Control method of smart helmet and smart helmet

Abstract

The present disclosure relates to a control method of a smart device and a smart helmet, and relates to the technical field of order delivery, wherein the smart helmet is provided with an image acquisition unit and a shielding unit, the image acquisition unit is used to acquire environmental images around the smart helmet; the method comprises the following steps: obtaining environmental information of the smart helmet, the environmental information is used to represent environmental information where the smart helmet is located in a scenario that a user wearing the smart helmet performs an order delivery task; in the case that it is identified that the environmental scenario where the smart helmet is located after analyzing the environmental information is a sensitive scenario, controlling the image acquisition unit to stop image acquisition, and / or controlling the shielding unit to make the image acquisition unit in a shielded state; the sensitive scenario is a scenario involving sensitive information of a person or an organization. The control method of the smart device provided by the present disclosure can realize privacy protection in a sensitive scenario in an order delivery process.

Description

Technical Field

[0001] This disclosure relates to the field of order delivery technology, and more specifically, to a control method for a smart device and a smart helmet. Background Technology

[0002] In the delivery sector, some delivery personnel use wearable devices that have the ability to collect environmental information (such as taking pictures, recording videos, and transmitting images in real time). However, delivery personnel may wear these wearable devices into private or confidential areas, which may pose a risk to user privacy or information leakage. This issue needs to be addressed. Summary of the Invention

[0003] The purpose of this disclosure is to provide a control method for smart devices and a smart helmet to achieve privacy protection in sensitive scenarios during order delivery.

[0004] In a first aspect, this disclosure proposes a control method for a smart helmet, wherein the smart helmet is equipped with an image acquisition unit and an occlusion unit, the image acquisition unit being used to acquire environmental images surrounding the smart helmet; the method includes: The environmental information of the smart helmet is obtained, and the environmental information is used to characterize the environmental information of the smart helmet in the scenario where the user wearing the smart helmet is performing an order delivery task; If the environment scene of the smart helmet, as determined by the analysis and identification of the environmental information, is a sensitive scene, the system controls the image acquisition unit to stop image acquisition and / or controls the occlusion unit to put the image acquisition unit in an occluded state; the sensitive scene is a scene involving sensitive information of an individual or organization.

[0005] Optionally, the sensitive scene includes a sensitive location and / or a sensitive environment; upon receiving a result indicating that the environment scene of the smart helmet, obtained through analysis and identification of the environmental information, matches a sensitive scene, the image acquisition unit is controlled to stop image acquisition, and / or the occlusion unit is controlled to put the image acquisition unit in an occluded state, including: If the location area of ​​the smart helmet related to the order delivery task is identified as a sensitive location and / or the environment represented by the environmental perception parameters of the smart helmet related to the order delivery task is identified as a sensitive environment, the image acquisition unit is controlled to stop image acquisition and / or the occlusion unit is controlled to put the image acquisition unit in an occluded state.

[0006] Optionally, the method further includes: If the location area of ​​the smart helmet related to the order delivery task is identified as a personal sensitive privacy area and / or an organizational sensitive privacy area, the image acquisition unit is controlled to stop image acquisition and / or the occlusion unit is controlled to put the image acquisition unit in an occluded state. The sensitive locations include the personal sensitive privacy area and / or the organizational sensitive privacy area; the personal sensitive privacy area is the area where the smart helmet is located at a distance less than a preset distance from the delivery address specified in the order delivery task, and the organizational sensitive privacy area is the area where the organization is located and access is restricted to unauthorized personnel.

[0007] Optionally, the method further includes at least one of the following: The system acquires temperature and humidity information of the location area of ​​the smart helmet related to the order delivery task. If the spatial environment characteristics represented by the temperature and humidity information related to the order delivery task are determined to be the bathroom environment characteristics, the system determines that the sensitive environment of the smart helmet is a sensitive privacy environment. The system then controls the image acquisition unit to stop image acquisition and / or controls the occlusion unit to put the image acquisition unit in an occluded state. The system acquires the wireless network of the location area of ​​the smart helmet that is related to the order delivery task. If the wireless network of the location area related to the order delivery task is detected to be a home wireless network, the system determines that the sensitive environment of the smart helmet is a sensitive network environment, controls the image acquisition unit to stop image acquisition and / or controls the occlusion unit to put the image acquisition unit in an occluded state. If a region map of the location area related to the order delivery task is obtained, and there are sensitive geographical markers in the region map of the location area related to the order delivery task, and the location area of ​​the smart helmet related to the order delivery task is about to enter the sensitive geographical location represented by the sensitive geographical markers, then the sensitive environment of the smart helmet is determined to be a sensitive geographical environment, and the image acquisition unit is controlled to stop image acquisition and / or the occlusion unit is controlled to put the image acquisition unit in an occluded state. The system acquires an environmental image of the location area of ​​the smart helmet that is related to the order delivery task. If there are sensitive image features in the environmental image related to the order delivery task, the system determines that the sensitive environment of the smart helmet is a sensitive visual environment, controls the image acquisition unit to stop image acquisition and / or controls the occlusion unit to put the image acquisition unit in an occluded state. The system acquires ambient audio of the location area of ​​the smart helmet that is related to the order delivery task. If there are sensitive audio words in the ambient audio related to the order delivery task, the system determines that the sensitive environment of the smart helmet is a sensitive audio environment, controls the image acquisition unit to stop image acquisition and / or controls the occlusion unit to put the image acquisition unit in an occluded state.

[0008] Optionally, the method further includes: If the environmental scene represented by the environmental image and / or environmental audio is identified as a conflict scene, the image acquisition unit is controlled to acquire an image and the occlusion unit is controlled to keep the image acquisition unit in an unoccluded state; the environmental information includes the environmental image and / or the environmental audio. The conflict scenarios include adversarial communication scenarios in interpersonal communication.

[0009] Optionally, the method further includes: Upon receiving information that the environment scene of the smart helmet, as determined by the analysis and identification of the environmental information, is a non-sensitive scene and / or that the order status of the order delivery task is in delivery status, the system controls the image acquisition unit to start acquiring images and controls the occlusion unit to keep the image acquisition unit in an unoccluded state.

[0010] Optionally, upon receiving information that the environment scene of the smart helmet, as determined through analysis and identification of the environmental information, conforms to a non-sensitive scene and / or that the order status of the order delivery task is in delivery status, the system controls the image acquisition unit to start acquiring images and controls the occlusion unit to ensure the image acquisition unit is in an unoccluded state, including: When the location area of ​​the smart helmet related to the order delivery task is identified as a non-sensitive location and / or the environment characterized by the environmental perception parameters of the smart helmet is identified as a non-sensitive environment, the image acquisition unit is controlled to acquire images and the occlusion unit is controlled to keep the image acquisition unit in an unoccluded state; the non-sensitive scene includes the non-sensitive location and / or the non-sensitive environment.

[0011] Secondly, this disclosure provides a smart helmet, which is equipped with a scene recognition unit, a main control unit, an image acquisition unit, and an occlusion unit; The image acquisition unit is used to acquire environmental images around the smart helmet; The scene recognition unit is used to acquire the environmental information of the smart helmet. When it receives a scene where the environment of the smart helmet is located after the environmental information is analyzed and identified and it is determined to be a sensitive scene, it sends a privacy occlusion signal to the main control unit. The environmental information is used to characterize the environmental information of the smart helmet in the scenario where the user wearing the smart helmet is performing an order delivery task. The sensitive scene is a scene involving sensitive information of a person or organization. The main control unit is used to respond to the privacy occlusion signal, control the image acquisition unit to stop image acquisition, and / or control the occlusion unit to put the image acquisition unit in an occluded state.

[0012] Optionally, the blocking unit includes a blocking component and a driving component, wherein the blocking component is movably mounted on the smart helmet; The driving component is electrically connected to the main control unit, and the output terminal of the driving component is connected to the blocking component. The driving component is used to control the blocking component to move in front of the acquisition area of ​​the image acquisition unit so that the image acquisition unit is in a blocked state.

[0013] Optionally, the blocking component includes a rotating component, and the driving component includes a first driving component. The output end of the first driving component is connected to the rotating component. The first driving component is used to drive the rotating component to rotate in front of the acquisition area of ​​the image acquisition unit, so that the image acquisition unit is in a blocked state.

[0014] Optionally, the blocking component includes a sliding component, and the driving component includes a second driving component. The output end of the second driving component is connected to the sliding component. The second driving component is used to drive the sliding component to slide in front of the acquisition area of ​​the image acquisition unit so that the image acquisition unit is in a blocked state.

[0015] Through the above technical solution, in scenarios where the environment in which the smart helmet is located is identified as a sensitive scenario—that is, when it is detected that sensitive information of individuals or organizations may exist in the environment in which the smart helmet is located—the image acquisition unit on the smart helmet can be controlled to stop image acquisition, and / or the occlusion unit can be controlled to occlude the image acquisition unit. Thus, when the image acquisition unit stops image acquisition and / or is in an occluded state, it cannot continue to acquire environmental images around the smart helmet, thereby protecting the sensitive information of individuals and / or organizations in the vicinity of the smart helmet in sensitive scenarios. Furthermore, the smart helmet of this application can also automatically control the start / stop or opening / closing of the image acquisition / occlusion unit based on the delivery status of the delivery capacity and the relationship between the current location and the delivery route, combined with the autonomous identification and judgment of sensitive scenarios. It has scene judgment and autonomous control capabilities, and is intelligent.

