Method for detecting at least one wheel object in an elevator car and elevator car wheel detection system
By using optical imaging technology and neural network models in the elevator car to identify garbage objects and generate service demand requests based on the cleanliness standards, the problem of difficult monitoring of the cleanliness of the elevator car is solved, automated monitoring and management is realized, and passenger experience is improved.
Patent Information
- Application Number
- CN202280098421.5
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2022-07-27
- Publication Date
- 2025-02-28
AI Technical Summary
The existing technology is difficult to effectively monitor and manage the cleanliness of elevator cars, resulting in poor hygiene during the use of elevators and affecting the passenger experience.
Optical imaging technology and pre-trained neural network model are adopted to arrange imaging devices in the elevator car, capture optical image data, detect and classify objects in the elevator, identify garbage objects, and generate service demand requests based on predetermined cleanliness levels.
It realizes automatic monitoring and management of elevator car cleanliness, reduces cleaning costs, and improves the sanitation and passenger experience during the use of elevators.
Smart Images
Figure CN119546540A_ABST
Abstract
Description
Technical Field
[0001] The present invention generally relates to the technical field of elevators. In particular, the present invention relates to monitoring the cleanliness of an elevator car. Background Art
[0002] Typically, the hygienic conditions and cleanliness of the elevator car play a decisive role in the ride comfort of the passengers in the elevator car. Customers may often require that the elevator car be kept clean during its operating time. For example, a hotel may require strict cleaning of the elevator car to provide a good experience to its customers. Typically, the owner of the building is responsible for maintaining good hygienic conditions and cleanliness in the elevator car. For this purpose, for example, a health inspector may be required to go to the site (i.e., the elevator car) for a health inspection, and if the elevator car is dirty, the health inspector may call a cleaning service to clean the elevator car. Alternatively or additionally, the cleaning of the elevator car may be scheduled regularly.
[0003] Therefore, there is a need for further development of solutions for monitoring the cleanliness of elevator cars. Summary of the invention
[0004] A simplified overview is presented below to provide a basic understanding of some aspects of various inventive embodiments. This overview is not a broad overview of the present invention. It is neither intended to identify key or important elements of the present invention nor to describe the scope of the present invention. The following overview only presents some concepts of the present invention in a simplified form as a preface to a more detailed description of exemplary embodiments of the present invention.
[0005] The object of the present invention is to propose a method for detecting at least one garbage object in an elevator car, an elevator car garbage detection system and an elevator system. Another object of the present invention is that the method for detecting at least one garbage object in an elevator car, the elevator car garbage detection system and the elevator system improve the monitoring of the cleanliness of the elevator car.
[0006] The objects of the invention are achieved by a method, an apparatus and a computer program as defined by the respective independent claims.
[0007] According to a first aspect, a method for detecting at least one garbage object within an elevator car is provided, wherein the method comprises: obtaining optical image data of the interior of the elevator car; detecting one or more objects from the optical image data; classifying the detected one or more objects into predetermined object categories based on predetermined garbage object definition data, wherein the predetermined object categories include a garbage object category and at least one other object category; if at least one of the detected one or more objects is classified as a garbage object category, at least one garbage object is detected; and in response to detecting the at least one garbage object, generating a control signal to an elevator processing system for generating a service demand request.
[0008] The method may further include receiving a control signal, wherein the control signal may include trash quantity data representing the number of detected trash objects; obtaining predetermined cleanliness level data representing a required cleanliness level of the elevator car; and generating a service demand request based on the predetermined cleanliness level data and the trash quantity data.
[0009] Generating the service demand request may include generating an immediate service demand if the garbage quantity data satisfies a predetermined threshold level included in the predetermined cleanliness level data, and generating a standard service demand otherwise.
[0010] The garbage object category may further include one or more subcategories for different types of garbage objects, wherein the method may further include classifying the detected at least one garbage object into the one or more subcategories based on predetermined garbage object definition data.
[0011] One or more objects may be detected from optical image data by using at least one pre-trained neural network model.
[0012] The optical image data may be obtained from at least one imaging device arranged inside the elevator car.
[0013] A service demand request may be generated to an elevator service center and / or a cleaning service center.
