DE102022108295A1 - Method for automatically adjusting the behavior of a mobile user terminal - Google Patents

Abstract

The present invention relates to a method for automatically adjusting the behavior of a mobile user terminal to increase a probability that the mobile user terminal will successfully complete a task that includes, for example, interaction with a human, wherein successful completion of the task includes, for example that the human is caused to engage with an execution device, for example a, in particular mobile, robot device and / or the execution device engages with the human, the method being carried out by a processor in the mobile user terminal.

Description

The present invention relates to a method for automatically adapting the behavior of a mobile user terminal, as well as methods for user-dependent operation of at least one data processing system according to the respective preambles of patent claims 1 and 2.

A task to be solved is to offer a method for automatically adjusting the behavior of a mobile user terminal in a cost-effective and simple manner, in which a filling process, a heating process and/or a cooling process of a product can be completed in a particularly simple and cost-effective manner , such as a container, a treatment process, for example of the filling product, is or includes a treatment process of a container or a treatment object.

This task is solved by the subject matter of claim 1.

Everything independently disclosed for one method regarding one method is disclosed for the other method and vice versa.

The method described here for user-dependent operation of at least one data processing system includes, in a first step, providing at least a first computer unit which, based on a user's user data stored in a database, generates and/or retrieves at least one user profile of the user's usage objects that is uniquely assigned to the user.

For the purposes of the present invention, the user profile is a configuration of a user account of an operating system stored in a system administration. A user profile can include various rights, for example read rights, write rights, connections, installation of programs and deletion rights. These rights are assigned by the respective system administrator as part of user management and can be changed by any other system administrator. The administrators can be one or different users. The administrator, on the other hand, only has a privileged user profile. In order to ensure data protection, the user profiles of others can generally be restricted.

The user's own files and settings are preferably stored in the user profile. This also includes program configuration files.

Particularly sensitive user data can be additionally secured, for example in a root account or protected storage.

The first computing unit can be a computer, a notebook or another computer chip.

In a second step, a second computer unit is provided, which makes at least one usage suggestion to the user for the future use of a usage object, whereby the user can confirm, change and/or reject the usage suggestion and further in the event of a change and/or a rejection of the usage suggestion the second computing unit adapts the user profile to the changed user data by the user.

Such an adaptation can consist of usage data, which is uniquely, preferably uniquely, linked to a corresponding usage object, being changed accordingly in the user profile in order to be able to reflect a changed usage behavior of the individual usage objects.

In a third step, a third computer unit is provided, which then receives the user data transmitted by the first computer unit, the user data being control and/or regulation data, by means of which at least one usage object is controlled and/or regulated.

The present invention is therefore divided into at least three steps. A first step is designated by the operation carried out by the first computing unit and can be referred to as a learning phase of the data processing system.

A second step is defined by the provision of the second computing unit, which can be referred to as a correction phase of the data processing system, with a third learning phase representing an implementation phase, which is represented by the provision of the third computing unit.

According to at least one embodiment, an accuracy rate is calculated by the second and/or the third computer unit, the accuracy being a numerical ratio, in particular a decimal fraction, of proposed usage parameters to usage parameters actually selected by the user, and the user data only when the accuracy threshold value falls below or exceeds be transmitted to a third computer unit. In terms of accuracy It can be this or, alternatively, an estimable or learned action or reaction.

The usage parameters can be a usage time of a usage object during a day, an electricity consumption of a usage object during a day or other consumption of the usage object during a day or a predetermined other operating time.

For example, if the user sets a desired usage time and/or a desired initial usage time in the second computer unit and a decimal fractional ratio to the usage time previously stored in the database is calculated from this then changed usage time, then the corresponding accuracy results. If this value is below or above an accuracy threshold, the user data is transmitted for control by the third computer unit.

An accuracy threshold interval can also be stored in the first and/or second and/or third computing unit, within or outside of which the calculated accuracy must be.

It can therefore be provided that only when a condition has been met in this way is it possible for the first and/or second computing unit to transmit the respective user data to the third computing unit. The third computer unit is preferably the computer unit that controls and/or regulates the corresponding usage object.

According to at least one embodiment, in a first step of the method for user-dependent operation of at least one data processing system, at least a first computing unit is provided, which generates at least one user profile of the user's usage objects that is uniquely assigned to the user on the basis of user data stored in a database.