[0016] Other features and advantages of this disclosure will be described in detail in the following detailed description section. Attached Figure Description

[0017] The accompanying drawings are provided to further illustrate the present disclosure and form part of the specification. They are used together with the following detailed description to explain the present disclosure, but do not constitute a limitation thereof. In the drawings: Figure 1 This is a flowchart of the steps of a control method for a smart helmet according to an exemplary embodiment; Figure 2 This is a flowchart of the steps of a control method for a smart helmet according to an exemplary embodiment; Figure 3 This is an example of a region centered on a delivery address, proposed according to an exemplary embodiment. Figure 4 This is a schematic diagram illustrating the regions corresponding to various geographic identifiers, according to an exemplary embodiment. Figure 5 This is a flowchart of the steps of a control method for a smart helmet according to an exemplary embodiment; Figure 6 This is a flowchart of the steps of a control method for a smart helmet according to an exemplary embodiment; Figure 7 This is a schematic diagram illustrating the interaction between a main control unit and a scene recognition unit and an occlusion unit, according to an exemplary embodiment. Figure 8 This is a schematic diagram of an electrochromic sheet according to an exemplary embodiment; Figure 9 This is a schematic diagram of a shielding component according to an exemplary embodiment; Figure 10This is a schematic diagram of one structure of a shielding component according to an exemplary embodiment; Figure 11 This is a schematic diagram of another structure of a shielding component according to an exemplary embodiment; Figure 12 This is a schematic diagram of an electronic device according to an exemplary embodiment; Figure 13 This is a schematic diagram of an electronic device according to an exemplary embodiment. Detailed Implementation

[0018] The specific embodiments of this disclosure will be described in detail below with reference to the accompanying drawings. It should be understood that the specific embodiments described herein are for illustration and explanation only and are not intended to limit this disclosure.

[0019] It should be noted that all actions involving the acquisition of signals, information, or data in this disclosure are carried out in compliance with the relevant data protection laws and policies of the country where the location is situated, and with authorization from the owner of the relevant device.

[0020] Figure 1 This embodiment illustrates a control method for a smart helmet. This method can be applied to a smart helmet, a terminal communicating with the smart helmet (e.g., a mobile phone), or a server communicating with the smart helmet. The smart helmet is equipped with an image acquisition unit and an occlusion unit. The image acquisition unit is used to acquire environmental images around the smart helmet, and the occlusion unit is used to obstruct the field of view of the image acquisition unit. See also... Figure 1 As shown, the control method of this smart helmet includes the following steps: S101, Obtain the environmental information of the smart helmet.

[0021] Among them, smart helmets are helmets that can realize functions such as image acquisition and real-time image transmission. They are often used by delivery personnel to wear smart helmets when performing order delivery tasks, and are intelligent protective structures to protect the heads of delivery personnel.

[0022] The image acquisition unit can be a camera configured on the smart helmet. The field of view of the image acquisition unit is oriented towards at least one of the front, back, left, and right directions of the smart helmet, and can be used to realize the image acquisition functions required in delivery order scenarios such as road condition shooting, code scanning, and evidence collection.

[0023] The occlusion unit is a mechanical structure mounted on the smart helmet. It is used to automatically occlude the field of view of the image acquisition unit after the smart helmet enters a sensitive scene, so that the field of view of the image acquisition unit is occluded.

[0024] The environmental information of the smart helmet is used to characterize the environment in which the smart helmet is located when a delivery worker wearing the smart helmet is carrying out an order delivery task. This order delivery task is an order delivery task being executed by a terminal communicating with the smart helmet while the delivery worker is wearing the smart helmet. The order delivery task is associated with both the smart helmet and the terminal. The environmental information of the smart helmet characterizes the environmental features surrounding the smart helmet when the delivery worker is carrying out the order delivery task. This environmental information may include environmental images, environmental sounds, geographical location, and other information.

[0025] S102, upon receiving that the environment scene of the smart helmet, as determined by the analysis and identification of the environmental information, conforms to a sensitive scene, the image acquisition unit is controlled to stop image acquisition, and / or the occlusion unit is controlled to put the image acquisition unit in an occluded state.

[0026] The executor of analyzing environmental information to identify whether the environment in which the smart helmet is located is a sensitive scene can be determined by at least one of the smart helmet, a terminal communicating with the smart helmet, or a server. The smart helmet can analyze and identify whether the environment in which it is located meets the criteria for a sensitive scene on its own, or it can receive the analysis result of whether the environment in which the smart helmet is located meets the criteria for a sensitive scene sent by the terminal, or it can receive the analysis result of whether the environment in which the smart helmet is located meets the criteria for a sensitive scene forwarded by the terminal from the server, or it can receive the analysis result of whether the environment in which the smart helmet is located meets the criteria for a sensitive scene from the server.

[0027] For example, taking the server as the executor of the parsing results, the smart helmet can detect the environment in which the smart helmet is located and send the current environment to the server. The server compares the environment with the pre-configured sensitive scenes in the environment scene rule database. If the server identifies the environment as a sensitive scene, it can send a stop acquisition signal to the smart helmet. In response to the stop acquisition signal, the smart helmet controls the image acquisition unit to stop image acquisition and / or controls the occlusion unit to put the image acquisition unit in an occluded state.

[0028] The environmental scenarios in which the smart helmet is located include the geographical environment, time environment, audio environment, and air environment.

[0029] Sensitive scenarios refer to those involving sensitive information of individuals or organizations. Sensitive personal information can include at least one of the following: personal privacy behavior data or privacy identity data. Privacy behavior data includes an individual's private space, whereabouts, health data, and financial data; privacy identity data includes an individual's identity and biometric characteristics. Sensitive organizational information may involve organizational research data or technical information, such as organizational secrets, core technologies (e.g., technical seminars), and customer lists. Private spaces can be private spaces such as toilets, bathhouses, and residential homes, where individuals may engage in private activities that involve their privacy.

[0030] The control of the image acquisition unit to stop image acquisition includes at least one method for stopping image acquisition: controlling the image acquisition unit to pause image acquisition, or controlling the image acquisition unit to stop running and be in a closed state.

[0031] The occlusion unit includes at least one of the following implementation methods: Firstly, there's the electrochromic film, which covers the image acquisition unit's field of view. In environments identified as sensitive by the smart helmet, the film switches between transparent and opaque states. In the transparent state, the image acquisition unit is unobstructed; in the opaque state, it is obstructed. However, to prevent others from mistakenly believing the film is being taken, the electrochromic film's color in the opaque state can be configured to match the smart helmet's color. This ensures that when the image acquisition unit is obstructed, the electrochromic film remains the same color as the smart helmet, preventing it from attracting attention or causing misunderstandings.

[0032] Secondly, the obstruction component is installed on the smart helmet and can move on the smart helmet. In scenarios where the environment of the smart helmet is identified as a sensitive scene, the obstruction component can be controlled to move in front of the smart helmet's acquisition area, thereby making the image acquisition unit obstructed.

[0033] Optionally, the smart helmet can also be equipped with an audio acquisition unit, which is used to collect ambient sounds around the smart helmet. It can also control the audio acquisition unit to stop audio acquisition when it receives the environmental scene of the smart helmet after the environmental information is analyzed and identified as a sensitive scene.

[0034] Through the above technical solution, in scenarios where the environment in which the smart helmet is located is identified as a sensitive scenario—that is, when it is recognized that there may be sensitive information of individuals or organizations in the environment in which the smart helmet is located—the image acquisition unit on the smart helmet can be controlled to stop image acquisition, and / or the occlusion unit can be controlled to put the image acquisition unit in an occluded state. In this way, when the image acquisition unit stops image acquisition and / or is in an occluded state, it cannot continue to acquire environmental images around the smart helmet, thereby protecting the sensitive information of individuals or organizations in the surrounding area when the smart helmet is in a sensitive scenario, and solving the problem of abuse of the image acquisition unit on the smart helmet.

[0035] Figure 2 This is an exemplary embodiment involving step S102 above, which is used to interpret an exemplary embodiment of controlling the image acquisition unit to stop image acquisition and / or controlling the occlusion unit to put the image acquisition unit in an occluded state in a sensitive scene including a sensitive location and / or a sensitive environment, including the following steps: S102-1, if the location area of ​​the smart helmet related to the order delivery task is identified as the sensitive location and / or the environment represented by the environmental perception parameters of the smart helmet related to the order delivery task is identified as conforming to the sensitive environment, the image acquisition unit is controlled to stop image acquisition and / or the occlusion unit is controlled to put the image acquisition unit in an occluded state.

[0036] The location area related to the order delivery task includes the location area around the delivery address indicated on the order delivery task and / or the location area traversed by the delivery capacity during the order delivery task. This location area can be a specific geographical location or an area range divided with the geographical location as the center and a preset distance as the radius.

[0037] Understandably, determining whether delivery capacity has reached the delivery address of an order can be achieved through at least one of the following methods: First, obtain the delivery address specified in the order delivery task from the regional map and detect the current location of the smart helmet. If the current location of the smart helmet reaches the delivery address, then the delivery capacity has reached the delivery address of the order delivery task. Second, detect the delivery status of the order delivery task on the smart helmet's communication terminal. If the delivery status indicates that the order has been delivered, then the delivery capacity has reached the delivery address of the order delivery task. Third, detect the communication content of the smart helmet's communication terminal. If the communication content contains key audio words related to the current order delivery task indicating that delivery has arrived, then the delivery capacity has reached the delivery address of the order delivery task.

