Container system for implementing interactive assistants

Abstract

This invention relates to an object transport system that enables interactive communication. According to the present invention, such a system comprises at least one container (1, 10) configured to capture first data provided by a user, and an intelligent dialogue agent (18), wherein the intelligent dialogue agent (18) is configured to receive the first data transmitted by the container, perform semantic analysis of the first data, optionally generate second data resulting from the semantic analysis, and optionally transmit the second data to the at least one container, and the container (1, 10) is further configured to process the received second data.

Description

Technical Field

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[0001] The present invention relates to the field of interactive artificial intelligence related to connected objects known by the term IoT (Internet of Things).

[0002] More precisely, the present invention relates to intelligent containers for the transport of products, parts or objects.

[0003] The present invention is particularly applied to the transport of packages or parcels used in the field of logistics transport for the delivery of products.

Background Art

[0004] In the field of logistics, it is known to label parcels, identify their destinations, sort them and transfer them to their recipients via a logistics platform. Such techniques are subject to the need to add numerous labels depending on the number of logistics service providers involved in the transport. Furthermore, this preliminary technology encompasses many drawbacks related to the lack of peeled labels, readability problems, and the impossibility of tracking parcels between two identification points in the logistics platform. As a result, many parcels are lost and, in some cases, stolen.

[0005] Therefore, there is a clear need to use packages equipped with integrated electronic units having a screen that functions as a label and capable of transmitting location information to a monitoring platform along the logistics route to be followed.

[0006] Finally, to enhance the security of these packages, parcel locking means have been added to restrict access to authorized persons, very often the final recipient, by allowing opening under specific conditions.

[0007] However, these developments in packages for sending and transporting objects do not come without drawbacks.

[0008] Specifically, as soon as a new type of labeling is used, it is necessary to revise and redesign the process and anticipate operational and processing errors in the logistics chain.

[0009] Another drawback of such technology is that, in turn, all professionals in the logistics chain are required to be trained in this new, and often specialized, use.

[0010] Another drawback of this technology is that when the recipient receives their package, they have no information about its transport, even if they were able to track its route. [Overview of the Initiative] [Problems that the invention aims to solve]

[0011] Accordingly, the present invention aims to mitigate the drawbacks of the prior art described above.

[0012] More precisely, the present invention aims to provide an object transport system that enables interactive communication between the user and the transport package.

[0013] Another objective of the present invention is to provide such a technology that is easy for users to implement.

[0014] Another object of the present invention is to provide such a technology that enables appropriate interaction with the user.

[0015] Another objective of the present invention is to provide a technology that enables dialogue centered on the sender's profile.

[0016] Another object of the present invention is to provide such technology in a reliable and consumer-safe manner. [Means for solving the problem]

[0017] These objectives, along with other objectives revealed in the remainder of this text, are achieved using an object transport system that enables interactive communication.

[0018] In the context of the present invention, the system comprises at least one container configured to capture first data. The system further comprises a) Receive the first data sent by the container, b) Perform semantic analysis on the data described above, c) Optionally, generate second data resulting from semantic analysis, d) optionally comprising an intelligent dialogue agent configured to transmit the second data to at least one container, Furthermore, in this system, the container is configured to process the second received data.

[0019] Therefore, in such a system, these technical features make it possible for a container to send data to an intelligent dialogue agent, which can then semantically analyze the data and use the analysis results to initiate a dialogue.

[0020] According to a preferred embodiment of the present invention, the first data and the second data are so-called communication data that form an interactive exchange. The first data comes from the container user. The second data processing by the container involves transmitting the second data to the user. The intelligent dialogue agent further, - Maintain contextual information based on interactive exchanges, - The system is configured to use contextual information during the semantic analysis.

[0021] These features enable the user to query the container in natural language and, instead, obtain assistance and / or additional information provided in natural language. Furthermore, the user can interact with the container through a series of ordered questions / answers.

[0022] In addition, since the intelligent dialogue agent maintains a history of the questions and answers exchanged with the user, it can refine the analysis thereof and improve the accuracy of its answers.

[0023] According to an advantageous embodiment of the invention, the first data is so-called information data of the type of identifier, or physical quantity, or operating setting.

