food sales (such as online meal ordering), the present disclosure proposes an online food sales method. The execution subject of the method may be a server for providing online meal ordering services, such as an online meal ordering platform.

[0116] The method may include the following steps.

[0117] Step S1, obtaining odor data that can characterize the odor characteristics of food produced by a merchant.

[0118] The gas sensor in the terminal device used by the user who purchased the food can be used to collect odor data that can characterize the odor characteristics of the food produced by the merchant. After the user receives the order, the gas sensor can be used to collect odor data that can characterize the odor characteristics of the food produced by the merchant. For the data collection principle of the gas sensor, please refer to the relevant description above. By collecting data on the user side, it is possible to avoid fraud by the merchant to a certain extent and ensure the fairness of the odor data collection.

[0119] Step S2: Obtain an odor analysis result obtained by analyzing the odor data.

[0120] The analysis operation can be performed on the data collection end or on the server end. If the analysis operation is performed on the server end, the data collection end needs to have a communication function to send the collected data to the server.

[0121] Step S3: in response to the user's operation on the food displayed by the online merchant through the client, the smell analysis result of the product selected by the user is sent to the client.

[0122] Step S3 may be performed when the user orders a meal. The client may refer to a meal ordering software installed on a terminal device.

[0123] When a user browses foods provided by a merchant in the food browsing interface (i.e., software interface) provided by the client, for the food selected by the user, the odor analysis results obtained by previously collecting and analyzing odor data of the food produced by the merchant can be sent to the client, so that the client can inform the user of the odor analysis results and enable the user to decide whether to place an order after understanding the odor of the food.

[0124] As an example, an odor simulator can be set up on the user side. With the help of the odor simulator, the user can output the same odor as the detected odor analysis result, so that the user can smell the odor of food without touching the food. Among them, the odor simulator can contain multiple odor element substances. According to the odor analysis result, the odor simulator can be controlled to simulate a mixed gas with the same odor as the food on the user side.

[0125] The present disclosure also proposes a method for detecting food odor. The method can be implemented as a computer program or a computer program product. The method includes: obtaining odor data that can characterize the odor characteristics of food; obtaining an odor analysis result obtained by analyzing the odor data; and outputting the odor analysis result. The odor data can be obtained from a gas sensor. For details of the method, please refer to the relevant description above, which will not be repeated here.

[0126] Figure 4 A schematic diagram of the structure of a computing device that can be used to implement the above-mentioned food odor detection method or food online sales method according to an embodiment of the present invention is shown.

[0127] See also Figure 4 , the computing device 400 includes a memory 410 and a processor 420 .

[0128] Processor 420 may be a multi-core processor or may include multiple processors. In some embodiments, processor 420 may include a general-purpose main processor and one or more special coprocessors, such as a graphics processing unit (GPU), a digital signal processor (DSP), etc. In some embodiments, processor 420 may be implemented using a customized circuit, such as an application-specific integrated circuit (ASIC) or a field programmable gate array (FPGA).

[0129] The memory 410 may include various types of storage units, such as system memory, read-only memory (ROM), and permanent storage devices. Among them, ROM can store static data or instructions required by the processor 420 or other modules of the computer. The permanent storage device may be a readable and writable storage device. The permanent storage device may be a non-volatile storage device that does not lose the stored instructions and data even after the computer is powered off. In some embodiments, the permanent storage device uses a large-capacity storage device (such as a magnetic or optical disk, flash memory) as a permanent storage device. In some other embodiments, the permanent storage device may be a removable storage device (such as a floppy disk, optical drive). The system memory may be a readable and writable storage device or a volatile readable and writable storage device, such as a dynamic random access memory. The system memory may store some or all instructions and data required by the processor at run time. In addition, the memory 410 may include any combination of computer-readable storage media, including various types of semiconductor memory chips (DRAM, SRAM, SDRAM, flash memory, programmable read-only memory), and disks and / or optical disks may also be used. In some embodiments, the memory 410 may include a readable and / or writable removable storage device, such as a laser disc (CD), a read-only digital versatile disc (such as a DVD-ROM, a double-layer DVD-ROM), a read-only Blu-ray disc, an ultra-density optical disc, a flash memory card (such as an SD card, a mini SD card, a Micro-SD card, etc.), a magnetic floppy disk, etc. The computer-readable storage medium does not include carrier waves and transient electronic signals transmitted wirelessly or wired.

