Control method for IoT device, IoT device and storage medium

Abstract

The present application relates to a control method for an IoT device, an IoT device and a storage medium, wherein the control method for the IoT device includes: when a potential event is detected in a target signal, the duration of the detected potential event is calculated according to the start and end of the same potential event detected; when the duration of the detected potential event meets the preset active event duration requirement, the potential event is identified as an active event, and the operation of the IoT device is controlled based on the identified active event. It can identify active events from potential events, and then trigger the operation of the IoT device based on the active event, so that the high-performance system can be accurately triggered based on the active event while meeting the low power consumption requirements.

Description

Technical Field

[0001] The present application relates to the technical field of Internet of Things, and in particular to a control method for an Internet of Things device, an Internet of Things device, and a storage medium. Background Art

[0002] At present, IoT devices cannot meet users’ low power consumption requirements in practical applications due to their “random sparse events” characteristics. Specifically, Figure 1 This is a schematic diagram of the random sparse characteristics of IoT events. Figure 1 As shown, common IoT applications such as physiological signal detection, voice control, touch control, fault detection, and disaster detection generally have the characteristics of "random sparse events", where "random" means that events detected by sensors occur randomly, such as the sudden onset of disease; "sparse" means that the average interval between events is long, such as the long time interval between natural disasters.

[0003] Based on this, high-performance systems in IoT devices need to work normally in "random sparse event" scenarios to cope with IoT events that may arrive at any time. Therefore, the normally open high-performance system processes invalid data for a relatively long time, and processes valid data after the event arrives for a relatively short time, resulting in high invalid energy consumption and high overall power consumption during operation, which in turn cannot meet the low power consumption requirements of IoT applications for devices.

[0004] At present, in the relevant technology, dynamic voltage and frequency adjustment technology is usually used to dynamically adjust the operating frequency and voltage of the chip according to the computing power requirements of the application program running on the chip to reduce power consumption. However, this method has limited effect on reducing static power consumption. Alternatively, a periodic polling technology is used to periodically wake up the high-performance system. Due to the random and sparse characteristics of IoT events, if the wake-up cycle is too long, there will be a high probability of missing the target event. If the wake-up cycle is short, a large number of useless wake-ups will be generated. Therefore, this method still cannot reduce the power consumption of the device. Based on this, the relevant technology cannot accurately trigger the high-performance system while meeting the low power consumption requirements.

[0005] In summary, there is currently no effective solution to the problem in related technologies that high-performance systems cannot be accurately triggered while meeting low power consumption requirements. Summary of the invention

[0006] In this embodiment, a control method for an Internet of Things device, an Internet of Things device, and a storage medium are provided to solve the problem in the related art that it is impossible to accurately trigger a high-performance system while meeting low power consumption requirements.

[0007] In a first aspect, a control method for an IoT device is provided in this embodiment, including:

[0008] When a potential event is detected in the target signal, the duration of the detected potential event is calculated according to the start and end of the detected potential event;

[0009] When the duration of the detected potential event meets the preset active event duration requirement, the potential event is identified as an active event, and based on the identified active event, the operation of the Internet of Things device is controlled.

[0010] This embodiment can identify active events from potential events, and then trigger the operation of IoT devices based on the active events, so that high-performance systems can be accurately triggered based on active events while meeting low power consumption requirements.

[0011] In some embodiments, the method further comprises:

[0012] Triggering the start detection of a potential event in the target signal during the current detection process with the end of the last potential event detected previously;

[0013] Using the start of the currently detected potential event, triggering the end detection of the currently detected potential event, and triggering the accumulation of the duration of the currently detected potential event;

[0014] The end of the currently detected potential event triggers the start detection of the next potential event.

[0015] This embodiment can detect potential events by alternating the triggering of event start and event end, so that event detection can be always on and continuously performed, and complete detection of potential events can be completed at a low hardware cost. Therefore, the trigger mechanism provided by this embodiment can achieve timely response to potential events while meeting low power consumption requirements.

[0016] In some embodiments, the method further comprises:

[0017] When the amplitude and / or time-frequency characteristics of the target signal meet the preset starting conditions, determining the current signal as the start of the potential event;

[0018] When the start of the potential event is detected and the amplitude and / or time-frequency characteristics of the target signal meet the preset end condition, the current signal is determined to be the end of the potential event. This embodiment detects the start and end of the potential event based on the amplitude and / or time-frequency characteristics, which can achieve accurate detection of the start of the potential event.

[0019] In some embodiments, the method further comprises:

[0020] When the amplitude of the target signal exceeds the preset first amplitude threshold, it is determined whether the time-frequency characteristics of the target signal meet the preset first time-frequency conditions; if so, the current signal is determined to be the start of the potential event. This embodiment detects the start of potential events from two dimensions, amplitude and time-frequency characteristics, without relying on classification and recognition algorithms, so that potential events can be detected at a lower hardware cost and at a lower power consumption cost.

[0021] In some embodiments, the method further comprises:

[0022] When the start of the potential event is detected and the amplitude of the target signal is lower than the preset second amplitude threshold, it is determined whether the time-frequency characteristics of the target signal meet the preset second time-frequency conditions; if so, the current signal is determined to be the end of the potential event. This embodiment detects the end of the potential event by combining amplitude and time-frequency characteristics, and can complete a complete potential event detection without using a classification and recognition algorithm, thereby reducing the power consumption of IoT devices and improving their energy efficiency.

[0023] In some embodiments, when the duration of the detected potential event meets a preset active event duration requirement, identifying the potential event as an active event includes:

[0024] When the duration of the potential event matches the preset duration range, the potential event is identified as the active event. This embodiment can accurately screen active events based on the duration range, thereby completing the detection of active events at a lower hardware cost and less power consumption, avoiding invalid wake-up of high-performance systems, and improving the efficiency of information processing of IoT devices.