[0038] Sensitive locations are areas or specific geographical locations that involve personal or organizational sensitive privacy, including areas of personal and / or organizational sensitive privacy.

[0039] The personal sensitive privacy area includes the area where the smart helmet is located within a preset distance from the delivery address specified in the order delivery task, and / or the personal privacy area traversed by the delivery vehicle during the order delivery task. The delivery address may include the order's delivery location and / or pickup location and / or intermediate points along the order delivery route. For example, if the order delivery task specifies delivery to a user's residential location A, then the personal sensitive privacy area includes the area within a certain distance of the user's residential location A and / or intermediate points traversed by the delivery vehicle along the route when delivering the order, such as toilets, bathrooms, washrooms, hotels, nursing rooms, and other areas involving personal privacy. For example, during the delivery vehicle's execution of the order delivery task, environmental information around the smart helmet can be acquired. Upon receiving information that the environment scene where the smart helmet is located, identified through analysis of the environmental information, is within the delivery location and / or pickup location, the image acquisition device can be controlled to stop image acquisition, and / or the occlusion unit can be controlled to occlude the image acquisition unit.

[0040] Organizational sensitive privacy areas are areas within the organization where unauthorized personnel are restricted from entering. These include military facilities, production workshops, technical seminars, examination rooms, neonatal intensive care units, and other areas where unauthorized personnel are prohibited from entering.

[0041] For example, during the delivery process, environmental information around the smart helmet can be acquired. If the environment of the smart helmet is located in an area where unauthorized personnel are restricted, the image acquisition device can be controlled to stop image acquisition, and / or the occlusion unit can be controlled to put the image acquisition unit in an occluded state.

[0042] Optionally, if the location area of ​​the smart helmet related to the order delivery task is identified as belonging to the personal sensitive privacy area and / or the organization's sensitive privacy area, the image acquisition unit may be controlled to stop image acquisition and / or the occlusion unit may be controlled to put the image acquisition unit in an occluded state.

[0043] The location area of ​​the smart helmet related to the order delivery task can be the current location of the smart helmet worn by the delivery personnel performing the order delivery task, or the location area that will be entered when delivering the order according to the planned delivery route. The current location area of ​​the smart helmet can be obtained through the positioning unit of the smart helmet or the smart helmet communication terminal. The location area to be entered can be obtained through the current delivery route of the delivery personnel and the map related to the delivery route. The map marks the location area of ​​each travel point on the delivery route. When the delivery personnel travels to the previous location area, the next geographical area adjacent to the previous travel point on the delivery route can be determined by the delivery route on the map. Therefore, if the location area of ​​the smart helmet related to the order delivery task is identified as belonging to the personal sensitive privacy area and / or the organizational sensitive privacy area, controlling the image acquisition unit to stop image acquisition and / or controlling the occlusion unit to put the image acquisition unit in an occluded state includes: if, during the execution of the order delivery task, the delivery personnel wearing the smart helmet are currently located in or about to enter a location area identified as a personal sensitive privacy area and / or the organizational sensitive privacy area, controlling the image acquisition unit to stop image acquisition and / or controlling the occlusion unit to put the image acquisition unit in an occluded state.

[0044] In some scenarios, refer to Figure 3 As shown, taking a preset distance of 20m as an example, and the personal sensitive privacy area being the area centered on the user's residential location A specified in the order delivery task, with a preset distance of 20m as the radius, if the delivery personnel wearing smart helmets detect that the area the smart helmet is about to enter is within the personal privacy area of ​​the user's residential location A within 20m, for example... Figure 3 If the delivery capacity is about to enter the private area indicated by the dashed circle, the image acquisition unit can be controlled to stop image acquisition and / or the occlusion unit can be controlled to put the image acquisition unit in an occluded state, thereby preventing the image acquisition unit from capturing images of the private area within the user's residential location A.

[0045] In some scenarios, taking a toilet as an example of a sensitive area of ​​personal privacy, if a delivery person wearing a smart helmet goes to the toilet while delivering an order to a user's residence A, and the smart helmet is detected to be located in the vicinity of the toilet, the image acquisition unit can be controlled to stop image acquisition and / or the occlusion unit can be controlled to occlude the image acquisition unit, thereby preventing the image acquisition unit from capturing images of the toilet environment and the personal privacy of other people.

[0046] In some scenarios, taking a military industrial area as an example, when delivery personnel wearing smart helmets deliver orders to or through a military industrial area, if it is detected that the location of the smart helmet is too close to the military industrial area, the image acquisition unit can be automatically controlled to stop image acquisition and / or the occlusion unit can be controlled to put the image acquisition unit in an occluded state, thereby preventing the image acquisition unit from capturing the organization's privacy information in the military industrial area.

[0047] Among them, the environmental perception parameters related to the order delivery task include the environmental perception parameters around the delivery address indicated on the order delivery task and / or the environmental perception parameters of the area traversed by the delivery force during the order delivery task. These environmental perception parameters are used to characterize the delivery environment around the smart helmet when the delivery force is wearing the smart helmet to deliver the order. These environmental perception parameters include environmental images, environmental audio, physical features of surrounding buildings, environmental networks, geographic identifiers, etc.

[0048] A sensitive environment is a set of environmental features involving sensitive information of an individual or organization. The sensitive environment may include at least one of the following: bathroom environmental features, home wireless network, sensitive entity features, sensitive geographic identifiers, sensitive image features, and sensitive audio words.

[0049] Optionally, the temperature and humidity information of the location area of ​​the smart helmet related to the order delivery task is obtained. If the spatial environment characteristics represented by the temperature and humidity information related to the order delivery task are determined to be the bathroom environment characteristics, the sensitive environment of the smart helmet is determined to be a sensitive privacy environment, and the image acquisition unit is controlled to stop image acquisition and / or the occlusion unit is controlled to put the image acquisition unit in an occluded state.

[0050] Among them, the spatial environmental characteristics represented by temperature and humidity information are used to indicate the physical environmental characteristics of the place where the temperature and humidity information exists, such as the physical environmental characteristics of the building appearance and tile texture of the place where the temperature and humidity information exists; the bathroom environmental characteristics are spatial environments with specific temperature and humidity conditions. The temperature and humidity in physical spaces with bathroom environmental characteristics are generally higher than those in physical spaces without bathroom environmental characteristics.

[0051] Among them, sensitive privacy environments are spatial environments where personal privacy behaviors or physical privacy characteristics may occur. For example, such sensitive privacy environments may be spaces where personal privacy behaviors occur, such as toilets and bathrooms.

[0052] Among them, the temperature and humidity information of the location area related to the order delivery task where the smart helmet is located can be identified by an infrared sensing unit. After the infrared sensing unit is turned on, it can sense the temperature and humidity information around the smart helmet in real time.

[0053] The temperature and humidity information related to the order delivery task is used to characterize the temperature and humidity around the smart helmet during the delivery personnel's order delivery task. This information includes the temperature and / or humidity around the smart helmet. Typically, the temperature in a bathroom is higher than in a non-bathroom environment, and / or the humidity in a bathroom is higher than in a non-bathroom environment. Therefore, if the temperature and / or humidity around the smart helmet are detected to be higher than a preset temperature and / or a preset humidity during the delivery personnel's order delivery task, the spatial environment around the smart helmet is considered to be a bathroom environment. In this case, to protect personal privacy in the bathroom, the image acquisition unit can be controlled to stop image acquisition and / or the occlusion unit can be controlled to occlude the image acquisition unit, thereby preventing the image acquisition unit from acquiring images of the bathroom.

[0054] The preset temperature is the critical condition for whether the smart helmet is in a high-temperature environment. If the temperature around the smart helmet is higher than the preset temperature, it is considered to be in a high-temperature environment. Similarly, the preset humidity is the critical condition for whether the smart helmet is in a high-humidity environment. If the humidity around the smart helmet is higher than the preset humidity, it is considered to be in a high-humidity environment. Of course, the preset temperature can be adjusted according to seasonal changes. For example, if the current time is summer, when ambient temperatures are generally high, the preset temperature can be increased to better reflect summer temperatures. Conversely, if the current time is winter, when ambient temperatures are generally low, the preset temperature can be decreased to better reflect winter temperatures.

[0055] Optionally, the wireless network of the location area related to the order delivery task where the smart helmet is located is obtained. If the wireless network of the location area related to the order delivery task is a home wireless network, the sensitive environment where the smart helmet is located is determined to be a sensitive network environment, and the image acquisition unit is controlled to stop image acquisition and / or the occlusion unit is controlled to put the image acquisition unit in an occluded state.

[0056] Home wireless networks are private networks, which are network systems established within a home that can achieve network sharing and data transmission without physical cable connections. They can be used by authorized personnel (such as home users or authorized visitors). Home wireless networks typically cover private residences, unlike public networks which can cover large public places such as shopping malls and schools. Public networks are open networks with network sharing capabilities.

[0057] Among them, the sensitive network environment is used to characterize the network environment in which the terminal connected to the smart helmet or the smart helmet itself is located, which is a non-public private wireless network or a home user wireless network.