In a second step, a second computer unit is provided, which makes at least one usage suggestion to the user for the future use of a usage object, whereby the user can confirm, change and/or reject the usage suggestion, and furthermore in the event of a change and/or rejection of the Usage suggestion by the user, the second computer unit adapts the user profile to then changed usage data.

In a third step, a third computer unit is provided, which then receives the user data transmitted by the first computer unit, the user data comprising control and/or regulation data, by means of which at least one usage object is controlled and/or regulated.

According to at least one embodiment, an accuracy rate is calculated by the second and/or the third computer unit, the accuracy being a numerical ratio, in particular a decimal fraction, of proposed usage parameters to usage parameters actually selected by the user and only when the ratio is undercut and/or exceeded an accuracy threshold value, the user data is transmitted to the third computer unit.

It is also conceivable that the first computer unit, the second computer unit and/or the third computer unit are installed in a single or single common computer unit, for example a single integrated chip.

System-on-a-chip (SOC, German a chip system and also called system-on-a-chip) means the integration of all or part of the functions of a system on a chip (DIE), i.e. with integrated circuits ( IC) on a semiconductor substrate (also called monolithic integration). All computer units described above can be installed monolithically integrated with each other, so that they form a single system-on-a-chip.

Such a chip can then perform the different tasks of the computer units described here.

According to at least one embodiment, if the threshold value is undershot and/or exceeded, the second and/or third computer unit (2, 3) sends and/or triggers an error message and/or a correction reaction to the first computer unit (1).

In particular, an error message can be generated if the accuracy deviates by more than 10%, preferably by more than 5%, from the accuracy threshold and/or the accuracy interval and its limits.

According to at least one embodiment, the computer units form a completely independent and preferably self-contained data system in such a way that the establishment of the communication connection and operation of the communication connection between the computer units are exclusively based on Basis of data communication between the computer units. A local communication network can be created here.

In particular, communication between the individual computer units can be structured particularly independently and free from external network and/or Internet influences. An external network component is therefore, for example, a component that is not assigned to the local network described here. The assignment can be done using appropriate IP addressing.

In other words, the method described above and thus the data processing system described above is completely decentralized, so that a complete decoupling of the data processing system described above from a higher-level data processing system (for example the Internet) is possible, which significantly increases private security through the decoupling described above .

A local communication network in the sense of this application can be understood as a personal network (personal area network, abbreviation: PAN) that can be set up and broken down ad hoc by small devices such as PDAs or mobile phones (e.g. smartphones). PANs can therefore be set up using various wired transmission technologies such as USB or FireWire or Ethernet or also using wireless technologies such as IrDA, Bluetooth or WLAN (WPAN). PANs can be used to communicate between devices, but they can also be used to communicate with a larger network (uplink). A PAN created using Bluetooth is called a piconet.

• - dass ihnen eine ID (Identifikation) zugeordnet ist oder wird (beispielsweise durch spezifische Eingabe der ID) und Daten zum Authentifizieren mit Peers (andere Vorrichtungen, die die Erfindung enthalten), und/oder
• - dass ein Reproduzieren von Daten von Peers (wie basierend auf ID und Authentifizierung zur Verfügung gestellt) durchgeführt wird, und/oder
• - die Kontrolle von ausgegebenen Signalen auf Basis dieser Daten durchgeführt wird.

These devices then control, for example, other devices such as lamps (one or many), light switches (one or many), sockets (one or many), etc. thereby

• - that they are or will be assigned an ID (identification) (for example by specifically entering the ID) and data for authenticating with peers (other devices incorporating the invention), and/or
• - reproducing data from peers (as provided based on ID and authentication), and/or
• - the control of output signals is carried out on the basis of this data.

According to at least one embodiment, at least one data set is transferred from one computer unit to the other computer unit or vice versa by means of a separate input element and/or by means of an input element installed in one or more of the computer units. Alternatively, such data transmission can be free of separate input into such an input element, so that data transmission, for example after prior setting, can take place fully automatically to at least one of the computer units.