[0130] The memory 410 stores executable codes. When the executable codes are processed by the processor 420, the processor 420 can execute the food odor detection method or the food online sales method mentioned above.

[0131] The food smell detection method, or the food online sales method and the computing device according to the present invention have been described in detail above with reference to the accompanying drawings.

[0132] In addition, the method according to the present invention may also be implemented as a computer program or a computer program product, which includes computer program code instructions for executing the above steps defined in the above method of the present invention.

[0133] Alternatively, the present invention may also be implemented as a non-temporary machine-readable storage medium (or computer-readable storage medium, or machine-readable storage medium) on which executable code (or computer program, or computer instruction code) is stored. When the executable code (or computer program, or computer instruction code) is executed by a processor of an electronic device (or computing device, server, etc.), the processor executes the various steps of the above-mentioned method according to the present invention.

[0134] Those skilled in the art will further appreciate that the various illustrative logical blocks, modules, circuits, and algorithm steps described in connection with the disclosure herein may be implemented as electronic hardware, computer software, or a combination of both.

[0135] The flow chart and block diagram in the accompanying drawings show the possible architecture, function and operation of the system and method according to multiple embodiments of the present invention. In this regard, each square box in the flow chart or block diagram can represent a part of a module, program segment or code, and the part of the module, program segment or code contains one or more executable instructions for realizing the specified logical function. It should also be noted that in some alternative implementations, the functions marked in the square box can also occur in a sequence different from that marked in the accompanying drawings. For example, two continuous square boxes can actually be executed substantially in parallel, and they can sometimes be executed in the opposite order, depending on the functions involved. It should also be noted that each square box in the block diagram and / or flow chart, and the combination of the square boxes in the block diagram and / or flow chart can be implemented with a dedicated hardware-based system that performs the specified function or operation, or can be implemented with a combination of dedicated hardware and computer instructions.

[0136] The embodiments of the present invention have been described above, and the above description is exemplary, not exhaustive, and is not limited to the disclosed embodiments. Many modifications and variations will be apparent to those of ordinary skill in the art without departing from the scope and spirit of the described embodiments. The terms used herein are selected to best explain the principles of the embodiments, practical applications, or improvements to the technology in the market, or to enable other persons of ordinary skill in the art to understand the embodiments disclosed herein.

Claims

1. A method for detecting food odor, comprising: Collecting odor data that can characterize the odor characteristics of food; Obtaining an odor analysis result obtained by analyzing the odor data; as well as outputting the odor analysis result, The step of collecting odor data capable of characterizing the odor characteristics of food includes: Based on the drift amount of the scanning temperature corresponding to the peak value of the response signal of the gas sensor caused by the difference between the current environmental information and the reference environmental information, and the reference starting scanning temperature, a first scanning temperature is set, the difference between the reference starting scanning temperature and the first scanning temperature is equal to or substantially equal to the drift amount, and the reference starting scanning temperature is the starting scanning temperature of the gas sensor under the reference environmental information; or based on the drift amount caused by the difference between the current environmental information and the reference environmental information, and the reference scanning temperature interval of the gas sensor under the reference environmental information, a first scanning temperature interval is set, the temperature range of the first scanning temperature interval is equal to or substantially equal to the temperature range of the reference scanning temperature interval, and the difference between the starting temperature value of the first scanning temperature interval and the starting temperature value of the reference scanning temperature interval is equal to or substantially equal to the drift amount; Generating a plurality of second scanning temperatures with the first scanning temperature as the starting scanning temperature, wherein the first scanning temperature and the plurality of second scanning temperatures form a plurality of scanning temperatures, or generating a plurality of scanning temperatures through the first scanning temperature interval; A temperature adjustment model is formed based on the multiple scanning temperatures, the active material in the gas sensor is adjusted to a corresponding scanning temperature based on the temperature adjustment model, and response signals of the gas sensor at different scanning temperatures are collected.

2. The method according to claim 1, wherein: The smell analysis result is used to characterize the type and / or smell of the food.

3. The method according to claim 1, wherein: The step of outputting the odor analysis result comprises: The smell analysis result and the description information of the food are outputted in association.