[0014] According to a second aspect, an elevator car garbage detection system is provided, wherein the elevator car garbage detection system includes: at least one optical imaging device, which is arranged inside the elevator car and configured to capture optical image data of the interior of the elevator car; an elevator processing system; and a garbage identification unit, which is configured to: obtain optical image data of the interior of the elevator car captured by the at least one optical imaging device, detect one or more objects from the optical image data; classify the detected one or more objects into predetermined object categories based on predetermined garbage object definition data, wherein the predetermined object category includes a garbage object category and at least one other object category; if at least one of the one or more detected objects is classified as a garbage object category, at least one garbage object is detected; and in response to detecting the at least one garbage object, generate a control signal to the elevator processing system to generate a service demand request.
[0015] The elevator handling system may also be configured to: receive a control signal from a garbage identification unit, wherein the control signal may include garbage quantity data representing the number of detected garbage objects; obtain predetermined cleanliness level data representing the required cleanliness level of the elevator car; and generate the service demand request based on the predetermined cleanliness level data and the garbage quantity data.
[0016] The generation of the service demand request may include configuring the elevator handling system to generate an immediate service demand if the garbage quantity data satisfies a predetermined threshold level included in the predetermined cleanliness level data, and to generate a standard service demand otherwise.
[0017] The garbage object category may further include one or more subcategories for different types of garbage objects, wherein the garbage identification unit may be further configured to classify the detected at least one garbage object into the one or more subcategories based on predetermined garbage object definition data.
[0018] The garbage identification unit may be configured to detect one or more objects from the optical image data by using at least one pre-trained neural network model.
[0019] A service demand request may be generated to an elevator service center and / or a cleaning service center.
[0020] According to a third aspect, an elevator system is provided, wherein the elevator system comprises at least one elevator car arranged to travel along a respective elevator shaft, and an elevator car trash detection system as described above.
[0021] Various exemplary and non-limiting embodiments of the invention, both as to constructions and methods of operation, together with additional objects and advantages thereof, will be best understood from the following description of specific exemplary and non-limiting embodiments when read in connection with the accompanying drawings.
[0022] The verbs "comprise" and "include" are used in this document as open limitations, which neither exclude nor require the existence of unrecited features. Unless explicitly stated otherwise, the features recited in the dependent claims are mutually freely combinable. Furthermore, it should be understood that the use of "a" or "an" (i.e. the singular) throughout this document does not exclude a plurality. BRIEF DESCRIPTION OF THE DRAWINGS
[0023] Embodiments of the invention are illustrated by way of example and not limitation in the figures of the accompanying drawings.
[0024] Figure 1 An example of an elevator system is schematically shown.
[0025] Figure 2A An example of an elevator car trash detection system is schematically shown.
[0026] Figure 2B An example of an elevator handling system is schematically shown.
[0027] Figure 3 An example of a method for detecting at least one trash object within an elevator car is schematically shown.
[0028] Figure 4 An example of a service requirement level assessment process is schematically shown.
[0029] Figure 5 An example of components of a waste identification unit is schematically shown.
[0030] Figure 6 An example of components of an edge processing unit of an elevator processing system is schematically shown. DETAILED DESCRIPTION
[0031] Figure 1 Schematically illustrated is an example of an elevator system 100. The elevator system 100 includes at least one elevator car 110 configured to travel along a respective elevator shaft 120 between a plurality of landings. Figure 1 The example elevator system 100 includes one elevator car 110 traveling along one elevator shaft 120, however the elevator system 100 may also include an elevator group, i.e., a group of two or more elevator cars 110, each of which travels along a separate elevator shaft 120, and the elevator shafts 120 are configured to operate as a unit serving the same landing (for clarity, Figure 1 The elevator system 100 also includes an elevator control unit, such as an elevator controller 130. The elevator control unit 130 may be configured to at least partially control the operation of the elevator system 100. The elevator control unit 130 may reside, for example, in a machine room (not shown in the figure for clarity). Figure 1 ) or one of the landings of the elevator system 100. The elevator system 100 may also include one or more other known elevator-related entities, such as a hoisting system, a user interface device, a safety circuit and device, an elevator door system, etc., which are not shown in the figure for the sake of clarity. Figure 1 The elevator system 100 also includes an elevator car trash detection system 200 (for clarity, Figure 1 The entity of the elevator car garbage detection system 200 is not shown).