[0058] The wireless network in the location area related to the smart helmet's order delivery task can be the wireless network of the delivery address specified in the order delivery task. This wireless network can be a Wi-Fi network or a Bluetooth network, or other wireless local area network. If the wireless network of the delivery address specified in the order delivery task is a home wireless network, it means that the delivery address specified in the order delivery task is a home address or a private user address. To protect user privacy, the image acquisition unit can be controlled to stop image acquisition and / or the occlusion unit can be controlled to put the image acquisition unit in an occluded state, thereby preventing the image acquisition unit from acquiring images of the residential environment inside a home or private residence.

[0059] Among them, a blacklist can be pre-configured in the preset database. The blacklist records wireless networks that can be detected by the smart helmet but will not be identified as home wireless networks. For example, when public wireless networks such as those in supermarkets, stores, restaurants, and passersby Wi-Fi hotspots are detected, they will not be identified as home wireless networks.

[0060] Therefore, determining whether the wireless network in the location area related to the order delivery task is a home network includes: determining whether the wireless network in the location area related to the order delivery task is outside the blacklist; if it is outside the blacklist, then determining whether the network strength of the detected wireless network is greater than a preset strength; if it is greater than the preset strength, it means that the delivery capacity is near a home or private residence, and it can be determined that the current sensitive environment of the smart helmet is a sensitive network environment, thereby controlling the image acquisition unit to stop image acquisition and / or controlling the occlusion unit to put the image acquisition unit in an occluded state.

[0061] Optionally, entity features of the location area of ​​the smart helmet related to the order delivery task are obtained. If the entity features of the location area related to the order delivery task are sensitive entity features within an isolated privacy area, the sensitive environment of the smart helmet is determined to be a sensitive entity environment. The image acquisition unit is then controlled to stop image acquisition and / or the occlusion unit is controlled to put the image acquisition unit in an occluded state.

[0062] Among them, the isolated privacy area is a private area that is isolated from public places to restrict the entry of certain personnel. This isolated privacy area can be a residential house, bathroom, toilet, military industrial site, or hospital ward.

[0063] Among them, sensitive entity features are the distinctive features of entities within the isolated privacy area. These distinctive features of entities can be used to determine the type of isolated privacy area they represent. For example, by obtaining distinctive features of the texture, outline, structure, material, logo, layout, and lighting of entities such as buildings and furniture, it can be determined that the type of isolated privacy area represented by these distinctive features is a hospital ward.

[0064] The meaning of "sensitive physical environment" is the same as that of "isolated privacy area". A sensitive physical environment is an environment with sensitive physical characteristics. Sensitive physical environments can be residential buildings, bathrooms, toilets, military industrial sites, hospital wards, etc.

[0065] Among them, the entity features of the location area related to the order delivery task where the smart helmet is located can be obtained by the image acquisition unit. The environmental images acquired by the image acquisition unit will contain entity features of different entities.

[0066] Among them, the entity features of the location area of ​​the smart helmet related to the order delivery task can be the entity features of the location area specified in the order delivery task or the location area along the order delivery process, or the entity features of the location area along the delivery process.

[0067] For example, if a toilet sign is detected in the physical features of the area where the smart helmet is located, the sensitive environment of the smart helmet is determined to be a sensitive physical environment of a toilet. The image acquisition unit is then controlled to stop image acquisition and / or the occlusion unit is controlled to put the image acquisition unit in an occluded state, thereby preventing the image acquisition unit from capturing images of the environment inside the toilet and thus protecting the privacy of the toilet.

[0068] For example, if the location of the smart helmet is identified as containing the light and shadow features of a residential building or a house number, the sensitive environment of the smart helmet is determined to be a sensitive physical environment of a residential building. The image acquisition unit is then controlled to stop image acquisition and / or the occlusion unit is controlled to put the image acquisition unit in an occluded state, thereby preventing the image acquisition unit from capturing environmental images inside the residential building and thus protecting the privacy of the residential building.

[0069] It is also possible to pre-configure sensitive entity features within different types of isolated privacy areas in the rule database. After obtaining the entity features of the current location area of ​​the smart helmet, the similarity between the entity features and the sensitive entity features within each type of isolated privacy area is determined. From multiple similarities, the isolated privacy area with the highest similarity is selected as the sensitive entity environment where the smart helmet is currently located.

[0070] Optionally, a regional map of the location area related to the order delivery task is obtained. If there are sensitive geographic markers in the regional map of the location area related to the order delivery task, and the location area of ​​the smart helmet related to the order delivery task is about to enter the sensitive geographic location represented by the sensitive geographic marker, the sensitive environment where the smart helmet is located is determined to be a sensitive geographic environment. The image acquisition unit is then controlled to stop image acquisition and / or the occlusion unit is controlled to put the image acquisition unit in an occluded state.

[0071] The map of this area can be obtained from third-party software, and this disclosure does not impose any restrictions on it.

[0072] The location map related to the order delivery task can be a map of the area around the delivery route planned by the delivery capacity during the execution of the order delivery task. This map includes the location area of ​​each travel point on the delivery route and the distribution of buildings around the location area of ​​each travel point. The location area related to the order delivery task can be the location area where the smart helmet is currently located.

[0073] Sensitive geographic markers refer to geographic markers on regional maps that isolate private areas, such as toilets, military industrial areas, family residences, research institutes, etc. These sensitive geographic markers can be the names and / or symbols of sensitive locations. For example, such sensitive geographic markers could be geographical names like "XX Street YY Gate," "ZZ Research Institute," or toilet signs.

[0074] Among them, the sensitive environment of the smart helmet is the sensitive geographical environment used to characterize whether the delivery personnel wearing the smart helmet are in the isolated privacy area or about to enter the isolated privacy area.

[0075] Furthermore, each geographic identifier corresponds to a specific geographical location with its own regional extent or geographical boundaries on the regional map. (See [reference]). Figure 4 As shown, Figure 4The dotted lines in the map represent the delivery routes planned for executing delivery orders. This area map includes the geographical boundaries of the residential area containing Gate YY on XX Street, the ZZ Research Institute, and the restrooms. If the smart helmet's delivery personnel are currently located within or about to enter the geographical boundaries corresponding to sensitive geographical markers during the delivery process, the image acquisition unit can be controlled to stop image acquisition, and / or the occlusion unit can be controlled to occlude the image acquisition unit. For example, when the delivery personnel are about to enter the geographical boundary of the residential area containing Gate YY on XX Street according to the delivery route, the image acquisition unit can be controlled to stop image acquisition, and / or the occlusion unit can be controlled to occlude the image acquisition unit. This prevents the image acquisition unit from capturing environmental images around the sensitive geographical locations corresponding to the sensitive geographical markers, thus protecting the privacy of the sensitive geographical locations.

[0076] Different types of sensitive geographic identifiers for isolated privacy areas can be pre-configured in the rules database. After obtaining the current location of the smart helmet, the positional relationship between the location and the geographic boundaries represented by the sensitive geographic identifiers of each isolated privacy area is determined. If the distance between the location and the geographic boundary represented by the sensitive geographic identifier of a certain isolated privacy area is less than a preset distance, and the next travel point of the delivery route planned by the delivery capacity is located within the geographic boundary, it can be determined that the smart helmet is about to enter the isolated privacy area. Therefore, it can be determined that the smart helmet is currently in a sensitive geographic environment.

[0077] Optionally, an environmental image of the location area of ​​the smart helmet related to the order delivery task is acquired. If there are sensitive image features in the environmental image related to the order delivery task, the sensitive environment of the smart helmet is determined to be a sensitive visual environment, and the image acquisition unit is controlled to stop image acquisition and / or the occlusion unit is controlled to put the image acquisition unit in an occluded state.

[0078] Sensitive image features are image features related to personal or organizational privacy data. For example, sensitive image features can be image features related to human biometrics, documents (such as ID cards, bank cards, and qualification certificates), technical data, and other personal identity and property information.

[0079] The sensitive visual environment is used to characterize image features that are visually sensitive and involve privacy concerns. When delivery personnel wear smart helmets to deliver orders, if the environmental image captured by the image acquisition unit contains sensitive image features such as ID cards, bank cards, or qualification certificates, the system will control the image acquisition unit to stop image acquisition and / or control the occlusion unit to occlude the image acquisition unit, thereby preventing the leakage of user or organization's confidential image data.

[0080] Optionally, the ambient audio of the location area of ​​the smart helmet related to the order delivery task is acquired. If there are sensitive audio words in the ambient audio related to the order delivery task, the sensitive environment of the smart helmet is determined to be a sensitive audio environment, and the image acquisition unit is controlled to stop image acquisition and / or the occlusion unit is controlled to put the image acquisition unit in an occluded state.

[0081] Among them, ambient audio can be collected by an audio acquisition unit configured on the smart helmet.

[0082] Sensitive audio words are those that involve the privacy or secrets of individuals or organizations. For example, these sensitive audio words are related to private topics such as academic conferences, technical seminars, user calls, and user interactions.

[0083] The sensitive audio environment is used to characterize the physical environment in which sensitive audio words are present in the collected audio. During order delivery tasks while delivery personnel wear smart helmets, if the environmental audio collected by the audio acquisition unit contains private sensitive audio words such as those from academic conferences, technical seminars, user calls, or user interactions, the system will control the image acquisition unit to stop image acquisition and / or control the occlusion unit to occlude the image acquisition unit, thereby preventing the leakage of user or organization privacy.