[0025] In some embodiments, the method further comprises:

[0026] Based on the duration of all active events detected within the preset time period, the event activity within the preset time period is determined. Based on the calculated event activity, this embodiment can match the corresponding power consumption control strategy to flexibly adjust the opening and closing of the corresponding functions of the subsequent event processing process, so as to achieve full utilization of power consumption in the event processing process, thereby improving the utilization rate of power consumption in the event processing process.

[0027] In a second aspect, an Internet of Things device is provided in this embodiment, including a sensor, a preprocessing device, and a signal processor; wherein:

[0028] The sensor is used to collect sensor signals;

[0029] The preprocessing device is used to perform data preprocessing on the sensor signal to obtain a target signal, and output the target signal to the signal processor;

[0030] The signal processor is used to execute the control method of the Internet of Things device described in the first aspect above.

[0031] The above-mentioned IoT devices can identify active events from potential events, and then trigger the operation of IoT devices based on active events, thereby being able to accurately trigger high-performance systems based on active events while meeting low power consumption requirements.

[0032] In some embodiments, the signal processor includes a starting amplitude detection unit, an ending amplitude detection unit, an event duration judgment unit, and a time-frequency feature judgment unit; wherein:

[0033] The starting amplitude detection unit is used to trigger the operation of the ending amplitude detection unit and the event duration determination unit when detecting that the amplitude of the target signal reaches the starting amplitude of a preset potential event;

[0034] The end amplitude detection unit is used to trigger the time-frequency feature judgment unit to run when detecting that the amplitude of the target signal reaches the end amplitude;

[0035] The time-frequency feature judgment unit is used to trigger the start amplitude detection unit to run when it is detected that the time-frequency feature of the target signal reaches the end condition of the preset potential event;

[0036] The event duration determination unit is used to count the duration of the potential event.

[0037] This embodiment triggers the end detection and duration detection of a potential event based on the start detection of a potential event, and uses the end detection of a potential event to trigger the start detection of a new potential event. At the same time, only some event detection functions can be kept running, thereby reducing the energy consumption of the Internet of Things device and meeting the low power consumption requirements of actual Internet of Things application scenarios.

[0038] In a third aspect, an electronic device is provided in this embodiment, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein when the processor executes the computer program, the control method for an Internet of Things device described in the first aspect above is implemented.

[0039] In a fourth aspect, a storage medium is provided in this embodiment, on which a computer program is stored, and when the program is executed by a processor, the control method for an Internet of Things device described in the first aspect above is implemented.

[0040] Compared with the related art, the control method, IoT device and storage medium for IoT devices provided in this embodiment, when a potential event is detected in the target signal, calculates the duration of the detected potential event according to the start and end of the same potential event detected; when the duration of the detected potential event meets the preset active event duration requirement, the potential event is identified as an active event, and the operation of the IoT device is controlled based on the identified active event. It can identify active events from potential events, and then trigger the operation of IoT devices based on active events, so that it can accurately trigger high-performance systems based on active events while meeting low power consumption requirements.

[0041] Details of one or more embodiments of the present application are set forth in the following drawings and description to make other features, objects, and advantages of the present application more readily apparent. BRIEF DESCRIPTION OF THE DRAWINGS

[0042] The drawings described herein are used to provide a further understanding of the present application and constitute a part of the present application. The illustrative embodiments of the present application and their descriptions are used to explain the present application and do not constitute an improper limitation on the present application. In the drawings:

[0043] Figure 1 It is a schematic diagram of the random and sparse characteristics of IoT events;

[0044] Figure 2 is a hardware structure block diagram of a terminal of the control method of the Internet of Things device of this embodiment;

[0045] Figure 3 is a flow chart of the control method of the Internet of Things device of this embodiment;

[0046] Figure 4 is a schematic diagram of active event judgment in this embodiment;

[0047] Figure 5a is a waveform diagram of detecting the start of a potential event in this embodiment;

[0048] Figure 5b is a waveform diagram of detecting the end of a potential event in this embodiment;

[0049] Figure 6 is a schematic diagram of the duration of multiple active events within a preset time period provided in this embodiment;

[0050] Figure 7 is a flow chart of the active event detection method of the preferred embodiment;

[0051] Figure 8 is a flow chart of a potential event initiation detection method of the preferred embodiment;

[0052] Fig. 9 is a flow chart of a potential event end detection method of the preferred embodiment;

[0053] Fig.10 It is a structural block diagram of the Internet of Things device of this embodiment. DETAILED DESCRIPTION

[0054] In order to more clearly understand the purpose, technical solutions and advantages of the present application, the present application is described and illustrated below in conjunction with the accompanying drawings and embodiments.

[0055] Unless otherwise defined, the technical terms or scientific terms involved in this application shall have the general meaning understood by people with ordinary skills in the technical field to which this application belongs. The words "one", "a", "a", "the", "these" and the like in this application do not represent quantitative restrictions, and they can be singular or plural. The terms "include", "comprise", "have" and any variants thereof involved in this application are intended to cover non-exclusive inclusions; for example, a process, method and system, product or device comprising a series of steps or modules (units) is not limited to the listed steps or modules (units), but may include unlisted steps or modules (units), or may include other steps or modules (units) inherent to these processes, methods, products or devices. The words "connect", "connected", "coupled" and the like involved in this application are not limited to physical or mechanical connections, but may include electrical connections, whether directly or indirectly. The "multiple" involved in this application refers to two or more. "And / or" describes the association relationship of associated objects, indicating that there can be three relationships. For example, "A and / or B" can mean: A exists alone, A and B exist at the same time, and B exists alone. Usually, the character " / " indicates that the objects associated with each other are in an "or" relationship. The terms "first", "second", "third", etc. involved in this application are only used to distinguish similar objects and do not represent a specific ordering of the objects.