[0032] Figure 2A An example of an elevator car trash detection system 200 for detecting at least one trash object 230 within an elevator car 110 is schematically shown. The elevator car trash detection system 200 includes at least one optical imaging device 210, a trash identification unit 220, and an elevator processing system 250. The at least one optical imaging device 210 is communicatively coupled to the trash identification unit 220. The communication between the at least one optical imaging device 210 and the trash identification unit 220 can be based on one or more known wired or wireless communication technologies. The trash identification unit 220 is communicatively coupled to the elevator processing system 250. The communication between the trash identification unit 220 and the elevator processing system 250 can be based on one or more known wired or wireless communication technologies. The elevator car trash detection system 200 may also include at least one service center 240. Alternatively, the elevator processing system 250 may be associated with the at least one service center 240. The at least one service center 240 may, for example, include an elevator service center and / or a cleaning service center. The elevator processing system 250 is communicatively coupled to the at least one service center 240. Communications between the elevator processing system 250 and the at least one service center 240 may be based on one or more known wired or wireless communication techniques.
[0033] At least one optical imaging device 210 is disposed inside the elevator car 110 and is configured to capture optical image data of the interior of the elevator car 110. The optical image data provided by the at least one optical imaging device 210 may include one or more images and / or a video image including multiple consecutive images (i.e., frames). Preferably, the elevator car garbage detection system 200 may include one optical imaging device 210 disposed inside the elevator car 110. However, more than one optical imaging device 210 may be used to achieve better coverage of the elevator car 110 with optical image data, which improves the accuracy and reliability of detecting at least one garbage object in the elevator car. The at least one optical imaging device 210 may be disposed (e.g., placed) at different locations within the elevator car 110. Some non-limiting example placements of the at least one optical imaging device 210 may include: middle placement (e.g., at least one optical imaging device 210 may be placed in a middle placement), corner placement (e.g., at least one optical imaging device 210 may be placed in a corner placement), and ceiling placement (e.g., at least one optical imaging device 210 may be placed in a ceiling placement). For example, the intermediate placement may be located horizontally in the middle of the rear wall of the elevator car 110, such as Figure 2A Alternatively, the middle placement may be located horizontally in the middle of any other wall of the elevator car 110. For example, the corner placement may be at an upper rear corner of the elevator car 110. The upper rear corner of the elevator car 110 may be any of the upper rear corners of the elevator car 110. Alternatively, the corner placement may be at an upper front corner of the elevator car 110. The upper front corner of the elevator car 110 may be any of the upper front corners of the elevator car 110. Figure 2A , a non-limiting example location of at least one optical imaging device 210 inside the elevator car 110 is shown. Figure 2AAs shown in the example of , at least one optical imaging device 210 may preferably be placed near the ceiling of the elevator car 110, i.e. as high as possible. At least one optical imaging device 210 may be placed so that the optical image data provided by the at least one optical imaging device 210 covers the largest possible area of the elevator car 110. Preferably, at least one optical imaging device 210 may be placed so that the optical image data provided by the imaging device 210 completely covers at least one floor of the elevator car 110. At least one optical imaging device 210 may, for example, include a camera, such as a red, green, and blue (RGB) camera or a black and white camera. Preferably, at least one optical imaging device 210 may be capable of providing optical image data with high resolution and / or a wide field of view (FOV) to cover the largest area of the elevator car 110 by the optical image data. The elevator car garbage detection system 200 may also be configured to detect at least one garbage object 230 within one or more elevator cars 110 of the elevator system 100. In this case, at least one optical imaging device 210 may be arranged inside each elevator car 110 for capturing optical image data of the interior of the elevator car 110.