[0024] These features enable the intelligent dialogue agent to receive information regarding the context of the container. These information can be single, paired, or combined in order to provide a variable level of accuracy regarding the information collected. The first so-called information data can include, for example, only the internal temperature and / or the external temperature, the internal and / or external atmospheric pressure. This can further be information related to its movement, such as acceleration, or position by satellite positioning. Thus, from the movement information, the intelligent dialogue agent can infer that the container has been exposed to shock, vibration, or a fall. In the case of a fall, the height and / or acceleration of the fall can complete the information.

[0025] Advantageously, the identifier is an identifier specific to the application, or an identifier of a known type such as an SIM (registered trademark) (Subscriber Identity Module) card, or an NFC (registered trademark) (Near Field Communication) card identifier.

[0026] According to a particularly advantageous embodiment of the present invention, the second data is a command resulting from the semantic analysis of the first so-called information data and applied by the container. These features allow the second data to be optionally generated and transmitted to the container, and the container to use it, depending on the result of the semantic analysis. Thus, the intelligent dialogue agent can choose to output text or voice messages, or command various actions, in particular, to control light-emitting diodes (LEDs), sirens or loudspeakers, motors, display screens, locking / unlocking devices. Thus, the intelligent dialogue agent can, for example, command a flashing mode for an LED to attract the user's attention.

[0027] According to a preferred embodiment of the present invention, the intelligent dialogue agent is -The first so-called information data is stored in a continuous learning parameter database, - The system is configured to train a model of an intelligent dialogue agent using the continuous learning parameters stored in the database.

[0028] These features allow intelligent conversational agents to increase their knowledge base, improve the quality of their responses, and / or enhance their validity.

[0029] According to a particular aspect of the present invention, training is automated.

[0030] According to a particularly advantageous embodiment of the present invention, the training is deep learning, and each continuous learning parameter has an associated weighting of positive or negative approval of the parameter.

[0031] Therefore, the value of the training data is evaluated using machine learning or deep learning type algorithms, improving the reliability of subsequent semantic analysis.

[0032] According to one embodiment, the container includes means for inputting the first so-called communication data, which is voice capture means and / or text input means.

[0033] These features allow users to communicate with the container by directly querying it verbally in natural language and / or by using input means such as a touch-sensitive or mechanical keyboard or a stylus associated with handwriting recognition. According to certain embodiments of the present invention, the input means is an independent short-range remote control device such as a smartphone, which communicates using short-range wireless communication methods such as Bluetooth®, BLE® (Bluetooth Low Energy), or Wi-Fi® protocols.

[0034] These features allow for the manufacture of containers at a low cost, thereby expanding the target customer base for the product.

[0035] According to an advantageous embodiment of the present invention, the system comprises a text transcription means for the speech capture so that an intelligent dialogue agent receives the first data in text format.

[0036] These features allow users to communicate with the container by speaking, and the voice messages it captures are received by an intelligent conversational agent and converted into text messages that can be directly interpreted by conversational artificial intelligence.

[0037] According to one embodiment, the container includes the second so-called communication data audio playback means and / or display means.

[0038] These features allow users to receive answers to queries they indirectly submit to an intelligent dialogue agent via a container.

[0039] According to an advantageous embodiment of the present invention, the system comprises a means for transcribing second so-called communication data, which is generated in text format by an intelligent dialogue agent. These features allow the user to receive a voice response.

[0040] According to one embodiment, the container is selected from a group that includes luggage and reusable boxes.

[0041] Therefore, in novel and non-obvious ways, reusable boxes, reusable logistics delivery packages, electronic logistics labels intended to be equipped on disposable packages, and luggage such as shipping cases will enable users to interact with various types of information, particularly information that facilitates the use of containers.

[0042] In a particularly advantageous embodiment of the present invention, the intelligent dialogue agent is integrated within the embedded computer unit of the container and / or on a central computer platform configured to communicate with the container.

[0043] These features make it possible to have either a standalone container with localized intelligence or a container supported by intelligence transferred to a remote central computing platform. Furthermore, it is possible to distribute or concentrate the intelligence on either the central computing platform or the container to improve the validity and / or speed of responses, or to distribute the processing load according to the amount of processing power incorporated into the container.

[0044] In addition, the localized intelligence within each container also offers the advantage of improving confidentiality and / or privacy, especially in the case of hand luggage.

[0045] Furthermore, such localized intelligence mitigates the lack of connectivity to the central computer platform in the event of failures in long-range communication means. This also makes it possible to reduce the power consumption of long-range communication modules. This, in turn, makes it possible to manage and therefore minimize 4G data consumption.

[0046] According to a particular embodiment of the present invention, the intelligent dialogue agent is transferred to an external computer platform configured to communicate with the central computer platform.