[0056] The method embodiment provided in this embodiment can be executed in a terminal, a computer or a similar computing device. For example, running on a terminal, Figure 2 : is a hardware structure block diagram of a terminal of the control method of the Internet of Things device of this embodiment. Figure 2 As shown, the terminal may include one or more ( Figure 2 Only one is shown in the figure) processor 202 and memory 204 for storing data, wherein processor 202 may include but is not limited to a processing device such as a microprocessor MCU or a programmable logic device FPGA. The above terminal may also include a transmission device 206 and an input and output device 208 for communication functions. It can be understood by those skilled in the art that Figure 2The structure shown is only for illustration and does not limit the structure of the above terminal. Figure 2 More or fewer components as shown, or with Figure 2 Different configurations shown.

[0057] The memory 204 can be used to store computer programs, for example, software programs and modules of application software, such as the computer program corresponding to the control method of the Internet of Things device in this embodiment. The processor 202 executes various functional applications and data processing by running the computer program stored in the memory 204, that is, to implement the above method. The memory 204 may include a high-speed random access memory, and may also include a non-volatile memory, such as one or more magnetic storage devices, flash memory, or other non-volatile solid-state memory. In some examples, the memory 204 may further include a memory remotely arranged relative to the processor 202, and these remote memories may be connected to the terminal via a network. Examples of the above-mentioned network include, but are not limited to, the Internet, an intranet, a local area network, a mobile communication network, and combinations thereof.

[0058] The transmission device 206 is used to receive or send data via a network. The above network includes a wireless network provided by the communication provider of the terminal. In one example, the transmission device 206 includes a network adapter (Network Interface Controller, referred to as NIC), which can be connected to other network devices through a base station so as to communicate with the Internet. In one example, the transmission device 206 can be a radio frequency (Radio Frequency, referred to as RF) module, which is used to communicate with the Internet wirelessly.

[0059] In this embodiment, a control method for an Internet of Things device is provided. Figure 3 is a flow chart of the control method of the Internet of Things device of this embodiment. Figure 3 As shown, the process includes the following steps:

[0060] Step S310, when a potential event is detected in the target signal, the duration of the detected potential event is calculated according to the start and end of the same detected potential event.

[0061] The target signal may be any signal collected by a sensor, such as a physiological signal, a sound signal, or a touch signal. A potential event refers to a target signal within a preset period of time where one or more signal characteristics of the target signal meet preset conditions, and the target signal within the period of time is a potential event.

[0062] It should be noted that the detection of potential events in this embodiment is a pre-processing process of the process of judging the type of specific events, identifying information, etc. That is to say, when a potential event is detected, it indicates that the detection environment has produced a certain degree of signal change during the period, and this signal change may be caused by a specific event to be identified, or it may be caused by other events that do not need to be processed. Therefore, the detection of a potential event does not mean that the detection environment must have produced a specific event that needs to trigger a high-performance system for analysis and detection. For example, an IoT device with a voice recognition function needs to trigger the corresponding function based on a preset voice keyword. In an unmanned environment, the signal collected by the IoT device is mainly white noise in the environment, and its signal amplitude is low. When a voice command is issued to the IoT device or an interjection with no practical meaning is captured in this environment, the amplitude of the signal collected by the IoT device has a relatively obvious increase. If the amplitude of the signal is higher than the preset amplitude threshold at this time, it is considered that a potential event has been detected. That is, the above-mentioned captured voice command or interjection corresponds to a potential event, but this does not mean that the specific voice recognition module configured by the IoT device needs to be immediately awakened to perform voice recognition for the above-mentioned potential event. Therefore, this embodiment also needs to screen potential events to obtain events that need to be identified.

[0063] For IoT devices with low power consumption requirements, such as IoT devices deployed in application scenarios with limited power supply capacity such as highways, high-altitude areas, and grazing areas, they have relatively strict requirements on the hardware cost and power consumption required for event detection. Based on this, this embodiment can meet the low power consumption requirements of the above IoT devices by determining the events that need to be identified among potential events.

[0064] Preferably, in order to further reduce the hardware cost and power consumption cost, the present embodiment uses a trigger mechanism to alternately detect the start and end of a potential event. In the case of no potential event being detected, the start detection function of the potential event is in a normally open state, while the duration accumulation and end detection functions of the potential event are in a closed state. When the start of a potential event is detected from the target signal, the function of the start detection of the potential event is turned off, and the end detection of the potential event and the recording function of the duration of the event are triggered. After the end of the potential event is detected, a complete detection of a potential event is completed. At this time, the end detection function of the potential event and the accumulation of the duration of the event are turned off, and the start detection function of the potential event is triggered to detect the next potential event. In this way, based on the alternating triggering of the start detection and end detection of the potential event, it is possible to always have some detection functions in an open state and some detection functions in a closed state during the entire operation of the potential event detection, so that the power consumption of the operation of the Internet of Things device can be reduced while realizing the detection of normally open and continuous potential events, and there is no need to deploy complex event recognition functions, thereby reducing the hardware cost, thereby simultaneously meeting the hardware cost requirements and low power consumption requirements for the Internet of Things device in the above-mentioned application scenarios.

[0065] Step S320: When the duration of the detected potential event meets the preset active event duration requirement, the potential event is identified as an active event, and the operation of the IoT device is controlled based on the identified active event.