[0034] The waste identification unit 220 can be deployed to any on-site location in the elevator system 100 or any off-site location remote from the elevator system 100 (e.g., the waste identification unit 220 can be implemented as a remote computing unit, a cloud-based computing unit, or any other off-site computing unit). The elevator processing system 250 may include an edge processing unit 252 and a service demand engine 254. Figure 2B An example of entities of an elevator processing system 250 is shown. The edge processing unit 252 is an additional processing and connection unit of the elevator system 100. The edge processing unit 252 can communicate with the elevator control unit 130 (e.g., via a bus) to obtain elevator system related data. Alternatively or additionally, the edge processing unit 252 may include one or more sensor devices (internal and / or external sensor devices) for obtaining elevator system related data. According to an example, the edge processing unit 252 may be arranged to the elevator car 110 (e.g., on the roof of the elevator car 110 or any other location in the elevator car 110, inside the elevator car 110 or outside the elevator car 110) or any other on-site location in the elevator system 100. The service demand engine 254 is responsible for generating service demands for at least one service center 240. The service demand engine 254 may be arranged at an off-site location away from the elevator system 100. For example, the service demand engine 254 may be implemented as a cloud-based service demand engine (i.e., the service demand engine 254 is located in the cloud). According to an example, the garbage identification unit 220 can be integrated into the edge processing unit 252 of the elevator processing system 250. In other words, the operation of the garbage identification unit 220 can be implemented in the edge processing unit 252 of the elevator processing system 250.
[0035] Next, by referring to Figure 3 An example of a method for detecting at least one garbage object 230 within an elevator car 110 is described. Figure 3 The method is schematically shown in a flow chart. Figure 3 However, the method can also be applied accordingly to detect at least one garbage object 230 in more than one elevator car 110.
[0036] In step 310, the garbage identification unit 220 obtains optical image data of the interior of the elevator car 110 captured by the at least one optical imaging device 210. In other words, the garbage identification unit 220 obtains the optical imaging data of the interior of the elevator car 110 from the at least one optical imaging device 210. The garbage identification unit 220 may obtain the optical image data of the interior of the elevator car 110 constantly, periodically, or at a certain point in time. Alternatively or additionally, the garbage identification unit 220 may obtain the optical image data of the interior of the elevator car 110 upon request, i.e., the garbage identification unit 220 may, for example, generate a request to the at least one optical imaging device 210 to provide the optical image data of the interior of the elevator car 110.
[0037] At step 320, the garbage identification unit 220 detects (i.e., extracts or identifies) one or more objects from the optical image data. The garbage identification unit 220 is capable of identifying any kind of object. Therefore, the one or more objects detected by the garbage identification unit 220 may include any kind of object, such as garbage objects 230 and / or non-garbage objects. The garbage identification unit 220 may use at least one pre-trained neural network model 526 to detect one or more objects from the optical image data. The at least one pre-trained neural network model 526 may, for example, include a single shot multibox detector (SSD) having a VGG16 convolutional neural network model.
[0038] At step 330, in response to detecting one or more objects at step 320, the garbage identification unit 220 classifies the detected one or more objects into a predetermined object category based on predetermined garbage object definition data. The predetermined object category includes a garbage object category and at least one other object category. The predetermined garbage object definition data may include the definition of one or more predetermined garbage objects, i.e., one or more predetermined objects defined as garbage objects 230. The predetermined garbage object definition data may be stored in a memory portion 520 of the garbage identification unit 220. Alternatively or additionally, the predetermined garbage object definition data may be stored in a database from which the garbage identification unit 220 obtains the predetermined garbage object definition data. The predetermined garbage object definition data may be customer-specific. In other words, the one or more objects defined as garbage objects 230 may be customer-specific. This allows each customer to individually define which object(s) are defined as garbage objects. For example, some objects defined as garbage objects 230 by one customer may not be considered garbage objects 230 for some other customers. Some non-limiting examples of customers may include hotels, public transportation stations (e.g., subway stations, train stations, bus stations, and / or airports, etc.), and / or office buildings, etc. According to a non-limiting example, in the case where the customer is a hotel, at least the following objects may be defined as garbage objects 230, for example: empty cans, plastic bags, plastic containers, and / or cardboard boxes, etc. The garbage identification unit 220 classifies each of the one or more detected objects into a predetermined object category based on predetermined garbage object definition data. Each object of the one or more detected objects that is defined as a garbage object 230 based on the predetermined garbage object definition data is classified into a garbage object category, and each object of the one or more detected objects that is not defined as a garbage object 230 based on the predetermined garbage object definition data is classified into at least one other object category. The garbage object category may also include one or more subcategories for different types of garbage objects 230. The garbage identification unit 220 may also classify the at least one detected garbage object 230 into one or more subcategories based on the predetermined garbage object definition data. The garbage identification unit 220 may classify the one or more detected objects into the predetermined object category using at least one pre-trained neural network model 526. The pre-trained at least one neural network model 526 may be pre-trained, for example, by using images of garbage objects 230 within the elevator car 110 belonging to a plurality of different garbage categories (for example, but not limited to, 30 different garbage categories). The definitions of one or more predetermined garbage objects 230 (i.e., one or more predetermined objects defined as garbage objects 230) included in the predetermined garbage object definition data can belong to these multiple different categories used in the pre-training of at least one neural network model 526.