It is conceivable in this context that such a separate input element can be, for example, a display of a mobile phone or a light switch or another mechanical, electrical or electromechanical element that generates a data record that is sent directly to a computer unit assigned to this input element, preferably uniquely assigned is forwarded. In a computer of the computing unit, this data record generated by the separate input element is then converted into such a data record or such a data packet, which is at least partially written in an HTML language and also contains the structured mark-ups compatible with the HTML-based language elements (structured markups). This then modified data packet is forwarded from a temporary memory of the computer unit back to this computer, which then forwards this modified data packet (HTML data packet), for example in the form of a push notification, to at least one other data computer.

In particular, it is conceivable that a chain reaction takes place in this context, so that this further computer unit (for example the second and/or the third computer unit) modifies this, for example, modified data packet or, through a purely exemplary further modification of this further data packet, further modifies it Data packet is forwarded to an additional data computer (second and / or third computer unit) or any other data computers that form the private communication system. One of the data sets can therefore be displayed on a further separate input element and/or separate output element of one of the computer units, or an output element of a data computer, which is different from the input element of a data computer, can be controlled or regulated by means of this data set, which has been modified at least once. This data transport is therefore preferably not or not only a data transport as part of a relay function. Preferably, on each computer unit, the data fed into this computer unit is changed, i.e. modified, among other things, by adding specific markups.

The term “modification” can either refer to a partial or complete change to the data set, for example with regard to its data set architecture, or “modification” simply means that the data set or data remain unchanged and that everyone can use this unchanged data set or internal indexes and/or context files are attached to and/or connected to one of the data computers, for example for identification purposes. In this respect, it is conceivable that the HTML files generated by a data computer remain identical across the entire system and can only be supplemented by internal indexes and/or context files.

In addition, access and/or access by users can be controlled and monitored particularly easily with regard to the user himself, the location, the time and also generic (for example externally or internally generated) data.

In addition, it is possible that very large files, for example video files, can be exchanged with one another via the private data processing system described above, in particular for example using an e-mail exchange program, since this does not have access to the higher-level Internet.

Address books from input containers, input recovery programs, etc. can also be transferred from one of the data computers to the other. This is made possible, among other things, by the fact that at least one of the computers represents a central computing unit, which is selected, for example, by one or more users (for example via IP addressing) to form a central storage unit on which at least a part, preferably all Data is stored temporarily or permanently. This data is stored by this central computing unit, but is also sent on again by this central storage unit, for example as part of push messages, to the respective decentralized data computers of the private data communication system. However, instead of data transmission based on push messages, a pull message data transmission is possible.

According to at least one embodiment, the data packets include HTML data packets. The communication between the individual computing units and/or the usage objects with one another and the computing units can therefore take place on the basis of an HTML-based communication connection.

In a further step, an HTML-based communication connection is established between the data computers, with data being transferred from one data computer to at least one other data computer after the communication connection has been established. “HTML-based communication connection” refers to any communication connection that is at least partially constructed according to an HTML standard and/or includes the transmission of data packets that are at least partially constructed in the form of an HTML data packet or at least partially contain one.

The term “HTML-based” simultaneously defines and/or forms a communication layer in the sense of registration, within which the data packets are moved. This HTML-based communication layer defined in this way is therefore an application-oriented layer. For example, the data packets represented in this invention do not leave the communication layers defined by the HTML data packet.

This can mean in particular that the communication connection is free of data packets that represent a “deeper” programming language or representation in the sense of the OSI standard compared to the HMTL communication layer described above. In principle, the present invention is therefore based, among other things, on the concept that the communication system described here not only has a predefinable selection of well-defined users who can always be set by the user, but is also a communication system which - after prior specific IP Addressing by the user - but then particularly user-friendly, the HTML layer described above is used as the deepest communication layer.

According to at least one embodiment, at least one, for example exactly one, computer unit (central data computer) within the data processing system is a data memory of the data processing system, with all data packets preferably being sent from the data computer (peripheral computer units) to this data computer and then managed and/or stored by this data computer .

According to at least one embodiment, data from a peripheral computing unit, i.e. at least one of the computing units described above, is restored by retrieving one of the data stored in the central computing unit (also one or more of the computing units described above).

According to at least one embodiment, a computing unit is, in particular, a mobile one User terminal, such as a toothbrush, a coffee machine, or similar.