[0066] Among them, active events refer to events that carry valid data and need to be analyzed and processed based on a high-performance system. The active events are events that are screened out from the above potential events and have the value of analysis and identification. For example, the voice events to be recognized in the voice recognition scene, the face targets that appear in the face recognition scene, and the combustible gases detected in the fire warning scene are all active events corresponding to the actual application scene. In addition, in order to eliminate interference factors such as sudden noise, this embodiment uses the duration of the potential event as an indicator to measure whether the potential event is an active event, thereby improving the accuracy of active event screening. Continue to use the above voice recognition scene as an example for explanation. Based on the duration of the occurrence of the word, the duration of the voice event will fluctuate within a specific duration range, so the voice event can be distinguished from other interference events based on the duration of the potential event. For example, if a potential event such as a short bird chirping is detected in the environment, because the duration of its duration does not meet the preset duration requirement, it can be directly confirmed that this type of potential event is not an active event. Alternatively, if a potential event such as prolonged honking is detected in the environment, then since the duration of the honking exceeds the maximum duration of a voice event, it can be directly confirmed that the potential event is not an active event.

[0067] That is, this embodiment screens potential events based on the preset active event duration requirement to determine whether they are active events, thereby improving the accuracy of active event identification. Among them, the active event duration requirement can specifically be a preset duration threshold or a duration range. For example, only when the duration of the potential event belongs to the preset duration range, the potential event is identified as an active event, thereby improving the accuracy of active event detection and avoiding interference of invalid information in subsequent event processing. This embodiment screens potential events and triggers the operation of the Internet of Things device only when it is determined that the potential event is an active event, thereby avoiding invalid power consumption caused by the wake-up of the Internet of Things device by irrelevant events, so as to achieve accurate triggering of high-performance systems in Internet of Things devices while meeting low power consumption requirements.

[0068] In addition, after an active event is identified, it can be used as a trigger signal to wake up the corresponding function of the IoT device and control the operation of the IoT device. For example, the corresponding event analysis function deployed in the IoT device can be triggered to run based on the active event, or the corresponding alarm function of the IoT device can be triggered to run.

[0069] Figure 4 FIG. 4 is a schematic diagram of active event determination in this embodiment. Figure 4 As shown, after detecting the start of potential event 1, the end of potential event 1 is triggered, and the accumulation of the duration of potential event 1 is started at the same time. After detecting the end of potential event 1, the accumulation of the duration of potential event 1 is stopped to obtain the duration of potential event 1. At this time, the start detection of potential event 2 is started, and based on the above steps, the detection of the start, end and duration of potential event 2 is completed. In addition, since the duration of potential event 1 meets the preset active event duration requirement, potential event 1 is an active event; if the duration of potential event 2 does not meet the preset active event duration requirement, potential event 2 is an inactive event.

[0070] In addition, all active events detected within a preset time period can be counted to determine the overall event activity within the time period. The specific calculation method can be set based on the actual application scenario. For example, the duration, amplitude or combination of all active events within the preset time period can be statistically processed to calculate the event activity. After obtaining the event activity, the operating state of the subsequent associated event processing module can be adjusted based on the size of the activity. For example, based on different activity levels, the corresponding power consumption control strategy is preset. The higher the activity level, the more complex the functions that the event processing module needs to perform, and the higher the power consumption required. Therefore, based on the calculated event activity, the corresponding power consumption control strategy can be matched to flexibly adjust the opening and closing of the corresponding functions of the subsequent event processing process, so as to achieve full utilization of power consumption in the event processing process, thereby improving the utilization rate of power consumption in the event processing process.

[0071] In the above steps S310 to S320, when a potential event is detected in the target signal, the duration of the detected potential event is calculated based on the start and end of the same potential event detected; when the duration of the detected potential event meets the preset active event duration requirement, the potential event is identified as an active event, and the operation of the IoT device is controlled based on the identified active event. It can identify active events from potential events, and then trigger the operation of IoT devices based on active events, so that it can accurately trigger high-performance systems based on active events while meeting low power consumption requirements.

[0072] Furthermore, in one embodiment, the control method for an IoT device may further include the following steps:

[0073] Step S331, triggering the start detection of potential events in the target signal in the current detection process with the end of the previous potential event detected previously;

[0074] Step S332, triggering the end detection of the currently detected potential event based on the start of the currently detected potential event, and triggering the accumulation of the duration of the currently detected potential event;

[0075] Step S333: The end of the currently detected potential event triggers the start detection of the next potential event.

[0076] On the one hand, when no potential event is detected, this embodiment only turns on the start detection function of the potential event, and turns off the end detection function and the duration accumulation function, thereby reducing the power consumption of the IoT device. On the other hand, after a potential event is detected, the start detection function of the potential event is turned off, and the end detection of the potential event and the accumulation of the duration are triggered, so as to complete the complete detection of the potential event at a lower hardware cost. Further, if a potential event has been detected in the previous detection process, the start detection function of the potential event in the current detection process needs to be triggered based on the end of the previous potential event detected earlier, that is, the end of the latest potential event detected earlier. Similarly, after the end detection of the potential event is completed in the current detection process, the end detection function is turned off, and the start detection function for the next potential event is triggered. Therefore, the trigger mechanism provided by this embodiment can achieve timely response to potential events while meeting the low power consumption requirements.

[0077] In addition, it should be noted that when there is no previously detected potential event, for example, when the chip that detects potential events is powered on for the first time and there is no previous detected potential event, the start detection of the first potential event can be performed automatically without the need for an end trigger of the potential event.

[0078] Additionally, in one embodiment, based on the above steps S331 to S333, the above control method for an IoT device may further include the following steps:

[0079] Step S341, when the amplitude and / or time-frequency characteristics of the target signal meet the preset starting conditions, determine that the current signal is the start of a potential event.