[0039] At step 340, if at least one of the one or more objects detected at step 330 is classified as a garbage object category, then the garbage identification unit 220 detects at least one garbage object 230. In other words, if at least one of the one or more objects detected is classified as a garbage object category, then the garbage identification unit 220 infers that at least one garbage object 230 may be detected within the elevator car 110.
[0040] At step 350, the waste identification unit 220 generates a control signal to the elevator processing system 250 for generating a service demand request in response to detecting at least one waste object 230 at step 340. The control signal may, for example, include an indication that at least one waste object 230 within the elevator car 110 is detected and / or an instruction to generate a service demand request. The elevator processing system 250 may generate the service demand request in response to receiving the control signal from the waste identification unit 220. For example, the edge processing unit 252 of the elevator processing system 250 may receive the control signal from the waste identification unit 220 and instruct the service demand engine 254 of the elevator processing system 250 to generate the service demand request. The service demand request may be generated to at least one service center 240, for example, an elevator service center and / or a cleaning service center.
[0041] According to an example, the elevator processing system 250 may perform a service demand level assessment process in response to receiving a control signal from the garbage identification unit 220 before generating a service demand request. Figure 4 Describe an example of a process for assessing service needs levels. Figure 4 The service requirement level assessment process is schematically shown in a flow chart.
[0042] At step 410, the edge processing unit 252 of the elevator processing system 250 may receive a control signal from the garbage identification unit 220. As described above, the control signal may include an indication of detection of at least one garbage object 230 within the elevator car 110 and / or an instruction to generate a service demand request. Alternatively or additionally, the control signal may include garbage quantity data indicating the quantity of garbage objects 230 detected.
[0043] At step 420, the edge processing unit 252 of the elevator processing system 250 may obtain predetermined cleanliness level data representing a desired cleanliness level of the elevator car 110. The edge processing unit 252 may obtain the predetermined cleanliness level data, for example, from a database. According to a non-limiting example, the edge processing unit 252 may obtain the predetermined cleanliness level data, for example, from a database included in the cloud. The predetermined cleanliness level data may, for example, include a predetermined threshold level representing a desired cleanliness level of the elevator car 110. The predetermined threshold level may, for example, be the number of garbage objects 230 detected. The cleanliness level data may be predefined or configured by a customer. In other words, a customer may individually define the cleanliness level desired by the customer.
[0044] At step 430, the elevator handling system 250 may generate a service demand request based on the predetermined cleanliness level data and the garbage quantity data. Generating the service demand request at step 430 may include: if the garbage quantity data satisfies the predetermined threshold level included in the predetermined cleanliness level data at step 440, the elevator handling system 250 generates an immediate service demand at step 450, or the elevator handling system 250 generates a standard service demand at step 460. In other words, the edge processing unit 252 compares the garbage quantity data included in the control signal received from the garbage identification unit 220 with the predetermined threshold level included in the predetermined cleanliness level data at step 440. If the garbage quantity data (i.e., the number of garbage objects 230 detected) satisfies the predetermined threshold level, the edge processing unit 252 instructs the service demand engine 254 to generate an immediate service demand for at least one service center 240 at step 450. Alternatively, if the garbage quantity data (i.e., the number of garbage objects 230 detected) does not satisfy the predetermined threshold level, the edge processing unit 252 instructs the service demand engine 254 to generate a standard service demand for at least one service center 240 at step 460. An immediate service demand may include an instruction to immediately clean the elevator car 110. A standard service demand may include an instruction to clean the elevator car 110 according to a scheduled cleaning (e.g., the next time a cleaning crew visits the elevator car 110). According to a non-limiting example, the predetermined threshold level may be three detected trash objects 230, whereby if the trash quantity data indicates that the number of detected trash objects 230 is three or more, the edge processing unit 252 instructs the service demand engine 254 to generate an immediate service demand, and if the trash quantity data indicates that the number of detected trash objects 230 is less than three, the edge processing unit 252 instructs the service demand engine 254 to generate a standard service demand.