For example, the mobile user terminal is a robot. A robot, as the term is used here, is an electromechanical machine that contains computer hardware and software that causes the robot to perform functions independently and without assistance from a human. Example robots commercially available today include robot vacuum cleaners and lawn mowers. For example, a conventional commercial robot vacuum cleaner contains computer-executable instructions that, when executed by a processor of the robot vacuum cleaner, cause the robot vacuum cleaner to automatically vacuum a specific area (e.g., a room) based on inputs received from sensors of the robot vacuum cleaner are received. A conventional commercially available robotic lawn mower is configured with computer-executable instructions that, when executed by a processor of the robotic lawn mower, cause such robotic lawn mower to automatically and without human intervention cut grass in a specified area (e.g. B. in a homeowner's garden).

However, it is also possible for the mobile user terminal to be different from a robot. A mobile user terminal is then understood to mean a device that is not operated fully automatically but rather semi-automatically. This can mean that a process can only be completed with the help of a user or another device. In this version, human action is therefore necessary to operate the mobile user terminal. The computing unit can also be a non-mobile user terminal, such as permanently installed devices.

Artificial intelligence ( _“ AI”) is only a few decades old as a scientific discipline and is therefore significantly younger than the classic natural sciences. Nevertheless, it rightly claims the status of its own scientific sector. Your object has a special fascination. The reason for this may be that abstract thinking, creativity and even more so consciousness are widely viewed as generic human abilities. The fact that AI systems increasingly appear to be acquiring or at least imitating these abilities and may soon surpass humans in this respect is no less radical a paradigm shift than the discovery of the heliocentric worldview or biological evolution. AI is also playing an increasingly important role in technological advancement, and there is no indication that this trend will end any time soon.

• Künstliche Intelligenz und maschinelles Lernen basieren auf Rechenmodellen und Algorithmen zur Klassifizierung, Bündelung, Regression und Dimensionalitätsreduktion wie zum Beispiel neuronalen Netzen, genetischen Algorithmen, Support Vector Machines, k-Means, Kernel-Regression und Diskriminanzanalyse. Solche Rechenmodelle und Algorithmen sind per se von abstrakter mathematischer Natur, unabhängig davon, ob sie anhand von Trainingsdaten „trainiert“ werden können. Daher gelten die Leitlinien in G-II, 3.3 in der Regel auch für solche Rechenmodelle und Algorithmen.

The technicality of an invention is crucial for access to patent protection. Whether inventions such as a computer program for machine translation or word processing, for image recognition on satellite images, a computer-based medical diagnostic system or a teaching tutorial for learning a foreign language, a legal tech or autonomous driving system, speech recognition software or a chess computer are to be viewed as technical or not, is not obvious. Nevertheless, the distinction between technical and non-technical inventions developed in its details by case law also has a function of central importance for the promotion of innovation through patents for the new and dynamic sector of AI:

• Artificial intelligence and machine learning are based on computational models and algorithms for classification, pooling, regression and dimensionality reduction such as neural networks, genetic algorithms, support vector machines, k-means, kernel regression and discriminant analysis. Such computational models and algorithms are inherently abstract mathematical in nature, regardless of whether they can be “trained” using training data. Therefore, the guidelines in G-II, 3.3 generally also apply to such calculation models and algorithms.

Expressions such as “support vector machine”, “reasoning engine” or “neural network” can, depending on the context, only refer to abstract models or algorithms and therefore do not necessarily imply the use of technical means in themselves.

Artificial intelligence and machine learning are used in various areas of technology. For example, the use of a neural network in a cardiac monitoring device to identify irregular heartbeats makes a technical contribution. The classification of digital images, videos, audio and speech signals based on low-level features (e.g. edges or pixel attributes for images) is another typical technical application of classification algorithms.

If a classification method serves a technical purpose, the steps “creating the training data set” and “training the classifier” may also contribute to the technical nature of the invention if they help achieve that technical purpose.

According to at least one embodiment, the method includes automatically adjusting the behavior of a mobile user terminal to increase a probability that the mobile user terminal successfully completes a task that includes, for example, interaction with a human, wherein successful completion of the task, for example comprises causing the human to engage with an execution device, for example a, in particular mobile user terminal, and/or the execution device engages with the human, the method being carried out by a processor in the mobile user terminal.