[0047] These characteristics allow intelligent dialogue agents to be moved to external platforms, such as those of specialized providers.

[0048] According to a particular embodiment of the present invention, the transport system further comprises means for communicating with a global computer network. According to a modified embodiment, the communication means connects a central computer platform and / or external computer platforms to the global computer network.

[0049] These features allow intelligent conversational agents to complete their learning by searching the internet. Furthermore, they can improve the quality of their responses with information collected from global computer networks, such as weather information related to temperature peaks recorded by containers at specific locations.

[0050] According to an advantageous embodiment of the present invention, - The container is configured to identify users, classify identified users into typical conversation profiles, and send typical conversation profiles to an intelligent conversation agent. - The intelligent dialogue agent is configured to adapt semantic analysis according to a typical dialogue profile.

[0051] These features allow the intelligent conversational agent to provide targeted information according to typical conversational profiles, and therefore, according to the user's role, such as a customer receiving a package, a logistics worker responsible for transporting it, or an agent responsible for maintaining a reusable package. Thus, the identified maintenance agent can use voice command keywords to obtain diagnostic information or information or recommendations from after-sales service manuals that are not available to other roles.

[0052] According to one embodiment of the present invention, user identification is achieved through authentication.

[0053] Therefore, this technology can be used to ensure, for example, that only the recipient customer can open the container during delivery.

[0054] According to a particularly advantageous embodiment of the present invention, the intelligent dialogue agent is configured to select a dialogue language in accordance with the location of a container received in first so-called information data. The location, which is a physical positioning quantity, is typically the most recent GPS location of the container. However, it can also be estimated from other information, such as the current cell phone cell, or the known location of the current storage warehouse and / or its Wi-Fi® network to which the container can connect.

[0055] Therefore, the intelligent dialogue agent will converse in the local language if available, and otherwise switch to an international language, typically English, Spanish, or French.

[0056] Advantageously, intelligent dialogue agents use measured location to determine local cultural standards and adapt the generated responses to these standards.

[0057] Certain aspects of the present invention are based on the idea of ​​leveraging advances in artificial intelligence in the dialogue field, particularly using "generative pre-trained transformers" type LLMs (Large-Scale Language Models), such as OpenAI®'s GPT3® and ChatGPT®, Google®'s Bert® and Bard®, or using generative artificial intelligence.

[0058] Other features and advantages of the present invention will become clearer upon understanding the following description of two embodiments of the invention given as simple, explanatory, and non-limiting examples, as well as the accompanying drawings. [Brief explanation of the drawing]

[0059] [Figure 1] Figure 1 is a schematic diagram of an exemplary embodiment of an object transport system featuring a communication container according to the present invention. [Figure 2] This is a schematic diagram of a second exemplary embodiment of intelligent baggage according to the present invention. [Modes for carrying out the invention]

[0060] 1. Exemplary Embodiments of the Invention Figure 1 shows a first embodiment of an object transport system according to the present invention, comprising a container 1, a computer infrastructure 14, and an external computer platform 19.

[0061] The interactive container 1 includes an embedded computer unit 2, data storage means 3, power supply battery 4, microphone 5, loudspeaker 6, digital screen 7, one or more control buttons 8, first communication means 9, and one or more actuators (not shown), and the whole is assembled using essentially known technology.

[0062] It further includes numerous sensors (not shown) to obtain various information related to its storage, transport, or environment. Thus, it may obtain GPS (Global Positioning System) location and motion information used to track its movement, estimate when it has been subjected to impact, estimate whether it has been exposed to vibration, or record drops. Container 1 may also record internal and / or external information such as temperature and atmospheric pressure. These various pieces of information may also include an identifier unique to Container 1, an identifier unique to Computer Unit 2, a SIM (Subscriber Identification Module) card identifier, an NFC (Near Field Communication) code, or any other known identifier essentially known to those skilled in the art.

[0063] The computer infrastructure 14 includes a computer platform 15, a database 16, and a second communication means 17 that communicates with the computer unit 2 of the container 1 via a first communication means 9.

[0064] Furthermore, the computer infrastructure 14 can communicate with the external computer platform 19 using the third communication means 20.

[0065] In this embodiment, the external computer platform 19 is a) Receive the captured data transmitted by container 1 via the computer infrastructure 14, b) Perform semantic analysis on the captured data, c) Generate data resulting from semantic analysis, d) Conversational artificial intelligence modules, typically including software, comprising a conversational agent 18 configured to transmit the resulting data to container 1 via the computer infrastructure 14.