[0045] The verb "satisfy" in the context of a threshold level is used in this patent application to indicate that a predetermined condition is satisfied. For example, the predetermined condition may be reaching and / or exceeding a predetermined threshold level.
[0046] Figure 5 An example of components of the garbage identification unit 220 is schematically shown. The garbage identification unit 220 may include a processing unit 510 having one or more processors, a memory unit 520 having one or more memories, a communication unit 530 having one or more communication devices, and a possible user interface (UI) unit 540. The mentioned elements may be communicatively coupled to each other via, for example, an internal bus. The memory unit 520 may store and maintain a computer program (code) 525, at least one neural network model 526, obtained optical image data, predetermined garbage object definition data, and parts of any other data. The computer program 525 may include instructions that, when executed by the processing unit 510 of the garbage identification unit 220, may cause the processing unit 510, thereby causing the garbage identification unit 220 to perform the desired tasks of the garbage identification unit 220, such as one or more method steps performed by the above-mentioned garbage identification unit 220. Therefore, the processing unit 510 may be arranged to access the memory unit 520 and retrieve any information from and store any information to the memory unit 520. For the sake of clarity, the processor herein refers to any unit suitable for processing information and controlling the operation of the garbage identification unit 220 and other tasks. The operation can also be implemented with a microcontroller solution with embedded software. Similarly, the memory unit 520 is not limited to a certain type of memory, but any memory type suitable for storing the described multiple pieces of information can be applied in the context of the present invention. The communication unit 530 provides one or more communication interfaces for communicating with any other unit (e.g., at least one optical imaging device 210, the elevator processing system 250, one or more databases) or with any other unit. The user interface unit 540 may include one or more input / output (I / O) devices such as buttons, keyboards, touch screens, microphones, speakers, displays, etc. for receiving user input and output information. The computer program 525 can be a computer program product that can be included in a tangible non-volatile (non-transitory) computer-readable medium that carries the computer program code 525 embodied therein for use with a computer (i.e., the garbage identification unit 220).
[0047] Figure 6An example of components of an edge processing unit 252 of an elevator processing system 250 is schematically shown. The edge processing unit 252 may include a processing unit 610 having one or more processors, a memory unit 620 having one or more memories, a communication unit 630 having one or more communication devices, and a possible user interface (UI) unit 640. The mentioned elements may be communicatively coupled to each other via, for example, an internal bus. The memory unit 620 may store and maintain parts of a computer program (code) 625, predetermined cleanliness level data, and any other data. The computer program 625 may include instructions that, when the processing unit 610 of the edge processing unit 252 executes the computer program 625, may cause the processing unit 610 and the edge processing unit 252 to perform the desired tasks of the edge processing unit 252, for example, one or more method steps performed by the above-mentioned edge processing unit 252. Therefore, the processing unit 610 may be arranged to access the memory unit 620 and retrieve any information from and store any information to the memory unit 620. For clarity, the processor here refers to any unit suitable for processing information and controlling the operation of the edge processing unit 252 and other tasks. The operation can also be implemented with a microcontroller solution with embedded software. Similarly, the memory unit 620 is not limited to a certain type of memory, but any memory type suitable for storing the described multiple pieces of information can be applied in the context of the present invention. The communication unit 630 provides one or more communication interfaces for communicating with any other unit (e.g., the garbage identification unit 220, the service demand engine 254, one or more databases) or with any other unit. The user interface unit 640 may include one or more input / output (I / O) devices such as buttons, keyboards, touch screens, microphones, speakers, displays, etc. for receiving user input and output information. The computer program 625 can be a computer program product that can be included in a tangible non-volatile (non-transitory) computer-readable medium that carries the computer program code 625 embodied therein for use with a computer (i.e., the edge processing unit 252).
[0048] The above-described method and elevator car trash detection system 200 improve the monitoring of the cleanliness of the elevator car 110. The method and elevator car trash detection system 200 enable the process of monitoring the cleanliness of the elevator car 110 to be automated. The method and elevator car trash detection system 200 enable the cleaning costs of the elevator car 110 to be reduced by eliminating the need for health inspectors to visit on-site at the elevator. In addition, the method and elevator car trash detection system 200 enable the use of customer-specific cleanliness requirements in trash detection, because not all customers require the same level of cleanliness of the elevator car 110.