[0084] Optionally, the temperature and humidity information, wireless network, entity features, area map, environmental images, and environmental audio features mentioned above can be combined to more accurately determine whether the environment in which the smart helmet is currently located is a sensitive environment.

[0085] For example, wireless networks, environmental images, and environmental audio can be combined. If the wireless network in the area where the smart helmet is located is a home wireless network, environmental audio triggered by opening a door or doorbell is detected, and sensitive physical features of a home are detected in the environmental image, it indicates that the delivery capacity has delivered the order to the user's doorstep, and the user has opened the door to sign for the takeout or package. At this time, it can be determined that the smart helmet is in a sensitive environment. The image acquisition unit can be controlled to stop the image acquisition box unit or the occlusion unit can be controlled to put the image acquisition unit in an occluded state, thereby protecting the user's home environment from privacy leaks.

[0086] For example, temperature and humidity information can be combined with environmental images. If the spatial environmental characteristics represented by the temperature and humidity information of the area where the smart helmet is located are bathroom environmental characteristics and / or there are sensitive entity characteristics of a bathroom in the environmental image, it indicates that the delivery force has entered the bathroom. At this time, it can be determined that the smart helmet is in a sensitive environment. The image acquisition unit can be controlled to stop the image acquisition unit or the occlusion unit can be controlled to make the image acquisition unit occluded, thereby protecting the privacy of the bathroom environment from leakage.

[0087] For example, temperature and humidity information can be combined with sensitive geographic identifiers. If the spatial environmental characteristics represented by the temperature and humidity information of the smart helmet's location area are bathroom environmental characteristics and / or the smart helmet's location area is a sensitive address location corresponding to a toilet identifier, it indicates that the delivery force has entered the bathroom. At this time, it can be determined that the smart helmet is in a sensitive environment. The image acquisition unit can be controlled to stop the image acquisition unit or the occlusion unit can be controlled to make the image acquisition unit in an occluded state, thereby protecting the privacy of the bathroom environment from leakage.

[0088] Of course, the above solution can also be combined with the order delivery status. For example, when the order delivery status is in delivery and the smart helmet is in a sensitive environment, the image acquisition unit can be controlled to stop the image acquisition unit or the occlusion unit can be controlled to make the image acquisition unit in an occluded state, which can protect the privacy of the delivery personnel in the sensitive environment around the order delivery process.

[0089] For example, if the order delivery status is "arrived" and the wireless network in the area where the smart helmet is located is a home wireless network, it means that the delivery force has delivered the order to the user's doorstep. At this time, it can be determined that the smart helmet is in a sensitive environment. The image acquisition unit can be controlled to stop the image acquisition box unit or the occlusion unit can be controlled to make the image acquisition unit occluded, thereby protecting the user's home environment from privacy leaks.

[0090] Optionally, a rule database can be pre-configured to store sensitive location and sensitive environment perception parameters. After obtaining the location area of ​​the smart helmet, the location area is compared with the sensitive locations stored in the rule database to determine whether the location area of ​​the smart helmet is a sensitive location. Alternatively, after obtaining the environmental perception parameters around the smart helmet, the environmental perception parameters are compared with the sensitive environment perception parameters of the sensitive environment stored in the rule database to determine whether the environment in which the smart helmet is located is a sensitive environment.

[0091] The rules database can be configured in the cloud, on a terminal, or in a smart helmet. Programmers or delivery personnel can update sensitive locations and environments in the rules database.

[0092] For example, delivery personnel can collect environmental images through smart terminals and / or upload the geographical location of the environmental images as a sensitive location to a rule database. For instance, if a "No Photography" sign is clearly posted on the building of Unit XX, the delivery personnel can upload the "No Photography" sign and the geographical location of Unit XX to the rule database. Subsequently, when other delivery personnel enter Unit XX, if the system detects that the delivery personnel wearing smart helmets are located in or about to enter Unit XX, it will automatically control the image acquisition unit or the occlusion unit to obstruct the image acquisition unit, thereby protecting the privacy of Unit XX.

[0093] Through the above technical solution, when the location area of ​​the smart helmet related to the order delivery task is identified as a sensitive location and / or the environment represented by the environmental perception parameters related to the order delivery task is identified as a sensitive environment, the image acquisition unit can be controlled to stop image acquisition and / or the occlusion unit can be controlled to put the image acquisition unit in an occluded state. Firstly, it provides a multi-dimensional scene recognition method, which can automatically control the image acquisition unit to stop image acquisition and / or control the occlusion unit to block the image acquisition unit when delivery personnel enter private places such as toilets and bathrooms, or pass through military industrial areas, thus eliminating the need for manual operation by delivery personnel and effectively preventing privacy leaks. Secondly, the sensitive locations and / or sensitive environments in the rule database support the adjustment of delivery personnel according to the personalized needs of different places. For example, sensitive locations and / or sensitive environments of a community or a residential user can be personalized, so that when subsequent delivery orders reach the previously configured sensitive locations and / or sensitive environments, the image acquisition unit can be actively controlled to stop image acquisition and / or the occlusion unit can be controlled to block the image acquisition unit, solving the problem of poor universality of sensitive locations and / or sensitive environments.

[0094] Figure 5 This is an exemplary embodiment of the present disclosure, which is used to interpret an exemplary scheme for controlling an image acquisition unit to acquire images, including the following steps: S103, if the environmental scene represented by the environmental image and / or environmental audio is identified as a conflict scene, the image acquisition unit is controlled to acquire an image and the occlusion unit is controlled to keep the image acquisition unit in an unoccluded state.

[0095] Optionally, if the environmental scene represented by the environmental image and / or environmental audio is identified as a conflict scene, the image acquisition unit can be controlled to acquire images, the occlusion unit can be controlled to make the image acquisition unit unoccluded, and the audio acquisition unit can be controlled to acquire audio.

[0096] For example, when the environmental scene represented by the environmental image is a conflict scene, the audio acquisition unit can be controlled to synchronously acquire audio.

[0097] For example, when the environmental scene represented by the environmental audio is a conflict scene, the image acquisition unit can be controlled to acquire images synchronously, and the occlusion unit can be controlled to keep the image acquisition unit in an unoccluded state.

[0098] This includes the environmental image and / or the environmental audio.

[0099] Among them, conflict scenarios include confrontational communication scenarios in interpersonal communication, such as verbal abuse, physical assault, and vehicle collisions.

[0100] The occlusion unit, which puts the image acquisition unit in an unoccluded state, is used to indicate that the occlusion unit has moved away from the acquisition field of the image acquisition unit.

[0101] Through the above technical solution, when environmental images and / or environmental audio are collected in a conflict scenario, the image acquisition unit can be controlled to acquire images and the occlusion unit can be controlled to keep the image acquisition unit in an unoccluded state, thereby capturing on-site image information and audio information, providing direct audio and video evidence for subsequent event tracing and problem investigation.

[0102] Figure 6 This is an exemplary embodiment of the present disclosure, which is used to interpret the steps of a control method for an image acquisition unit when the control environment scenario is a non-sensitive scenario and / or the order status of the order delivery task is in the delivery status, including the following steps: S104, upon receiving that the environment scene where the smart helmet is located is a non-sensitive scene and / or the order status of the order delivery task is a delivery status, after analyzing and identifying the environmental information, the image acquisition unit is controlled to start acquiring images and the occlusion unit is controlled to make the image acquisition unit in an unoccluded state.

[0103] The environmental scene in which the smart helmet is located, as determined by the analysis and identification of the environmental information, is a non-sensitive scene. The executor can be the smart helmet, a server communicating with the smart helmet, or a terminal communicating with the smart helmet.

[0104] For example, the current environment of the smart helmet can be detected and sent to the server. The server compares the current environment with the pre-configured non-sensitive scenes in the environment scene rule database. The terminal communicating with the smart helmet can also send the order status of the order delivery task to the server. If the server recognizes that the environment is a non-sensitive scene and / or the order status of the order delivery task is in the delivery status, it can send a collection signal to the smart helmet. In response to the collection signal, the smart helmet controls the image acquisition unit to start collecting images and controls the occlusion unit to keep the image acquisition unit in an unoccluded state.

[0105] Non-sensitive scenarios include non-sensitive locations and / or non-sensitive environments. Non-sensitive locations are public locations that do not involve the sensitive privacy of individuals or organizations, such as public places like squares, supermarkets, and roadsides. Non-sensitive environments are public environments that do not involve the privacy of individuals or organizations, such as public places like squares, supermarkets, and roadsides.

[0106] Optionally, if the location area of ​​the smart helmet related to the order delivery task is identified as a non-sensitive location and / or the environment characterized by the environmental perception parameters of the smart helmet is identified as a non-sensitive environment, the image acquisition unit can be controlled to acquire images and the occlusion unit can be controlled to keep the image acquisition unit in an unoccluded state.

[0107] For example, the server, or delivery service system, obtains parameters related to the current location area of ​​the smart helmet. These parameters include the location area of ​​the smart helmet and environmental perception parameters of that location area. The server compares this location area with pre-configured non-sensitive locations in the rule scene database and compares the environmental perception parameters of the smart helmet with pre-configured non-sensitive environmental perception parameters in the rule database. If the location area of ​​the smart helmet is identified as a non-sensitive location and / or the environment represented by the environmental perception parameters of the smart helmet is identified as conforming to a non-sensitive environment, the server sends a collection signal to the smart helmet. In response to the collection signal, the smart helmet controls the image acquisition unit to start acquiring images and controls the occlusion unit to keep the image acquisition unit in an unoccluded state.