[0066] If the captured data is the first so-called communication data and the resulting data is the second so-called communication data, a dialogue begins. In this case, the first and second communication data are stored by the dialogue agent 18 using essentially known methods to preserve contextual information. As the dialogue progresses, the quality of the dialogue history, composed of this contextual information, improves.

[0067] To initiate a dialogue, the user presses button 8 on container 1. The computer unit then begins capturing speech using microphone 5 and records the voice message spoken by the user. It then sends this captured voice message, called the first captured voice message, to the computer infrastructure 14. The computer infrastructure 14 is equipped with means for converting speech to text, known as "speech-to-text" and "text-to-speech," and is responsible for transcribing the first voice message into a corresponding first text message. The computer infrastructure 14 then sends this first voice message to the dialogue agent 18 on the external computer platform 19.

[0068] In the dialogue, the resulting data is a second text message, which is then received by the computer infrastructure 14. This infrastructure converts the second text message into a second voice message and sends it to container 1. Container 1 then plays the second voice message to the user via the loudspeaker 6, allowing the user to continue the dialogue. Thus, through this series of interactions, container 1 engages in dialogue with the user.

[0069] Furthermore, since it is equipped with other information sources specified above, container 1 is also configured to transmit at least one of various pieces of information that can be used as captured data messages. For example, the transmitted, captured data may convey information about its GPS location. Alternatively, the captured data may include a combination of information such as an identifier, internal temperature, and external temperature measured by container 1.

[0070] Therefore, if the captured data is so-called informational data rather than a user's voice message, the resulting data is a command sent to container 1, which then applies it to at least one actuator. For example, the resulting command might command the unlocking of container 1 and allow the user to open it. However, a user's voice message could be interpreted by the conversational agent 18 as a command to control one of the actuators. Nevertheless, in the configuration of container 1 and / or conversational agent 18, the user is not necessarily able to act on all the actuators equipped in container 1.

[0071] In the context of an object transport system, the set of data that is fed to the dialogue agent 18 by the container fleet contributes to improving the quality of the model.

[0072] Furthermore, contextualizing container 1 makes it possible to guide the conversation to provide the user with the most appropriate information possible regarding container 1, particularly its potential.

[0073] Furthermore, contextual information is provided to the model of the dialogue agent 18 for training, giving it an initial corpus of conditions. Typically, this contextual information relates to container 1, its description, how to use it, possible uses, frequently asked questions from users, sales offers for transporting objects using container 1, or information about businesses that manage a fleet of containers 1 forming an object transport system.

[0074] To do this, the dialogue agent 18 undergoes a specialization of its model, in which it is provided with a set of keywords and associated semantics that form a corpus of initial conditions.

[0075] For example, learning about transportation-related events can be done by following the pseudocode provided below, which will be helpful in the explanation. 「Each stored event is composed of type, value where date is the date of the event, type is the type of the event and value is defined per type as follows: - 'sender': name, address - 'recipient':name, address - 'startShipment': date, latitude,longitude - 'endShipment': date, latitude, longitude - 'sensors':date, 'externalTemperature',measure (in °C), 'internalTemperature', measure (in °C), 'externalHumidity',measure (in %), 'internalHumidity', measure (in %), 'pressure', measure (inhPa) - 'geolocation': date, latitude, longitude - 'warehouse': enterDate, exitDate,latitude, longitude, name - 'flight': fromDate, fromLatitude,fromLongitude, fromAirport, toDate, toLatitude,toLongitude, toAirport - 'alert': date, latitude, longitude,subtype (in 'externalTemperature', 'internalTemperature', 'externalHumidity','internalHumidity', 'freeFall'), measure -'events': You will return every event containing the keyword 'store' as a list without displaying the keyword itself. When 'event' is followed by a type, return every events of the defined type as a list instead of all 'store' keywords and return the closest city instead of raw location coordinates." Learning related semantics can be done as follows: "A duration between two events event A and event B is defined as the difference between the date of the event B and the date of the event A. The duration of an event is defined as the difference between the exitDate and the enterDate of the event or the toDate and the fromDate of the event.” Container 1 is, for example, a transport parcel or package according to the present invention.

[0076] 2. Other exemplary embodiments of the present invention Figure 2 shows a container 1, which appears here in the form of a transport case 10, forming an object transport system according to a second embodiment of the present invention.