According to at least one embodiment is or includes
the behavior is an operating time, an operating pattern, a filling behavior of a type of filling product preset by the user and/or a filling temperature of the filling product. Preferably everything mentioned above is individually tailored to the user.

According to at least one embodiment, the task is or includes the completion of a filling molding process, a heating and/or cooling process of a product, such as a container, a treatment process for example of the filling product, a treatment process of a container or a treatment object. Preferably everything mentioned above is individually tailored to the user.

For this purpose, the robot device, including, among other things, the mobile user terminal, can comprise at least one actuator, such as a heating or cooling device, a filling device or another treatment unit. This could include, for example, a cooling or heating surface on which a container, such as a cup, is placed so that it can then be filled with the bottling product, such as tea or coffee. For this purpose, a filling neck can also be used as a treatment element, through which the waste product flows into the cup, preferably in a lockable manner.

According to at least one embodiment, the method includes receiving sensor data, which include a, in particular first, signal that is output by a first sensor, wherein the first signal indicates that a human is in an environment of the mobile user terminal, wherein receiving the Sensor data can also be carried out by pressing, heating or by automatic recognition systems, in particular of a person.

According to at least one embodiment, the method comprises a second signal that is output by a second sensor, the second signal indicating a first state of the mobile user terminal, the first state being subject to control by the mobile user terminal and the first state being relevant to the Probability is identified that the mobile user terminal will successfully complete the task.

According to at least one embodiment, the method includes identifying an action to be performed by the mobile user terminal, the action being identified to increase a probability of successful completion of the task. According to at least one embodiment, the identified action is based at least in part on the received sensor data and a model representing successes and failures of the mobile user terminal's past attempts to complete the task with other people.

According to at least one embodiment, a signal is transmitted to an actuator of the mobile user terminal to cause the mobile user terminal to perform the action as an attempt to complete the task.

According to at least one embodiment, an indicator identifies whether the user terminal has successfully completed the task based on a human response to the mobile user terminal performing the action.

According to at least one embodiment, sensor data of the action performed and the identified indication of whether the mobile user terminal has successfully completed the task are provided for adapting the model.

According to one embodiment, the individual users are classified, for example in the form of digital images, videos, audio and voice signals, in particular based on low-level features (e.g. edges or pixel attributes for images).

This classification can be used to make a recommendation to the user, whereby the user can decide whether this recommendation is followed or whether the recommendation needs to be corrected by the user. The then corrected data record also serves, among other things, to increase the probability of successful completion of the upcoming action.

• Empfangen von Sensordaten, die eines ersten Signals umfassen, das von einem ersten Sensor ausgegeben wird, wobei das erste Signal anzeigt, dass sich ein Mensch in einer Umgebung des mobilen Benutzerendgeräts befindet.

According to at least one embodiment, the method for automatically adjusting the behavior of a mobile user terminal to increase a probability that the mobile user terminal successfully completes a task that includes, for example, interaction with a human, wherein successful completion of the task, for example comprises causing the human to engage with an execution device, for example a, in particular mobile, user terminal and/or the execution device engages with the human, the method being carried out by a processor in the mobile user terminal, wherein the method includes:

• Receiving sensor data comprising a first signal output by a first sensor, the first signal indicating that a human is in an environment of the mobile user terminal.

• Identifizieren einer von dem mobilen Benutzerendgerät auszuführenden Aktion, wobei die Aktion identifiziert wird, um eine Wahrscheinlichkeit des erfolgreichen Abschlusses der Aufgabe zu erhöhen, wobei die identifizierte Aktion zumindest teilweise auf den empfangenen Sensordaten und einem Modell basiert, das Erfolge und Misserfolge vergangener Versuche des mobilen Benutzerendgeräts darstellt, die Aufgabe mit anderen Menschen abzuschlie-ßen;
• Übertragen eines Signals an einen Aktuator des mobilen Benutzerendgeräts, um die mobile Robotervorrichtung zu veranlassen, die Aktion als einen Versuch, die Aufgabe zu erledigen, auszuführen.
• Gemäß zumindest einer Ausführungsform ist das Verfahren dadurch gekennzeichnet durch das Identifizieren einer Anzeige, ob das Benutzerendgerät die Aufgabe erfolgreich abgeschlossen hat, basierend auf einer Reaktion des Menschen auf die Durchführung der Aktion durch das Benutzerendgerät; und
• Bereitstellen der Sensordaten, der durchgeführten Aktion und der identifizierten Anzeige, ob das Benutzerendgerät die Aufgabe erfolgreich abgeschlossen hat, zum Anpassen des Modells.