[0080] Step S342, when the start of a potential event is detected and the amplitude and / or time-frequency characteristics of the target signal meet the preset end conditions, determine that the current signal is the end of the potential event.

[0081] Specifically, this embodiment triggers the start detection of a potential event in the current detection process by the end of the previous potential event detected previously. In the start detection process, it can be determined whether the current signal is the start of a potential event based on the amplitude, time-frequency characteristics, or amplitude combined with time-frequency characteristics of the target signal, and after detecting the start of the potential event, it is determined whether the current signal is the end of the potential event based on the above characteristics. The above current signal refers to a signal whose amplitude and / or time-frequency characteristics in the target signal meet the preset start conditions of the potential event. The above time-frequency characteristics refer to the data characteristics of the target signal obtained within a preset interval in the time domain and frequency domain, such as the slope, waveform, and other characteristics of the data in the preset interval in the time domain or frequency domain. Among them, the data characteristics in the frequency domain need to be obtained after Fourier transforming the data in the preset interval. The above start conditions and end conditions can be thresholds, numerical ranges, or other feature ranges pre-set based on actual application scenarios, and this embodiment does not specifically limit this.

[0082] In addition, for some application scenarios such as geological phenomenon detection, temperature detection, and smoke concentration detection, the start and end detection of potential events can be completed based only on the amplitude of the target signal. For application scenarios such as electrocardiogram heartbeat recognition, it is necessary to complete the detection of potential events by combining amplitude with time-frequency characteristics. Based on this, according to the needs of the actual application scenario, the detection of potential events can be achieved based on the amplitude, time-frequency characteristics, or amplitude combined with time-frequency characteristics of the target signal. Based on the alternating triggering of the start and end of the potential event, this embodiment further detects the start and end of the potential event based on the amplitude and / or time-frequency characteristics, which can achieve accurate detection of the start of the potential event. Preferably, in order to further reduce the misjudgment of the start detection of the potential event, this embodiment realizes the detection of the start and end of the potential event by combining the amplitude with the time-frequency feature detection, thereby reducing the hardware cost and power consumption of the potential event detection.

[0083] Additionally, in one embodiment, based on the above steps S331 to S333, the above control method for an IoT device may further include the following steps:

[0084] Step S343, when the amplitude of the target signal exceeds the preset first amplitude threshold, determine whether the time-frequency characteristics of the target signal meet the preset first time-frequency conditions; if so, determine that the current signal is the start of a potential event.

[0085] Based on the trigger of the end of the previous potential event detected previously, the detection of the start of the potential event in the current detection process is started. Figure 5a FIG. 4 is a waveform diagram of detecting the start of a potential event in this embodiment. Figure 5aAs shown, before the start detection of a potential event is performed, the target signal is first preprocessed. Exemplarily, the DC offset is separated from the potential event to be detected to avoid interference of the DC offset with the subsequent processing process, and the target signal after the DC offset is eliminated is obtained. Afterwards, the target signal with the DC offset eliminated is subjected to an operation to increase the signal-to-noise ratio, thereby obtaining a target signal that has completed the preprocessing. Specifically, the absolute value of the target signal can be taken and then a sliding integral can be performed to obtain a target signal with an increased signal-to-noise ratio. In addition, the above preprocessing process can be adaptively adjusted based on the needs of the actual application, and this embodiment does not specifically limit this. Continue to combine Figure 5a To illustrate, this embodiment determines the amplitude of the target signal after the signal-to-noise ratio is increased. When the amplitude of the target signal exceeds the preset first amplitude threshold, it is determined that the target signal meets the amplitude condition. Thus, the detection of the time-frequency characteristics of the target signal is triggered. Specifically, data within a preset time interval can be taken from the moment when the target signal meets the amplitude condition, and the time domain characteristics can be analyzed, and the frequency domain characteristics can be analyzed after Fourier transform. When the time-frequency characteristics meet the preset first time-frequency condition, the current signal in the target signal that meets the starting condition is determined as the start of a potential event.

[0086] Among them, the elimination of the above-mentioned DC offset can be achieved based on a filtering network composed of components such as resistors, capacitors and inductors, or digital filtering. The above-mentioned method of increasing the signal-to-noise ratio can also be achieved based on filtering, squaring, energy calculation, i.e., power calculation, etc. The specific process of the above-mentioned amplitude determination can also include implementation based on threshold determination, linear classification method and machine learning method. In addition, the detection of time-frequency features can also be based on time length threshold detection, zero crossing rate detection, slope sign change, wavelength detection, statistical value detection, power spectrum density, spectrum estimation based on autoregressive model and wavelet transform.

[0087] This embodiment takes into account that potential events often present certain characteristics in terms of slope, waveform, etc. in the time domain or frequency domain. Therefore, when the amplitude of the target signal exceeds the preset first amplitude threshold, the time-frequency characteristics of the target signal are analyzed to further complete the judgment of the start of the potential event. For example, the slope of human voice in the time domain and the distribution in the frequency domain are different from those of other animals. When the human voice and the voice of other animals are close in sound amplitude, the start of the potential event cannot be accurately detected based only on the amplitude of the target signal. Therefore, in addition to the dimension of amplitude, this embodiment also considers the characteristics of the target signal in time and frequency to distinguish potential events. This embodiment realizes the detection of the start of potential events from the two dimensions of amplitude and time-frequency characteristics, without relying on classification and recognition algorithms, so that the detection of potential events can be achieved at a lower power consumption cost under the premise of paying a smaller hardware cost.

[0088] In one embodiment, the control method for the IoT device may further include the following steps:

[0089] Step S344, when the start of a potential event is detected and the amplitude of the target signal is lower than a preset second amplitude threshold, determine whether the time-frequency characteristics of the target signal meet the preset second time-frequency conditions; if so, determine that the current signal is the end of the potential event.