[0077] Here too, container 1 is equipped with electronic means including an embedded computer unit 2, data storage means 3, power supply battery 4, microphone 5, loudspeaker 6, and button 8, all assembled in accordance with essentially known technology. The embedded computer unit 2 of transport case 10 is configured to capture requests explicitly made by the user of transport case 10 using the microphone 5 and to emit a response via the loudspeaker 6. Thus, the microphone 5 and loudspeaker 6 form an interface with the user of transport case 10.

[0078] Furthermore, the embedded computer unit 2 is configured to run an intelligent dialogue agent and thus autonomously interact with the user of the transport case 10.

[0079] In addition, the embedded computer unit 2 can receive a specialized corpus, selected according to the intended use of the transport case 10, using the communication means 9. For example, this corpus is specialized for a particular trip by including information on planned transit points such as train stations, airports, and urban transportation infrastructure, as well as information on subway station maps. Thus, the user can obtain information to find their position in the labyrinth of transit points through interaction with the transport case 10.

[0080] In a modified version of the second embodiment, the embedded computer unit 2 communicates with an intelligent dialogue agent 18, which has been moved to a computer infrastructure 14 (not shown) or an external computer platform 19, using communication means 9.

[0081] 3. Any other features and advantages of the present invention Furthermore, the following can be provided in the modified embodiments of the present invention described in detail above. - If the captured data is at least one of various pieces of information, the conversational agent 18 records the captured data in a database for storing continuous learning parameters and trains its model using a technique known as "machine learning". Thus, the conversational agent 18 can train its model on the one hand, and it is configured to train it automatically on the other hand. - The captured data is associated with positive or negative approval weights considered by the model of the conversational agent 18. Thus, the model training takes the form of "deep learning." This improves the statistical analysis performance of the model and, consequently, the validity of the conversational interaction with the user. - Integrate means of identifying and / or authenticating the user into the container to determine the user's role and, consequently, the dialogue profile to be adopted. Identification can be achieved by any known method, such as badges or speech recognition. - Integrate the speech-to-text conversion means into container 1, or transfer this means to an external platform or specialized provider. - The conversational agent 18 is integrated into the computer infrastructure 14, and response time is optimized in particular. - An interactive agent 18 is incorporated into the computer unit 2 of container 1, which functions as a transport package, and thus given autonomy to interact with the user. - An interactive agent 18 integrated into the computer unit 2 receives arbitrarily weighted continuous learning parameters from the computer infrastructure 14. The learning parameters relate to information feedback from the fleet of containers 1 currently in use. - Specialize the intelligent dialogue agent so that it adapts its semantic analysis to the current location of the container. - For example, in the event of a fall detection, a message requesting extra care in handling container 1 is sent, following the analysis of the captured data, based on a set value, in other words, a voice message for the user. - Use a touch-sensitive digital screen as the input and / or output interface between container 1 and the user. - The first communication means 9 is integrated into the electronic means of the transport case 10. - Depending on the customer's specifications, contextualization is performed, and the initial corpus used by the conversational agent 18 is divided to create a fleet specific to each customer of the logistics carrier.

[0082] The aforementioned technology for manufacturing an object transport system that enables interactive interaction can be used with various types of containers, for example, to form cargo transport container type containers.

[0083] It should be understood that the elements shown in the diagram can be implemented in various forms of hardware, software, or combinations thereof. Preferably, these elements are implemented as a combination of hardware and software of one or more multipurpose devices programmed in an appropriate manner, which may include a processor, memory, and input / output interfaces.

[0084] This explanation is illustrative of the principles of this disclosure. Therefore, those skilled in the art will understand that, although not expressly described or shown herein, they can conceive of various designs that embody and fall within the scope of these principles.

[0085] All examples and conditional terms used herein are intended for educational purposes to help readers understand the concepts provided by the inventors to advance the principles and techniques of this disclosure, and should be construed as not being limited to these specifically mentioned examples and conditions.

[0086] Furthermore, all statements relating to the principles, aspects, and embodiments of this disclosure, as well as specific examples thereof, are intended to encompass their structural and functional equivalents. Moreover, these equivalents are intended to include both currently known equivalents and future-developed equivalents, i.e., any developed elements that perform the same function regardless of their structure.