According to at least one embodiment, the method comprises a second signal that is output by a second sensor, the second signal indicating a first state of the mobile user terminal, the first state being subject to control by the mobile user terminal and the first state being relevant to the Probability is identified that the mobile user terminal will successfully complete the task, the method being characterized by further comprising:

• Identifying an action to be performed by the mobile user terminal, the action being identified to increase a probability of successful completion of the task, the identified action based at least in part on the received sensor data and a model that reflects successes and failures of past attempts of the mobile user terminal represents completing the task with other people;
• transmitting a signal to an actuator of the mobile user terminal to cause the mobile robotic device to perform the action as an attempt to complete the task.
• According to at least one embodiment, the method is characterized by identifying an indication of whether the user terminal has successfully completed the task based on a human response to the user terminal performing the action; and
• Providing the sensor data, the action taken and the identified indication of whether the user terminal successfully completed the task to customize the model.

According to at least one embodiment, at least one computer unit has at least one interface to a non-local computer network (Internet), so that a further computer unit connected to the non-local computer network is controlled in order to generate further use of a usage object and/or a further usage object. According to at least one embodiment, at least one computer unit is designed in the form of a system-on-a-chip.

The invention is described in more detail below using an exemplary embodiment and the associated figures. In the 1 an exchange of information within the data system is shown in a schematic representation.

In the 1 It is shown that the method 1000 described here for user-dependent operation of at least one data processing system comprises three computer units, each of which is identified by the reference numbers 1, 2, 3.

In particular, the computer unit 1 can be represented as a behavior database, which is in data communication with the computer unit 2 and stores the respective user behavior. The computer unit 2 can carry out a behavior analysis (or user behavior analysis), whereby the computer unit 3 can carry out the prediction of the behavior.

However, the individual tasks can also be swapped using the computer units described here. In particular, it is shown that all three computer units are in data communication with one another and with one another. The computer unit 1 can communicate directly with the computer unit 3, just as the computer unit 3 can communicate directly with the computer unit 2, which also applies to the computer communication between the computer unit 1 and the computer unit 2.

The computer units 1 to 3 can also be designed as a single data communication element in the form of a “smart device”. These can be integrated into a local budget.

It can also be seen that this smart device includes a control interface 4 and a user ID interface 5, so that the control interface 4 and the user ID interface 5 can communicate independently of one another with the user interface 7 in order to various to be able to connect external usage objects and/or computer units.

In addition, corresponding usage objects 110B of a user are shown at 11B. A user profile is stored in particular in the smart device, but alternatively also in the usage object. The usage objects can be mobile phones, tablets, notebooks, alarm clocks, smart toothbrushes, smart shavers, smart motion sensors, smart mattresses, smart TVs and smart microphones. However, this list is not exhaustive. The usage objects are in direct data communication with the smart device and thus in direct data communication with the computer units 1 to 3.

Both the usage objects and the smart device can communicate with an internal or external database 8.

The usage objects can therefore identify the individual users, for example household users. The usage objects and/or the individual computers can determine and learn the individual usage characteristics, i.e. the individual personal preferences, based on the individual usage wishes of the schedules, moods or other users of the household.

The individual usage objects and/or the individual computing units 1 to 3 then predict the individual usage behavior that is likely to happen in the future based on the user's individual wishes and the user's individual expectations based on personal and environmental factors. Based on the user's response, individual suggestions or behavior patterns of the usage object or the usage of the usage object are predicted, with a corresponding improvement and/or correction of the usage prediction being carried out if there is a deviation outside the threshold values and/or threshold value intervals described above.

The usage objects can only be made available to the user after a personal confirmation or a personal unlocking, in particular on the basis of the learned behavior.

The communication can either be rooted through a local gateway or can be carried out directly between the usage objects, i.e. the smart device and the usage objects.

An example can be the operation of a coffee machine in a household with several people.

The behavior of the residents (setting of the coffee program, such as type, intensity, etc. as well as times of use on different days) is recorded in the learning phase already described above (use of the devices and smart sensor data).