[0090] Accordingly, after the start of a potential event is detected, the end of the potential event may also be detected based on the amplitude and / or time-frequency characteristics of the target signal. Figure 5b FIG. 4 is a waveform diagram of detecting the end of a potential event in this embodiment. Figure 5b As shown, after the target signal is preprocessed to separate the DC offset and increase the signal-to-noise ratio, the target signal is subjected to amplitude judgment. If the amplitude of the target signal is lower than the preset second amplitude threshold, the time-frequency feature detection of the target signal is triggered. Similarly, data within a preset time interval is taken from the moment when the target signal meets the amplitude condition, and the time domain features are analyzed, and the frequency domain features are analyzed after Fourier transform. When the time-frequency features of the target signal meet the preset second time-frequency condition, it is confirmed that the target signal meets the preset end condition, and the end detection of the target signal is completed. By Figure 5b It can be seen that the analysis result of the first time-frequency feature does not meet the second time-frequency condition, so it is judged as the non-end of the potential event; therefore, it returns to the steps of data preprocessing and amplitude detection; until the moment when the amplitude is lower than the second amplitude threshold is found for the second time, the analysis of the time-frequency feature is triggered again. After confirming that the time-frequency feature meets the above-mentioned second time-frequency condition, it is judged as the end of the potential event.

[0091] Take the recognition of polysyllabic English words as an example. The end of a polysyllabic English word should be the end of the last syllable, but since the amplitude of the target signal corresponding to the end of the middle syllable may also be less than the preset second amplitude threshold, the end of the middle syllable may be mistakenly regarded as the end of the entire word based only on the amplitude judgment of the target signal. Therefore, this embodiment introduces a time-frequency judgment mechanism, which is based on the analysis of time domain features. After the amplitude of the target signal is less than the second amplitude threshold and maintains for more than a preset time, it is determined that the end of the entire word is detected. Since the pause time between syllables is usually shorter than the pause time between words, this embodiment can accurately distinguish between the end of a word and the end of a syllable based on amplitude and time-frequency features. Based on the above analysis, it is not difficult to see that this embodiment detects the end of a potential event by combining amplitude and time-frequency features, and can complete a complete potential event detection without using a classification recognition algorithm, thereby reducing the power consumption of IoT devices and improving their energy efficiency.

[0092] Additionally, in one embodiment, based on the above step S320, when the duration of the detected potential event meets the preset active event duration requirement, identifying the potential event as an active event may further include the following steps:

[0093] Step S321, when the duration of the potential event matches the preset duration range, the potential event is identified as an active event. That is, only when the duration of the potential event is higher than the preset first duration threshold and lower than the preset second duration threshold, the potential event is identified as an active event. Potential events that last too long or too short are not active events. This embodiment can accurately screen active events based on the duration range, thereby completing the detection of active events at a lower hardware cost and less power consumption, avoiding invalid wake-up of high-performance systems, and improving the efficiency of information processing of IoT devices.

[0094] In addition, in one embodiment, the control method for the IoT device may further include the following steps:

[0095] Step S350, determining the event activity within the preset time period based on the duration of all detected active events within the preset time period.

[0096] The duration of all active events within a preset period can be statistically analyzed to obtain the activity of the events within the preset period. The specific statistical method can be set based on actual application requirements. For example, Figure 6 This is a schematic diagram of the duration of multiple active events within a preset time period provided in this embodiment. Figure 6 As shown, the preset time period T includes N active events, namely active event 1, active event 2, ..., active event N. The corresponding durations are t 1 ,t 2 ,…,t N The duration of active events in the preset time period T is accumulated and averaged to obtain the event activity in the time period. The specific formula is as follows:

[0097]

[0098] Where α is the event activity, t iis the duration of the i-th active event. N is the number of active events in the preset time period T. By calculating the event activity to match the corresponding power consumption control strategy, the state of each functional module in the subsequent event processing process can be flexibly adjusted to avoid high-performance systems using large power consumption to process simpler active events. Therefore, this embodiment helps to fully utilize power consumption and improve the utilization rate of power consumption in the event processing process. In addition, this embodiment can also quantify the activity level of events in different time periods, so as to facilitate users to make corresponding decisions based on event activity.

[0099] The present embodiment is described and illustrated below through preferred embodiments.

[0100] Figure 7 FIG. 4 is a flow chart of the active event detection method of this preferred embodiment. Figure 7 As shown, the active event detection method includes the following steps:

[0101] Step S701, detecting the start of a potential event;

[0102] Step S702, determining whether the start of a potential event is detected; if so, executing step S703; otherwise, returning to executing step S701;

[0103] Step S703, triggering detection of the end and duration of a potential event;

[0104] Step S704, determining whether the end of the potential event is detected; if so, executing step S706; otherwise, returning to executing step S703;

[0105] Step S705, determining whether the duration of the potential event meets the duration requirement of the active event; if so, executing step S706; otherwise, returning to executing step S701;

[0106] Step S706, determining whether the determination results of step S704 and step S705 are both yes; if yes, executing step S707; otherwise, returning to executing step S701;

[0107] Step S707: determine the currently detected potential event as an active event, and calculate the event activity.

[0108] Figure 8 is a flow chart of the potential event initiation detection method of the preferred embodiment. Figure 8 As shown, the potential event initiation detection method includes the following steps:

[0109] Step S801, eliminating the DC offset of the target signal;

[0110] Step S802, increasing the signal-to-noise ratio of the target signal;

[0111] Step S803, determining whether the amplitude of the target signal reaches a preset first amplitude threshold; if so, executing step S804; otherwise, returning to executing step S801;

[0112] Step S804, determining whether the time-frequency characteristics of the target signal meet the preset first time-frequency condition; if so, executing step S805; otherwise, returning to executing step S801;

[0113] Step S805, confirming that the start of a potential event is detected, triggering detection of the end and duration of the potential event.