[0108] Optionally, by querying the delivery orders of the delivery capacity, the delivery route related to the delivery capacity and the order delivery task can be obtained. If the delivery capacity and the order delivery task are located on the delivery route based on the location area obtained by the smart helmet or terminal, and if the environment scene where the smart helmet is located is identified as a non-sensitive scene, the image acquisition unit is automatically controlled to start acquiring images and the occlusion unit is controlled to keep the image acquisition unit in an unoccluded state.

[0109] For example, when a delivery route related to an order delivery task is planned based on the starting point and delivery address of the delivery order using the queried delivery capacity, or when the delivery route planned by the delivery capacity for the order delivery task is obtained on the terminal, and the delivery capacity is determined to be on the delivery route based on the location area obtained by the smart helmet or terminal, and the environment scene where the smart helmet is located is identified as a non-sensitive scene, the image acquisition unit is automatically controlled to start acquiring images, and the occlusion unit is controlled to keep the image acquisition unit in an unoccluded state. Obtaining the delivery route related to the order delivery task based on the delivery order may include: automatically planning the delivery route related to the order delivery task based on the starting point and delivery address in the delivery order, or obtaining the delivery route planned by the delivery capacity for this order delivery task on the terminal.

[0110] Optionally, the delivery service system receives signals transmitted from the smart helmet, obtains the delivery status of the delivery capacity based on the identity identifier of the delivery capacity associated with the smart helmet, and controls the image acquisition unit to stop acquiring images and / or controls the occlusion unit to put the image acquisition unit in an occlusion state when the delivery capacity is in an order-free state.

[0111] Optionally, the delivery service system, based on whether the delivery capacity is in an order-accepting state and whether the smart helmet is on a delivery route for an order delivery task, determines whether to take action to stop the image acquisition unit from acquiring images and / or obstruct the image acquisition unit when the location is in a sensitive or private area. If the system finds that the delivery capacity is in an order-not-accepting state, or that the delivery capacity's current location or route is not related to an order delivery task, the system controls the image acquisition unit not to acquire images. A route not related to an order delivery task can be a route planned by the delivery capacity when it is not performing an order delivery task, such as a route planned by the delivery capacity when it is resting or navigating in a normal non-order-accepting state. It is understood that if it is determined that the smart helmet is on a non-delivery route not related to an order delivery task, it means that the delivery capacity may be going home or resting. To protect the privacy and security of the delivery capacity or to save energy for the smart helmet, the system can control the image acquisition unit not to acquire images.

[0112] When the delivery capacity is online and accepting orders, it means that the delivery capacity has started the order delivery task. The image acquisition unit can be controlled to start acquiring images, and the occlusion unit can be controlled to keep the image acquisition unit in an unobstructed state, so as to meet the needs of order delivery such as video recording, barcode scanning, and delivery evidence collection under normal delivery conditions.

[0113] Optionally, the system can also obtain the order status of the terminal's delivery software and the delivery route related to the order delivery task obtained based on the delivery order. When the order status of the delivery software is obtained as "accepted" and / or the delivery capacity is determined to be on the delivery route based on the location area obtained from the smart helmet or terminal positioning, the system can automatically control the image acquisition unit to start acquiring images and control the occlusion unit to keep the image acquisition unit in an unoccluded state.

[0114] For example, the system can obtain the order status of the delivery software on the terminal and the delivery route related to the order delivery task obtained based on the delivery order, and obtain the location area of ​​the smart helmet. If the order status of the delivery software is in the order acceptance state, and / or the delivery capacity is determined to be at the starting position of the delivery route based on the location area obtained by the smart helmet or terminal positioning, the system can determine that the delivery capacity has accepted the order and start delivering the order. The system can automatically control the image acquisition unit to start acquiring images, and control the occlusion unit to keep the image acquisition unit in an unoccluded state.

[0115] It is understandable that when the delivery capacity is in the order-accepting state and / or the delivery capacity is on the delivery route, it means that the delivery capacity has started the order delivery task. The image acquisition unit can be controlled to start acquiring images and the occlusion unit can be controlled to keep the image acquisition unit in an unoccluded state, so as to meet the needs of order delivery such as video recording, barcode scanning, and delivery evidence collection under normal delivery conditions.

[0116] Through the above technical solutions, the smart helmet can automatically control the start, stop or open / close of the image acquisition / or occlusion unit based on the delivery status of the delivery capacity, the relationship between the current location and the delivery route of the order delivery task, and the autonomous recognition and judgment of sensitive scenes. It has autonomous perception, scene judgment and autonomous control capabilities, and is intelligent. Specifically, firstly, when the delivery personnel are on the delivery route and the environment of the smart helmet is identified as a non-sensitive scene, the image acquisition unit can be controlled to work normally, thereby meeting the needs of order delivery such as video recording, barcode scanning, and delivery evidence collection under normal delivery conditions. Secondly, when the order status of the terminal is "not accepted" and the navigation software of the terminal is traveling on a route related to non-order delivery tasks, it can be determined that the delivery personnel are using terminal navigation without accepting orders, and the image acquisition unit will be controlled to stop image acquisition to protect the personal privacy of the delivery personnel. Thirdly, the order status of the terminal's delivery software and the delivery route related to the order delivery task can also be obtained. When the order status of the delivery software is "accepted" and the location area obtained from the smart helmet or terminal positioning determines that the delivery personnel are on the delivery route, it means that the delivery personnel have accepted the order and started delivery. Therefore, the image acquisition unit can be automatically controlled to automatically acquire images without the delivery personnel having to manually turn it on, thereby reducing the operational trouble of the delivery personnel using the smart helmet.

[0117] Figure 7 This is an exemplary solution for a smart helmet according to an exemplary embodiment. The smart helmet includes a scene recognition unit, a main control unit, an image acquisition unit, and an occlusion unit. (See attached document.) Figure 7 As shown, the main control unit is electrically connected to the scene recognition unit, the occlusion unit, and the device carrying the rule database (such as a smart helmet, terminal, or server).

[0118] The image acquisition unit is used to acquire environmental images around the smart helmet; The scene recognition unit is used to acquire the environmental information of the smart helmet. When it receives a scene recognition result obtained by parsing and recognizing the environmental information, indicating that the environment scene in which the smart helmet is located matches a sensitive scene, it sends a privacy occlusion signal to the main control unit. The environmental information is used to characterize the environmental information of the smart helmet in the scenario where the user wearing the smart helmet is performing an order delivery task. The sensitive scene is a scenario involving sensitive information of a person or organization. The main control unit is used to respond to the privacy occlusion signal, control the image acquisition unit to stop image acquisition, and / or control the occlusion unit to put the image acquisition unit in an occluded state.

[0119] The environmental scenario includes the geographical environment, temporal environment, and audio environment of the smart helmet. The geographical environment includes the geographical location and the surrounding environment. The scenario recognition unit includes at least one of the following: an image acquisition unit, an audio acquisition unit, an infrared sensing unit, and a positioning unit. The image acquisition unit is used to acquire environmental images around the smart helmet, the audio acquisition unit is used to acquire environmental audio around the smart helmet, the infrared sensing unit is used to sense temperature and humidity information around the smart helmet, and the positioning unit is used to locate the location area of ​​the smart helmet. This positioning unit can be a unit integrating GPS (Global Positioning System) and BeiDou positioning modules.

[0120] Optionally, the sensitive scene includes a sensitive location and / or a sensitive environment. The scene recognition unit can also send an occlusion signal to the main control unit when the location area of ​​the smart helmet related to the order delivery task is identified as the sensitive location and / or when the environment represented by the environmental perception parameters of the smart helmet related to the order delivery task is identified as conforming to the sensitive environment. The main control unit is used to respond to the privacy occlusion signal, control the image acquisition unit to stop image acquisition, and / or control the occlusion unit to put the image acquisition unit in an occluded state.

[0121] Optionally, the sensitive location includes the personal sensitive privacy area and / or the organizational sensitive privacy area; the scene recognition unit may also send an occlusion signal to the main control unit if the location area of ​​the smart helmet related to the order delivery task is identified as belonging to the personal sensitive privacy area and / or the organizational sensitive privacy area. The main control unit is used to respond to the privacy occlusion signal, control the image acquisition unit to stop image acquisition, and / or control the occlusion unit to put the image acquisition unit in an occluded state.

[0122] Optionally, the scene recognition unit may also send an occlusion signal to the main control unit in the presence of at least one of the following conditions, wherein the main control unit is used to respond to the privacy occlusion signal by controlling the image acquisition unit to stop image acquisition and / or controlling the occlusion unit to put the image acquisition unit in an occluded state: The temperature and humidity information of the location area of ​​the smart helmet related to the order delivery task is obtained, and the spatial environmental characteristics represented by the temperature and humidity information related to the order delivery task are the bathroom environmental characteristics; The wireless network of the location area of ​​the smart helmet related to the order delivery task is obtained, and the wireless network of the location area related to the order delivery task is a home wireless network; Obtain the entity features of the location area of ​​the smart helmet that is related to the order delivery task, and the entity features of the location area related to the order delivery task are sensitive entity features; Obtain a regional map of the location area related to the order delivery task, and find that the regional map of the location area related to the order delivery task contains sensitive geographic markers, and that the location area of ​​the smart helmet related to the order delivery task is about to enter the sensitive geographic location represented by the sensitive geographic markers. Obtain an environmental image of the location area of ​​the smart helmet that is related to the order delivery task, and the environmental image related to the order delivery task contains sensitive image features; The system acquires ambient audio of the location area of ​​the smart helmet that is related to the order delivery task, and the ambient audio related to the order delivery task contains sensitive audio words.