In a correction phase, suggestions are made to the user about the objects of use and/or the smart device, which includes, for example, an offer for the preset coffee program at certain times of the day or occasions.

If the user makes a different choice, this is first analyzed by the second computer unit and linked to other external influences (such as the daytime temperature, ambient air humidity, ambient temperature).

The presence of other people in the room or in the household may also depend on this.

In an implementation phase, the accuracy of the suggestions made is preferably above a certain threshold that can be confirmed by the user. This allows the smart device to independently control certain actions, such as switching on the device at a certain time, preheating, making program preselections, etc. The suggestions are preferably prepared and offered independently.

In particular, it can be provided that data exchange between the smart devices placed in the household and the smart sensors (usage level) with internally based external intelligence or databases is prevented.

Preferably, for example, such data exchange is not possible. The gateway can be used for local data storage and control. This means that those affected have the opportunity to monitor and/or delete this database at any time. A connection to internet-based services, such as ordering consumables such as food, detergent, etc. or repair services, can be made through a controlled and monitored interface as described above.

The 2 shows, in one embodiment, a method 400 for automatically adjusting the behavior of a mobile user terminal 102, to increase a probability that the mobile user terminal 102 successfully completes a task 408 that includes, for example, an interaction with a human 104, wherein successful completion of the task includes, for example, causing the human 104 to interact with an execution device , for example a, in particular mobile, user terminal 102 to engage and / or the execution device with the human 104 engages, the method 400 being carried out by a processor 220 in the mobile user terminal 102, the method 400 comprising: receiving of sensor data 302, which include a, in particular first, signal that is output by a first sensor 404, the first signal indicating that a person 104 is in an environment 100 of the mobile user terminal 102.

• Identifizieren einer von dem mobilen Benutzerendgeräts 102 auszuführenden Aktion, wobei die Aktion identifiziert wird, um eine Wahrscheinlichkeit des erfolgreichen Abschlusses der Aufgabe zu erhöhen, wobei die identifizierte Aktion zumindest teilweise auf den empfangenen Sensordaten 302 und einem Modell 306 basiert, das Erfolge und Misserfolge vergangener Versuche des mobilen Benutzerendgeräts 102 darstellt, die Aufgabe 408 mit anderen Menschen 104 abzuschließen;
• Übertragen eines Signals an einen Aktuator 410 des mobilen Benutzerendgeräts 102, um das mobilen Benutzerendgeräts 102 zu veranlassen, die Aktion als einen Versuch, die Aufgabe 408 zu erledigen, auszuführen.

2 a second signal can also be seen, which is output by a second sensor 406, the second signal indicating a first state of the mobile user terminal 102, the first state being subject to control by the mobile user terminal 102 and the first state being relevant for the Probability is identified that the mobile user terminal 102 will successfully complete the task 408, the method 400, further comprising:

• Identifying an action to be performed by the mobile user terminal 102, the action being identified to increase a probability of successful completion of the task, the identified action based at least in part on the received sensor data 302 and a model 306 representing successes and failures of past attempts of the mobile user terminal 102 represents completing the task 408 with other people 104;
• Transmitting a signal to an actuator 410 of the mobile user terminal 102 to cause the mobile user terminal 102 to perform the action as an attempt to complete the task 408.

Also is from the 2 identifying an indication of whether the robot 102 has successfully completed the task 408 based on a response of the human 104 to the robot 102 performing the action; and providing the sensor data 302, the action taken, and the identified indication of whether the mobile user terminal 102 has successfully completed the task 408 to customize the model 306.

The invention is not limited by the description and the exemplary embodiment. Rather, the invention encompasses every new feature and every combination of features, which also includes in particular every combination of the patent claims, even if this feature or this combination itself is not explicitly disclosed in the patent claims or in the exemplary embodiment.