[0114] Fig. 9 Flow chart of the potential event end detection method of the preferred embodiment. Fig. 9 As shown, the potential event end detection method includes the following steps:

[0115] Step S901, eliminating the DC offset of the target signal;

[0116] Step S902, increasing the signal-to-noise ratio of the target signal;

[0117] Step S903, determining whether the amplitude of the target signal is less than a preset second amplitude threshold; if so, executing step S904; otherwise, returning to executing step S901;

[0118] Step S904, determining whether the time-frequency characteristics of the target signal meet the preset second time-frequency condition; if so, executing step S905; otherwise, returning to executing step S901;

[0119] Step S905 , confirming that the end of a potential event is detected, triggering the determination of an active event, and triggering the detection of the start of the next potential event.

[0120] Fig.10 is a structural block diagram of the Internet of Things device of this embodiment, such as Fig.10 As shown, the Internet of Things device includes: a sensor 12, a preprocessing device 14 and a signal processor 16; wherein: the sensor 12 is used to collect sensor signals; the preprocessing device 14 is used to perform data preprocessing on the sensor signals to obtain target signals and output the target signals to the signal processor 16; the signal processor 16 is used to execute the control method of the Internet of Things device provided in the above embodiment.

[0121] The IoT device can be any device suitable for application scenarios with low power consumption requirements. For example, it can be a smart manhole cover, a water quality biological detection device, a combustible gas detector, etc. Fig.10It can be seen that the sensor 12 can be any sensor suitable for IoT devices, such as a touch sensor, a sound sensor, and an image sensor. The preprocessing device 14 may include a multiplexer, a filter network, and a data converter. In addition, the preprocessing device 14 may also be composed of other parts, which is not limited in this embodiment. The sensor signal collected by the sensor 12 enters the filter network through the multiplexer in a time-division multiplexing manner to separate the DC offset and collect the transient change of the signal. Afterwards, the transient change signal is sent to the data converter and converted into a digital signal, thereby obtaining the above-mentioned target signal.

[0122] Furthermore, after the target signal is sent to the signal processor 16, the absolute value of the target signal is first taken, and then a sliding integration is performed, so as to increase the signal-to-noise ratio of the signal and improve the accuracy of subsequent calculations. Afterwards, the starting amplitude detection unit in the signal processor 16 judges the amplitude of the target signal. For example, if the preset first amplitude threshold is reached, it is considered that the start of a potential event is detected, and the end amplitude detection unit is immediately triggered to run. At the same time, the trigger counter records the length of time from the start of the potential event. At the same time, the event duration judgment unit judges in real time whether the duration of the potential event violates the preset duration requirement of the active event based on the counting result of the counter.

[0123] When it is detected that the amplitude of the target signal meets the end condition of the potential event, the data buffer unit and the time-frequency feature judgment unit are triggered to run. The data buffer unit saves the data of the target signal within the preset time frame and uses it for time-frequency feature detection. When the time-frequency characteristics of the target signal meet the end condition of the potential event in the time-frequency domain, it is determined that the end of the potential event has been detected. At this time, if the event duration detection unit detects that the duration meets the preset active event duration requirement, it can be determined that an active event has been detected, and the event activity calculation module is triggered to perform event activity calculation.

[0124] The above-mentioned IoT device can detect potential events by alternating the start and end of events, and identify active events from potential events, so as to reduce the power consumption of signal processing while always opening and continuously detecting the activity level of events, and accurately trigger high-performance systems based on active events while meeting low power consumption requirements.

[0125] Further, in one embodiment, the signal processor 16 includes a starting amplitude detection unit, an ending amplitude detection unit, an event duration judgment unit and a time-frequency feature judgment unit; wherein: the starting amplitude detection unit is used to trigger the ending amplitude detection unit and the event duration judgment unit to run when it is detected that the amplitude of the target signal reaches the starting amplitude of a preset potential event; the ending amplitude detection unit is used to trigger the time-frequency feature judgment unit to run when it is detected that the amplitude of the target signal reaches the ending amplitude; the time-frequency feature judgment unit is used to trigger the starting amplitude detection unit to run when it is detected that the time-frequency feature of the target signal reaches the ending condition of a preset potential event; the event duration judgment unit is used to count the duration of the potential event.

[0126] This embodiment triggers the end detection and duration detection of a potential event based on the start detection of a potential event, and uses the end detection of a potential event to trigger the start detection of a new potential event. At the same time, only some event detection functions can be kept running, thereby reducing the energy consumption of the Internet of Things device and meeting the low power consumption requirements of actual Internet of Things application scenarios.

[0127] It should be noted that the above modules can be functional modules or program modules, and can be implemented by software or hardware. For modules implemented by hardware, the above modules can be located in the same processor; or the above modules can be located in different processors in any combination.

[0128] In this embodiment, an electronic device is further provided, including a memory and a processor, wherein a computer program is stored in the memory, and the processor is configured to run the computer program to execute the steps in any one of the above method embodiments.

[0129] Optionally, the electronic device may further include a transmission device and an input / output device, wherein the transmission device is connected to the processor, and the input / output device is connected to the processor.

[0130] Optionally, in this embodiment, the processor may be configured to perform the following steps through a computer program:

[0131] S1, when a potential event is detected in the target signal, the duration of the detected potential event is calculated according to the start and end of the same detected potential event;

[0132] S2, when the duration of the detected potential event meets the preset active event duration requirement, the potential event is identified as an active event, and the operation of the IoT device is controlled based on the identified active event.