[0123] Optionally, if the environmental scene represented by the environmental image and / or environmental audio is identified as a conflict scene, the scene recognition unit may send an occlusion release signal to the main control unit. The main control unit then controls the image acquisition unit to acquire an image and controls the occlusion unit to keep the image acquisition unit in an unoccluded state. The environmental information includes the environmental image and / or the environmental audio. The conflict scene is used to represent an adversarial communication scene in the process of interpersonal communication.

[0124] Optionally, the scene recognition unit may also send an occlusion release signal to the main control unit when it receives a signal that the environment scene in which the smart helmet is located is a non-sensitive scene and / or the order status of the order delivery task is a delivery status, after the environmental information is analyzed and recognized. The main control unit then controls the image acquisition unit to acquire images and controls the occlusion unit to keep the image acquisition unit in an unoccluded state.

[0125] Optionally, non-sensitive scenarios include non-sensitive locations and / or the non-sensitive environment; the scene recognition unit may also send an occlusion release signal to the main control unit when the location area of ​​the smart helmet related to the order delivery task is identified as a non-sensitive location and / or the environment represented by the environmental perception parameters of the smart helmet is identified as conforming to a non-sensitive environment. The main control unit then controls the image acquisition unit to acquire images and controls the occlusion unit to keep the image acquisition unit in an unoccluded state.

[0126] Alternatively, the shading unit includes the following two implementations: The first method involves electrochromic film 2, see reference. Figure 8As shown, the electrochromic sheet 2 covers the field of view of the image acquisition unit 4. In a scene where the environment of the smart helmet 1 is identified as a sensitive scene, the electrochromic sheet 2 can be controlled to switch from a transparent state to a non-transparent state.

[0127] In the transparent state, the light transmittance of the electrochromic film 2 is greater than or equal to the first visible threshold; in the non-transparent state, the light transmittance of the electrochromic film 2 is less than or equal to the second visible threshold, and the first visible threshold is greater than the second visible threshold.

[0128] The second method involves occlusion unit 3, see [link / reference] Figure 9 As shown, the occlusion unit 3 includes an occlusion component and a driving component. The occlusion component is movably mounted on the smart helmet 1. The driving component is electrically connected to the main control unit, and the output end of the driving component is connected to the occlusion component. The driving component is used to control the occlusion component to move in front of the acquisition area of ​​the image acquisition unit 4, so that the image acquisition unit 4 is in an occluded state.

[0129] For example, see Figure 10 As shown, the occlusion component includes a rotating component 32, and the driving component includes a first driving component 31. The output end of the first driving component 31 is connected to the rotating component 32. The first driving component 31 is used to drive the rotating component 32 to rotate in front of the acquisition area of ​​the image acquisition unit 4, so that the image acquisition unit 4 is in an occlusion state.

[0130] Among them, see Figure 10 As shown, the first driving component 31 can be a first driving motor, and the rotating component 32 can be a rotating plate. The output end of the first driving motor is connected to the rotating plate. An opening is provided on the smart helmet 1, which is opposite to the acquisition port of the image acquisition unit 4. When the main control unit receives the occlusion release signal, it can control the output end of the first driving motor to rotate, thereby driving the rotating plate to rotate and move away from the opening, thus exposing the acquisition port of the image acquisition unit 4. At this time, the image acquisition unit 4 can acquire environmental images around the smart helmet 1. When the main control unit receives the privacy occlusion signal, it can control the output end of the first driving motor to rotate, thereby driving the rotating plate to rotate until it covers the opening, thus making the image acquisition unit 4 in an occluded state.

[0131] For example, see Figure 11 As shown, the occlusion component includes a sliding component 35, and the driving component includes a second driving component. The output end of the second driving component is connected to the sliding component 35. The second driving component is used to drive the sliding component 35 to slide in front of the acquisition area of ​​the image acquisition unit 4, so that the image acquisition unit 4 is in an occlusion state.

[0132] Among them, see Figure 11 As shown, the second driving component includes a second driving motor 33, a driving link 34, and a limiting component (not shown in the figure). The sliding component 35 can be a sliding plate, and the end of the sliding plate is provided with a sliding hole 36. The output end of the second driving motor 33 is connected to one end of the driving link 34, and the other end of the driving link 34 is provided with a protrusion. The end of the protrusion away from the driving link slides in the sliding hole 36. The limiting component can be a cover, which is detachably installed on the smart helmet 1 to cover the second driving component 33 and the sliding plate. The sliding plate can slide inside the cover, and the cover is provided with an opening. The opening is used to expose the acquisition port of the image acquisition unit 4 when the sliding plate no longer blocks the acquisition port of the image acquisition unit 4. When the main control unit receives the blocking release signal, it can control the output end of the second drive motor 33 to rotate. When the output end of the second drive motor 33 rotates, it drives the drive linkage 34 to rotate, which in turn causes the protrusion at the other end of the drive linkage 34 to slide in the sliding hole 36. When the other end of the drive linkage 34 slides left and right in the sliding hole 36, it drives the sliding plate 35 to slide up and down in the limiting component, thereby moving away from the opening and exposing the acquisition port of the image acquisition unit 4. At this time, the image acquisition unit 4 can acquire environmental images around the smart helmet 1. Conversely, if the second drive component 33 rotates the drive linkage 34 in the opposite direction, it can control the sliding plate 35 to slide to the opening and block the opening, thereby making the image acquisition unit 4 in a blocked state.

[0133] It is understandable that the second drive component 33 can also be implemented by a second drive motor, a lead screw and a limiting component. The lead screw can convert rotary motion into linear motion, which will not be elaborated here.

[0134] Optionally, the smart helmet 1 is also equipped with a prompting unit. When the image acquisition unit 4 acquires an image, the prompting device outputs a first prompt, for example, a prompting light that displays green, to indicate that the image acquisition unit 4 is working. When the image acquisition unit 4 stops acquiring an image, the prompting device outputs a second prompt, for example, a prompting light that displays red, to indicate that the image acquisition unit 4 has stopped working.

[0135] Figure 12 This is a block diagram illustrating an electronic device 1200 according to an exemplary embodiment. The electronic device 1200 can be a smart helmet or a terminal communicating with the smart helmet. Figure 12 As shown, the electronic device 1200 may include: a processor 1201 and a memory 1202. The electronic device 1200 may also include one or more of a multimedia component 1203, an input / output (I / O) interface 1204, and a communication component 1205.

[0136] The processor 1201 controls the overall operation of the electronic device 1200 to complete all or part of the steps in the control method of the smart helmet described above. The memory 1202 stores various types of data to support the operation of the electronic device 1200. This data may include, for example, instructions for any application or method operating on the electronic device 1200, and application-related data such as contact data, sent and received messages, pictures, audio, video, etc. The memory 1202 can be implemented by any type of volatile or non-volatile storage device or a combination thereof, such as Static Random Access Memory (SRAM), Electrically Erasable Programmable Read-Only Memory (EEPROM), Erasable Programmable Read-Only Memory (EPROM), Programmable Read-Only Memory (PROM), Read-Only Memory (ROM), magnetic storage, flash memory, magnetic disk, or optical disk. Multimedia component 1203 may include a screen and an audio component. The screen may be, for example, a touchscreen, and the audio component is used to output and / or input audio signals. For example, the audio component may include a microphone for receiving external audio signals. The received audio signals may be further stored in memory 1202 or transmitted via communication component 1205. The audio component also includes at least one speaker for outputting audio signals. I / O interface 1204 provides an interface between processor 1201 and other interface modules, such as a keyboard, mouse, buttons, etc. These buttons may be virtual or physical buttons. Communication component 1205 is used for wired or wireless communication between the electronic device 1200 and other devices. Wireless communication, such as Wi-Fi, Bluetooth, Near Field Communication (NFC), 2G, 3G, 4G, NB-IoT, eMTC, or other 5G technologies, or combinations thereof, is not limited here. Therefore, the corresponding communication component 1205 may include: a Wi-Fi module, a Bluetooth module, an NFC module, etc.

[0137] In an exemplary embodiment, the electronic device 1200 may be implemented by one or more application-specific integrated circuits (ASICs), digital signal processors (DSPs), digital signal processing devices (DSPDs), programmable logic devices (PLDs), field-programmable gate arrays (FPGAs), controllers, microcontrollers, microprocessors, or other electronic components to execute the control method of the smart helmet described above.

[0138] In another exemplary embodiment, a computer-readable storage medium including program instructions is also provided, which, when executed by a processor, implement the steps of the above-described control method for a smart helmet. For example, the computer-readable storage medium may be the memory 1202 including program instructions, which may be executed by the processor 1201 of the electronic device 1200 to complete the above-described control method for a smart helmet.