4. The method according to claim 1, wherein: The step of obtaining the odor analysis result obtained by analyzing the odor data comprises: Analyze the odor data locally to obtain an odor analysis result; or The odor data is sent to a server, and an odor analysis result obtained by analyzing the odor data by the server is obtained from the server.

5. A method for selling food online, comprising: Acquiring odor data that can characterize the odor characteristics of food produced by the merchant; Obtaining an odor analysis result obtained by analyzing the odor data; In response to the user's operation on the food displayed by the online merchant through the client, the smell analysis result of the food selected by the user is sent to the client, The step of obtaining odor data that can characterize the odor characteristics of the food produced by the merchant includes: using a gas sensor in a terminal device used by a user who purchased the food to collect odor data that can characterize the odor characteristics of the food produced by the merchant, specifically including: Based on the drift amount of the scanning temperature corresponding to the peak value of the response signal of the gas sensor caused by the difference between the current environmental information and the reference environmental information, and the reference starting scanning temperature, a first scanning temperature is set, the difference between the reference starting scanning temperature and the first scanning temperature is equal to or substantially equal to the drift amount, and the reference starting scanning temperature is the starting scanning temperature of the gas sensor under the reference environmental information; or based on the drift amount caused by the difference between the current environmental information and the reference environmental information, and the reference scanning temperature interval of the gas sensor under the reference environmental information, a first scanning temperature interval is set, the temperature range of the first scanning temperature interval is equal to or substantially equal to the temperature range of the reference scanning temperature interval, and the difference between the starting temperature value of the first scanning temperature interval and the starting temperature value of the reference scanning temperature interval is equal to or substantially equal to the drift amount; Generating a plurality of second scanning temperatures with the first scanning temperature as the starting scanning temperature, wherein the first scanning temperature and the plurality of second scanning temperatures form a plurality of scanning temperatures, or generating a plurality of scanning temperatures through the first scanning temperature interval; A temperature adjustment model is formed based on the multiple scanning temperatures, the active material in the gas sensor is adjusted to a corresponding scanning temperature based on the temperature adjustment model, and response signals of the gas sensor at different scanning temperatures are collected.

6. A method for detecting food odor, comprising: Acquiring odor data capable of characterizing the odor characteristics of food; Obtaining an odor analysis result obtained by analyzing the odor data; as well as outputting the odor analysis result, The step of obtaining odor data capable of characterizing the odor characteristics of food includes: Based on the drift amount of the scanning temperature corresponding to the peak value of the response signal of the gas sensor caused by the difference between the current environmental information and the reference environmental information, and the reference starting scanning temperature, a first scanning temperature is set, the difference between the reference starting scanning temperature and the first scanning temperature is equal to or substantially equal to the drift amount, and the reference starting scanning temperature is the starting scanning temperature of the gas sensor under the reference environmental information; or based on the drift amount caused by the difference between the current environmental information and the reference environmental information, and the reference scanning temperature interval of the gas sensor under the reference environmental information, a first scanning temperature interval is set, the temperature range of the first scanning temperature interval is equal to or substantially equal to the temperature range of the reference scanning temperature interval, and the difference between the starting temperature value of the first scanning temperature interval and the starting temperature value of the reference scanning temperature interval is equal to or substantially equal to the drift amount; Generating a plurality of second scanning temperatures with the first scanning temperature as the starting scanning temperature, wherein the first scanning temperature and the plurality of second scanning temperatures form a plurality of scanning temperatures, or generating a plurality of scanning temperatures through the first scanning temperature interval; A temperature adjustment model is formed based on the multiple scanning temperatures, the active material in the gas sensor is adjusted to a corresponding scanning temperature based on the temperature adjustment model, and response signals of the gas sensor at different scanning temperatures are collected.

7. A computing device comprising: processor; as well as A memory having executable codes stored thereon, which, when executed by the processor, causes the processor to execute the method according to any one of claims 1 to 6.

8. A computer program product, comprising executable codes, which, when executed by a processor of an electronic device, cause the processor to perform the method according to any one of claims 1 to 6.

9. A non-transitory machine-readable storage medium having executable codes stored thereon, which, when executed by a processor of an electronic device, causes the processor to execute the method according to any one of claims 1 to 6.

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