[0087] Accordingly, for example, a person skilled in the art will understand that the principle diagrams described herein represent conceptual diagrams of exemplary circuits that implement the principles of the present disclosure. Similarly, all block diagrams, flowcharts, and other diagrams may be represented in essence on a computer-readable medium and will therefore be understood to represent various processes that can be performed by a computer or processor, whether or not the computer or processor is explicitly depicted.

[0088] The functions of the various elements shown in the diagram can be achieved through the use of dedicated hardware and hardware capable of executing software programs in conjunction with appropriate software programs. Where they are performed by processors, the functions can be performed by a single dedicated processor, a single shared processor, or multiple individual processors, some of which may be shared. Furthermore, the explicit use of the terms “processor” or “controller” should not be interpreted as referring only to hardware capable of executing software programs, but implicitly, without limitation, may include digital signal processors (DSPs), read-only memory (ROM), random access memory (RAM), and non-volatile storage media for storing software programs. Additionally, certain elements may be independent or combined into, for example, a microcontroller (MCU) or a system-on-a-component (SoC, an acronym for System-on-Chip).

[0089] Other conventional and / or personalized software programs may also be included. Similarly, all switches shown in the diagram are purely conceptual. Their functions may be performed by the operation of program logic, by dedicated logic circuits, by the interaction of program instructions and dedicated software programs, or manually, and specific techniques are selectable by the executor, so that they are understood more concretely in context.

[0090] In the claims of this document, any element represented as a means for performing a specified function is intended to encompass any method for performing the function, including, for example, a) a combination of circuit elements for performing the function, or b) any form of software program. The software program consequently includes a microprogram, microcode, or the like, and is combined with appropriate circuitry for executing the software program in order to perform the function. The disclosure as defined by such claims lies in the fact that functions provided by different referred means are combined and brought together in the manner defined in the claims. Accordingly, all means that may provide these functions are considered equivalent to those described herein.

Claims

1. An object transport system that enables interactive communication, A fleet formed from at least one reusable baggage or parcel-type object transport container, Equipped with an intelligent dialogue agent, The at least one container is configured to capture first data that forms a component of the dataset raised by the fleet of containers, The aforementioned intelligent dialogue agent, a) Receiving the first data transmitted by the container, b) Perform semantic analysis of the first data. c) Optionally, generate a second set of data resulting from the semantic analysis, d) Optionally configured to transmit the second data to at least one container, The container is further configured as an object transport system to process the received second data.

2. The first data and the second data are so-called communication data that form an interactive exchange. The first data is provided by the user of the container. The processing of the second data by the container involves transmitting the second data to the user. The aforementioned intelligent dialogue agent further, The context information based on the aforementioned interactive exchange is retained, The object transport system according to claim 1, configured to use the context information during the semantic analysis.

3. The object transport system according to claim 1, wherein the first data is so-called informational data of the type of identifier, physical quantity, or operation setting.

4. The object transport system according to claim 3, wherein the second data is a command that arises from the semantic analysis of the first so-called information data and is applied by the container.

5. The aforementioned intelligent dialogue agent, The aforementioned first so-called information data is stored in a continuous learning parameter database, The object transport system according to claim 3 or 4, configured to train a model of the intelligent dialogue agent using the continuous learning parameters stored in the database.

6. The object transport system according to any one of claims 3 to 5, wherein the intelligent dialogue agent is configured to select a dialogue language according to the location of the container received in the first so-called information data.

7. The object transport system according to any one of claims 1 to 6, wherein the container comprises means for inputting the first so-called communication data, which is a voice capture means and / or a text input means.

8. The object transport system according to claim 7, further comprising a text transcription means for the voice capture object so that the intelligent dialogue agent receives the first data in text format.

9. The object transport system according to any one of claims 1 to 8, wherein the container comprises the second so-called communication data audio playback means and / or display means.

10. The object transport system according to claim 9, further comprising a voice transcription means for the second so-called communication data generated in text format by the intelligent dialogue agent.

11. The object transport system according to any one of claims 1 to 10, wherein the intelligent dialogue agent is integrated within the embedded computer unit of the container and / or on a central computer platform configured to communicate with the container.

12. The object transport system according to claim 12, wherein the intelligent dialogue agent is transferred to an external computer platform configured to communicate with the central computer platform.

13. The container is configured to identify a user, classify the identified user into a typical dialogue profile, and transmit the typical dialogue profile to the intelligent dialogue agent. The object transport system according to any one of claims 1 to 12, wherein the intelligent dialogue agent is configured to adapt the semantic analysis according to the typical dialogue profile.

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