[0049] The specific examples provided in the description given above should not be construed as limiting the applicability and / or interpretation of the appended claims.The lists and groups of examples provided in the description given above are not exhaustive unless expressly stated otherwise.
Claims
1. A method for detecting at least one garbage object (230) in an elevator car (110), the method comprising: Obtaining (310) optical image data of the interior of the elevator car (110); detecting (320) one or more objects from the optical image data; classifying (330) the detected one or more objects into predetermined object classes based on predetermined junk object definition data, wherein the predetermined object classes include a junk object class and at least one other object class; detecting (340) at least one garbage object (230) if at least one of the detected one or more objects is classified in a garbage object category; and In response to detecting the at least one garbage object (230), a control signal is generated (350) to an elevator processing system (250) for generating a service demand request.
2. The method according to claim 1, further comprising: receiving (410) the control signal, wherein the control signal includes garbage quantity data representing a quantity of detected garbage objects (230); obtaining (420) predetermined cleanliness level data representing a desired cleanliness level of the elevator car (110); and The service demand request is generated (430) based on the predetermined cleanliness level data and the waste quantity data.
3. The method according to claim 2, wherein: Generating (430) the service demand request includes generating (450) an immediate service demand if the waste quantity data satisfies (440) a predetermined threshold level included in the predetermined cleanliness level data, and otherwise generating (460) a standard service demand.
4. A method according to any one of the preceding claims, wherein: The garbage object category further includes one or more subcategories for different types of garbage objects (230), wherein the method further includes classifying the detected at least one garbage object (230) into the one or more subcategories based on the predetermined garbage object definition data.
5. A method according to any one of the preceding claims, wherein: The one or more objects are detected from the optical image data using at least one pre-trained neural network model (526).
6. The method according to any of the preceding claims, wherein the optical image data are obtained from at least one imaging device (210) arranged inside the elevator car (110).
7. A method according to any one of the preceding claims, wherein: The service demand request is generated to an elevator service center and / or a cleaning service center (240).
8. An elevator car garbage detection system (200), comprising: at least one optical imaging device (210) disposed inside the elevator car (110) and configured to capture optical image data of the interior of the elevator car (110); an elevator handling system (250); and The garbage identification unit (220) is configured as follows: obtaining optical image data of the interior of the elevator car (110) captured by the at least one optical imaging device (210), detecting one or more objects from the optical image data; classifying the detected one or more objects into predetermined object classes based on predetermined junk object definition data, wherein the predetermined object classes include a junk object class and at least one other object class; If at least one of the detected one or more objects is classified in a garbage object category, at least one garbage object is detected (230); and In response to detecting the at least one garbage object (230), a control signal is generated to the elevator processing system (250) to generate a service demand request.
9. The elevator car garbage detection system (200) according to claim 8, wherein the elevator processing system (250) is further configured to: receiving the control signal from the garbage identification unit (220), wherein the control signal includes garbage quantity data indicating the quantity of detected garbage objects (230); obtaining predetermined cleanliness level data representing a desired cleanliness level of the elevator car (110); and The service demand request is generated based on the predetermined cleanliness level data and the garbage quantity data.
10. The elevator car garbage detection system (200) of claim 9, wherein the generation of the service demand request includes the elevator handling system (250) being configured to generate an immediate service demand if the garbage quantity data meets a predetermined threshold level included in the predetermined cleanliness level data, and otherwise generate a standard service demand.
11. An elevator car garbage detection system (200) according to any one of claims 8 to 10, wherein the garbage object category further includes one or more subcategories for different types of garbage objects (230), and wherein the garbage identification unit (220) is further configured to classify at least one detected garbage object into the one or more subcategories based on predetermined garbage object definition data.
12. The elevator car trash detection system (200) according to any one of claims 8 to 11, wherein the trash identification unit (220) is configured to detect the one or more objects from the optical image data by using at least one pre-trained neural network model (526).
13. The elevator car garbage detection system (200) according to any one of claims 8 to 12, wherein the service demand request is generated to an elevator service center and / or a cleaning service center (240).
14. An elevator system (100), comprising: at least one elevator car (110) arranged to travel along a respective elevator shaft (120), and An elevator car garbage detection system (200) according to any one of claims 8 to 13.