[0139] Figure 13 This is a block diagram illustrating an electronic device 1300 according to an exemplary embodiment. For example, the electronic device 1300 may be provided as a server, which may be a server communicating with a smart helmet. (Refer to...) Figure 13 The electronic device 1300 includes a processor 1322, which may be one or more, and a memory 1332 for storing computer programs executable by the processor 1322. The computer program stored in the memory 1332 may include one or more modules, each corresponding to a set of instructions. Furthermore, the processor 1322 may be configured to execute the computer program to perform the aforementioned control method for the smart helmet.

[0140] Additionally, the electronic device 1300 may also include a power supply component 1326 and a communication component 1350. The power supply component 1326 can be configured to perform power management of the electronic device 1300, and the communication component 1350 can be configured to enable communication of the electronic device 1300, such as wired or wireless communication. Furthermore, the electronic device 1300 may also include an input / output (I / O) interface 1358. The electronic device 1300 can operate on an operating system stored in the memory 1332.

[0141] In another exemplary embodiment, a computer-readable storage medium including program instructions is also provided, which, when executed by a processor, implement the steps of the above-described smart helmet control method. For example, the computer-readable storage medium may be the memory 1332 including the program instructions, which may be executed by the processor 1322 of the electronic device 1300 to complete the above-described smart helmet control method.

[0142] In another exemplary embodiment, a computer program product is also provided, the computer program product comprising a computer program executable by a programmable device, the computer program having a code portion for performing the control method of the smart helmet described above when executed by the programmable device.

[0143] The preferred embodiments of this disclosure have been described in detail above with reference to the accompanying drawings. However, this disclosure is not limited to the specific details of the above embodiments. Within the scope of the technical concept of this disclosure, various simple modifications can be made to the technical solutions of this disclosure, and these simple modifications all fall within the protection scope of this disclosure.

[0144] It should also be noted that the various specific technical features described in the above specific embodiments can be combined in any suitable manner without contradiction. In order to avoid unnecessary repetition, this disclosure will not describe the various possible combinations separately.

[0145] Furthermore, various different embodiments of this disclosure can be combined in any way, as long as they do not violate the spirit of this disclosure, they should also be regarded as the content disclosed in this disclosure.

Claims

1. A control method for a smart helmet, characterized in that, The smart helmet is equipped with an image acquisition unit and an occlusion unit. The image acquisition unit is used to acquire environmental images around the smart helmet. The method includes: The environmental information of the smart helmet is obtained, and the environmental information is used to characterize the environmental information of the smart helmet in the scenario where the user wearing the smart helmet is carrying out an order delivery task; If the environment scene of the smart helmet, as determined by the analysis and identification of the environmental information, is a sensitive scene, the system controls the image acquisition unit to stop image acquisition and / or controls the occlusion unit to put the image acquisition unit in an occluded state; the sensitive scene is a scene involving sensitive information of an individual or organization.

2. The control method for the smart helmet according to claim 1, characterized in that, The sensitive scenarios include sensitive locations and / or sensitive environments; upon receiving information that the environment of the smart helmet, identified through analysis of the environmental information, conforms to a sensitive scenario, the system controls the image acquisition unit to stop image acquisition, and / or controls the occlusion unit to place the image acquisition unit in an occluded state, including: If the location area of ​​the smart helmet related to the order delivery task is identified as a sensitive location and / or the environment represented by the environmental perception parameters of the smart helmet related to the order delivery task is identified as a sensitive environment, the image acquisition unit is controlled to stop image acquisition and / or the occlusion unit is controlled to put the image acquisition unit in an occluded state.

3. The control method for the smart helmet according to claim 2, characterized in that, The method further includes: If the location area of ​​the smart helmet related to the order delivery task is identified as a personal sensitive privacy area and / or an organizational sensitive privacy area, the image acquisition unit is controlled to stop image acquisition and / or the occlusion unit is controlled to put the image acquisition unit in an occluded state. The sensitive locations include the personal sensitive privacy area and / or the organizational sensitive privacy area; the personal sensitive privacy area is the area where the smart helmet is located at a distance less than a preset distance from the delivery address specified in the order delivery task, and the organizational sensitive privacy area is the area where the organization is located and access is restricted to unauthorized personnel.

4. The control method for the smart helmet according to claim 2, characterized in that, The method further includes at least one of the following: The system acquires temperature and humidity information of the location area of ​​the smart helmet related to the order delivery task. If the spatial environment characteristics represented by the temperature and humidity information related to the order delivery task are determined to be the bathroom environment characteristics, the system determines that the sensitive environment of the smart helmet is a sensitive privacy environment. The system then controls the image acquisition unit to stop image acquisition and / or controls the occlusion unit to put the image acquisition unit in an occluded state. The system acquires the wireless network of the location area of ​​the smart helmet that is related to the order delivery task. If the wireless network of the location area related to the order delivery task is detected to be a home wireless network, the system determines that the sensitive environment of the smart helmet is a sensitive network environment, controls the image acquisition unit to stop image acquisition and / or controls the occlusion unit to put the image acquisition unit in an occluded state. If a region map of the location area related to the order delivery task is obtained, and there are sensitive geographical markers in the region map of the location area related to the order delivery task, and the location area of ​​the smart helmet related to the order delivery task is about to enter the sensitive geographical location represented by the sensitive geographical markers, then the sensitive environment of the smart helmet is determined to be a sensitive geographical environment, and the image acquisition unit is controlled to stop image acquisition and / or the occlusion unit is controlled to put the image acquisition unit in an occluded state. The system acquires an environmental image of the location area of ​​the smart helmet that is related to the order delivery task. If there are sensitive image features in the environmental image related to the order delivery task, the system determines that the sensitive environment of the smart helmet is a sensitive visual environment, controls the image acquisition unit to stop image acquisition and / or controls the occlusion unit to put the image acquisition unit in an occluded state. The system acquires ambient audio of the location area of ​​the smart helmet that is related to the order delivery task. If there are sensitive audio words in the ambient audio related to the order delivery task, the system determines that the sensitive environment of the smart helmet is a sensitive audio environment, controls the image acquisition unit to stop image acquisition and / or controls the occlusion unit to put the image acquisition unit in an occluded state.

5. The control method for the smart helmet according to claim 1, characterized in that, The method further includes: If the environmental scene represented by the environmental image and / or environmental audio is identified as a conflict scene, the image acquisition unit is controlled to acquire an image and the occlusion unit is controlled to keep the image acquisition unit in an unoccluded state; the environmental information includes the environmental image and / or the environmental audio. The conflict scenarios include adversarial communication scenarios in interpersonal communication.

6. The control method for the smart helmet according to claim 1, characterized in that, The method further includes: Upon receiving information that the environment scene of the smart helmet, as determined by the analysis and identification of the environmental information, is a non-sensitive scene and / or that the order status of the order delivery task is in delivery status, the system controls the image acquisition unit to start acquiring images and controls the occlusion unit to keep the image acquisition unit in an unoccluded state.

7. The control method for the smart helmet according to claim 6, characterized in that, Upon receiving information that the environment in which the smart helmet is located, determined through analysis and identification of the environmental information, is a non-sensitive scenario and / or that the order status of the order delivery task is in delivery status, the system controls the image acquisition unit to start acquiring images and controls the occlusion unit to ensure that the image acquisition unit is in an unoccluded state, including: When the location area of ​​the smart helmet related to the order delivery task is identified as a non-sensitive location and / or the environment characterized by the environmental perception parameters of the smart helmet is identified as a non-sensitive environment, the image acquisition unit is controlled to acquire images and the occlusion unit is controlled to keep the image acquisition unit in an unoccluded state; the non-sensitive scene includes the non-sensitive location and / or the non-sensitive environment.

8. A smart helmet, characterized in that, The smart helmet is equipped with a scene recognition unit, a main control unit, an image acquisition unit, and an occlusion unit. The image acquisition unit is used to acquire environmental images around the smart helmet; The scene recognition unit is used to acquire the environmental information of the smart helmet. When it receives a scene where the environment of the smart helmet is located after the environmental information is analyzed and identified and it is determined to be a sensitive scene, it sends a privacy occlusion signal to the main control unit. The environmental information is used to characterize the environmental information of the smart helmet in the scenario where the user wearing the smart helmet is performing an order delivery task. The sensitive scene is a scene involving sensitive information of a person or organization. The main control unit is used to respond to the privacy occlusion signal, control the image acquisition unit to stop image acquisition, and / or control the occlusion unit to put the image acquisition unit in an occluded state.

9. The smart helmet according to claim 8, characterized in that, The shielding unit includes a shielding component and a driving component, wherein the shielding component is movably mounted on the smart helmet; The driving component is electrically connected to the main control unit, and the output terminal of the driving component is connected to the blocking component. The driving component is used to control the blocking component to move in front of the acquisition area of ​​the image acquisition unit so that the image acquisition unit is in a blocked state.

10. The smart helmet according to claim 9, characterized in that, The occlusion component includes a rotating component, and the driving component includes a first driving component. The output end of the first driving component is connected to the rotating component. The first driving component is used to drive the rotating component to rotate in front of the acquisition area of ​​the image acquisition unit so that the image acquisition unit is in an occlusion state.

11. The smart helmet according to claim 9, characterized in that, The occlusion component includes a sliding component, and the driving component includes a second driving component. The output end of the second driving component is connected to the sliding component. The second driving component is used to drive the sliding component to slide in front of the acquisition area of ​​the image acquisition unit so that the image acquisition unit is in an occlusion state.

Images