[0133] It should be noted that the specific examples in this embodiment can refer to the examples described in the above embodiments and optional implementation modes, and will not be repeated in this embodiment.

[0134] In addition, in combination with the control method for an IoT device provided in the above embodiments, a storage medium may also be provided in this embodiment to implement the control method. The storage medium stores a computer program; when the computer program is executed by a processor, any control method for an IoT device in the above embodiments is implemented.

[0135] It should be understood that the specific embodiments described herein are only used to explain the application, rather than to limit it. Based on the embodiments provided in this application, all other embodiments obtained by ordinary technicians in this field without creative work are within the protection scope of this application.

[0136] It should be noted that the user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data used for analysis, stored data, displayed data, etc.) involved in this application are all information and data authorized by the user or fully authorized by all parties.

[0137] Obviously, the drawings are only some examples or embodiments of the present application. For ordinary technicians in the field, the present application can also be applied to other similar situations based on these drawings without creative work. In addition, it is understandable that although the work done in this development process may be complicated and lengthy, for ordinary technicians in the field, certain changes in design, manufacturing or production based on the technical content disclosed in this application are only conventional technical means and should not be regarded as insufficient content disclosed in this application.

[0138] The term "embodiment" in this application refers to a specific feature, structure or characteristic described in conjunction with the embodiment that can be included in at least one embodiment of the present application. The appearance of this phrase in various locations in the specification does not necessarily mean the same embodiment, nor does it mean that it is mutually exclusive with other embodiments and is independent or optional. It is clearly or implicitly understood by those of ordinary skill in the art that the embodiments described in this application can be combined with other embodiments without conflict.

[0139] The above-mentioned embodiments only express several implementation methods of the present application, and the descriptions thereof are relatively specific and detailed, but they cannot be understood as limiting the scope of patent protection. It should be pointed out that, for a person of ordinary skill in the art, several variations and improvements can be made without departing from the concept of the present application, and these all belong to the scope of protection of the present application. Therefore, the scope of protection of the present application shall be subject to the attached claims.

Claims

1. A control method for an Internet of Things device, characterized in that: At least for pre-processing of event type judgment and information identification, the method includes: In the process of detecting potential events on the target signal, after completing the end detection of the previous potential event, the start detection function of the potential event is in a normally open state, and the duration accumulation function and the end detection function of the potential event are in a closed state; When the start of a potential event in the current detection process is detected from the target signal, the start detection function is turned off, and the end detection function and the duration accumulation function are triggered; After detecting the end of a potential event in the current detection process, confirming that a complete detection of a potential event has been completed, turning off the end detection function and the duration accumulation function, and triggering the start detection function to detect the next potential event; Calculate the duration of the detected potential event according to the start and end of the detected potential event; When the duration of the detected potential event meets the preset active event duration requirement, the potential event is identified as an active event, and based on the identified active event, the operation of the Internet of Things device is controlled.

2. The control method for an Internet of Things device according to claim 1, characterized in that: The method further comprises: When the amplitude and / or time-frequency characteristics of the target signal meet the preset starting conditions, determining the current signal as the start of the potential event; When the start of the potential event is detected and the amplitude and / or time-frequency characteristics of the target signal meet the preset end conditions, the current signal is determined to be the end of the potential event.

3. The control method for an Internet of Things device according to claim 1, characterized in that: The method further comprises: When the amplitude of the target signal exceeds a preset first amplitude threshold, it is determined whether the time-frequency characteristics of the target signal meet the preset first time-frequency conditions; if so, the current signal is determined to be the start of the potential event.

4. The control method for an Internet of Things device according to claim 1, characterized in that: The method further comprises: When the start of the potential event is detected and the amplitude of the target signal is lower than a preset second amplitude threshold, it is determined whether the time-frequency characteristics of the target signal meet the preset second time-frequency conditions; if so, it is determined that the current signal is the end of the potential event.

5. The control method for an Internet of Things device according to claim 1, characterized in that: The step of identifying the potential event as an active event when the duration of the detected potential event meets a preset active event duration requirement includes: When the duration of the potential event matches a preset duration range, the potential event is identified as the active event.

6. The control method for an Internet of Things device according to any one of claims 1 to 5, characterized in that: The method further comprises: The event activity within the preset time period is determined based on the duration of all detected active events within the preset time period.

7. An Internet of Things device, characterized in that: It includes a sensor, a preprocessing device and a signal processor; wherein: The sensor is used to collect sensor signals; The preprocessing device is used to perform data preprocessing on the sensor signal to obtain a target signal, and output the target signal to the signal processor; The signal processor is used to execute the control method for an Internet of Things device according to any one of claims 1 to 6.

8. The Internet of Things device according to claim 7, characterized in that: The signal processor includes a starting amplitude detection unit, an ending amplitude detection unit, an event duration judgment unit and a time-frequency feature judgment unit; wherein: The starting amplitude detection unit is used to trigger the operation of the ending amplitude detection unit and the event duration determination unit when detecting that the amplitude of the target signal reaches the starting amplitude of a preset potential event; The end amplitude detection unit is used to trigger the time-frequency feature judgment unit to run when detecting that the amplitude of the target signal reaches the end amplitude; The time-frequency feature judgment unit is used to trigger the start amplitude detection unit to run when it is detected that the time-frequency feature of the target signal reaches the end condition of the preset potential event; The event duration determination unit is used to count the duration of the potential event.

9. An electronic device comprising a memory and a processor, characterized in that: A computer program is stored in the memory, and the processor is configured to run the computer program to execute the control method for an Internet of Things device according to any one of claims 1 to 6.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the control method for an Internet of Things device described in any one of claims 1 to 6 are implemented.

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