Reference symbol list

1

Computer unit

2

Computer unit

3

Computer unit

4

Control interface

5

User ID interface

7

interface

8th

internal or external database

11

Database

11A

User data

11B

User

11C

User profile

100

Data processing system

101

Vicinity

102

mobile user terminal

104

Person

110B

Usage objects

220

processor

302

Sensor data

306

Model

400

Proceedings

404

first sensor

406

second sensor

408

Task

410

actuator

1000

Proceedings

Claims (10)

Method (400) for automatically adjusting the behavior of a mobile user terminal (102) to increase a probability that the mobile user terminal (102) successfully completes a task (408) that involves interaction with a human (104), wherein it - the behavior is an operating time Operating pattern, a filling behavior of a type of filling product preset by the user and / or a filling temperature of the filling product is or includes, and further wherein - the task is the completion of a filling molding process, a heating and / or a cooling process of a product, such as a container, a treatment process for example the filling product, a treatment process of a container or a treatment object, wherein successful completion of the task includes causing the human (104) to engage with a mobile robot device (102) and/or the robot device engages with the human (104), the method (400) being carried out by a processor (220) in the mobile user terminal (102), the method (400) comprising: receiving sensor data (302) which is a first , signal, which is output by a first sensor (404), the first signal indicating that a person (104) is in an environment (101) of the mobile user terminal (102), the method (400) further comprises: identifying an action to be performed by the mobile robotic device (102), the action being identified to increase a probability of successful completion of the task, the identified action being based at least in part on the received sensor data (302) and a model (306). based, which represents successes and failures of past attempts by the mobile robotic device (102) to complete the task (408) with other people (104); Transmitting a signal to an actuator (410) of the mobile robotic device (102) to cause the mobile robotic device (102) to perform the action as an attempt to complete the task (408). Procedure according to Claim 1 , characterized in that a second signal output by a second sensor (406), the second signal indicating a first state of the mobile user terminal (102), the first state being subject to control by the mobile user terminal (102) and the first state is identified as relevant to the probability that the mobile user terminal (102) will successfully complete the task (408). Procedure according to Claim 1 , characterized by identifying an indication of whether the robot (102) has successfully completed the task (408) based on a response of the human (104) to the robot (102) performing the action; and providing the sensor data (302), the action taken and the identified indication of whether the robot (102) successfully completed the task (408) to customize the model (306). Method (1000) for user-dependent operation of at least one data processing system (100), - providing at least one first computer unit (1), which, based on user data (11A) of a user (11B) stored in a database (11), at least one of the user (11B) 11B) generates and/or retrieves a uniquely assigned user profile (11C) of usage objects (110B) of the user (11B), - providing a second computer unit (2) which provides the user (11B) with at least one usage suggestion for the future use of a usage object (110B). makes, whereby the user (11B) confirms, changes and/or rejects the usage suggestion, and further wherein in the event of a change and/or rejection of the usage suggestion by the user (11B), the second computer unit (2) displays the user profile (11C). then adapts changed user data, - providing at least one third computer unit (3), which then receives the user data transmitted by the first computer unit (1), the user data being control and / or regulation data by means of which at least one usage object (110B) is controlled and / or is regulated. characterized in that an accuracy rate is calculated by the second and/or the third computer unit (2, 3), the accuracy being a numerical ratio, in particular a decimal fraction, of proposed usage parameters to usage parameters actually selected by the user, and only from below - or if an accuracy threshold value is exceeded, the user data is transmitted to the third computer unit (3). Procedure (1000) according to Claim 1 or 2 , characterized in that if the threshold value is undershot and/or exceeded, the second and/or third computer unit (2, 3) sends and/or triggers an error message and/or a correction reaction to the first computer unit (1). Method (1000) according to at least one of the preceding claims, characterized in that all computer units (1, 2, 3) form a completely independent and, preferably technically self-contained, data system, such that the establishment of the communication connection and operation of the communication connection between the computer units (1, 2, 3) is based exclusively on data communication between the computer units (1, 2, 3) with one another. Method (1000) according to at least one of the preceding claims, characterized in that all data packets for operating and establishing the communication connection are stored exclusively in at least one of the computer unit (1). Method (1000) according to the preceding claim, characterized in that the data packets are exchanged between the computer unit (1) on the basis of an email exchange system. Procedure (1000) according to Claim 6 , characterized in that the data packets include HTML data packets. Procedure (1000) according to Claim 6 , characterized in that at least one, for example exactly one, computer unit (1, 2, 3) computer unit (1) within the data processing system (100) is a data memory of the data processing system (100), wherein, preferably all, data packets from the data computers ( peripheral computer units) (1) are sent to this data computer and then managed and/or stored by this computer unit (1).

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