Sensor for generating power management data

Abstract

A sensor with a control unit, the sensor being configured to analyze data available to the sensor, in particular measurement data of the sensor, to generate power management data, wherein the power management data are configured for selecting a power saving mode from a plurality of available power saving modes of a wireless module (103) of the sensor and / or for controlling a time of a measurement interval of the sensor and / or for power management of the sensor.

Description

TECHNICAL FIELD

[0001] The present invention relates to process automation, in particular in an industrial environment. In particular, the present invention relates to a sensor, in particular a self-learning sensor, a control unit for such a sensor, a measurement system having one or more such sensors, a method for a possible self-learning planning of a measurement interval and a possible self-learning power management for a sensor, program elements, computer-readable media and the use of a computing unit in a measurement system. BACKGROUND

[0002] In process automation in an industrial environment, sensors such as fill level sensors, limit level sensors, pressure sensors or flow sensors are used. In order to save energy, these sensors are periodically or according to a fixed time pattern switched on and a measurement process is triggered. Thereafter, the sensor is switched off again or enters a low-energy (low-power) standby mode. SUMMARY

[0003] It is an object of the present invention to reduce the energy demand of a sensor.

[0004] A first aspect of the present disclosure relates to a possible self-learning sensor having a control unit configured to analyze data available to the sensor, in particular measurement data and / or other data of the sensor, to generate power management data. The power management data is configured for selecting a power saving mode of a wireless module of the sensor from a plurality of available power saving modes and / or for controlling a time of a measurement interval of the sensor and / or for a power management of the sensor.

[0005] The term "control unit" should be interpreted broadly. The control unit can be a coherent unit; however, it can also be arranged dispersedly in the sensor and / or its environment, for example in the cloud. For example, the control unit is a circuit having a processor.

[0006] According to an embodiment, the plurality of available power saving modes comprises a power saving mode (PSM: Power Saving Mode).

[0007] According to an embodiment, the plurality of available power saving modes comprises an extended discontinuous reception (eDRX: extended discontinuous reception) mode.

[0008] According to an embodiment, the plurality of available power saving modes comprises deactivating the wireless module.

[0009] According to an embodiment, the control unit is configured to consider an energy required when running the power saving mode when analyzing the data available to the sensor and when selecting the power saving mode from the plurality of available power saving modes.​

[0010] According to an embodiment, the control unit is configured to consider the maximum allowed duration in the power saving mode before communication must be performed again when analyzing the data available to the sensor and when selecting the power saving mode from the plurality of available power saving modes.

[0011] According to an embodiment, the control unit is configured to consider the energy required for re-registration or re-dial-in in the communication network when analyzing the data available to the sensor and when selecting the power saving mode from the plurality of available power saving modes.

[0012] According to an embodiment, the control unit is configured to consider external influences such as temperature, utilization of the radio channel or movement of the sensor when analyzing the data available to the sensor and when selecting the power saving mode from the plurality of available power saving modes.

[0013] According to an embodiment, the control unit is configured to consider the frequency of the current measurements when analyzing the data available to the sensor and when selecting the power saving mode from the plurality of available power saving modes.

[0014] According to an embodiment, the data available to the sensor also includes measurement data of neighboring sensors, environmental data of the sensor or of external sensor systems, position data and / or orientation data, signals of external actuators such as pumps, signals of external controllers or mobile terminals and / or calendar entries, information about public holidays, non-working days or times when, for example, a container is expected to be filled.

[0015] According to another embodiment, the control unit is configured to reduce or increase the frequency of future measurement intervals within a certain time interval based on the analysis of the data available to the sensor. For example, if the control unit comes to the conclusion during its analysis that the measurement data is not expected to change within a certain time interval in the future, for example due to a constant fill level in the container, the number of measurement intervals within this time interval can be reduced or even set to zero. However, if the control unit comes to the conclusion that the measurement data is expected to change very likely during a certain time interval in the future, for example due to filling or emptying the container, the control unit can increase the frequency of the measurement intervals within this time interval.

[0016] According to another embodiment, the control unit is configured to determine a first time interval in which a change in the measurement data of the sensor is expected based on the analysis of the data available to the sensor and to schedule one or more future measurement intervals within this first time interval. For this purpose, a quick, energy-saving and less accurate pre-measurement can be made to identify whether the fill level can have changed, thereby generating additional data for the controller.

[0017] According to another embodiment, the control unit is configured to determine, on the basis of the analysis of the sensor available data, a second time interval in which no change in the measurement data of the sensor is expected and to reduce the number of future measurement intervals planned within this second time interval.

[0018] According to another embodiment, the control unit is configured to adjust, on the basis of the analysis of the sensor available data, the frequency of future measurement intervals within a certain time interval in dependence on the rate of change of the measurement data expected within this time interval. For example, if the control unit can conclude that the expected rate of change is rather high, the frequency of future measurement intervals within this time interval is increased further, and vice versa.

[0019] According to another embodiment, the possibly self-learning sensor has an internal energy store and is configured to be operated self-sufficiently.

[0020] In particular, a radio interface can be provided through which the possibly self-learning sensor can communicate with an external control unit or an external computing unit. The sensor can be configured to transmit measurement data to such an external unit at certain times.

[0021] In this case, the external unit can take over the analysis task or at least part of the analysis task and then load its own, new power management data to the sensor.

[0022] In particular, the external unit can communicate with a large number of sensors and collect data from them. The external unit can also collect other data such as calendar entries and then generate its own power management data for each individual sensor from these data and then load this power management data to the sensor. This process can be carried out in a self-learning and automatic manner, so that the sensors gradually save more and more energy and, in other words, do not perform "unnecessary" measurements or reduce the time of these unnecessary measurements constantly. In this case, "unnecessary" measurements in particular refer to new measurement results which do not lead to a change compared to previous measurement results, for example, due to the fill level not changing or only changing very slowly.

[0023] In particular, the possibly self-learning sensor can be configured for process automation in an industrial environment.

[0024] For example, the sensor can be a fill level sensor, a limit level sensor, a flow sensor or a pressure sensor. In particular, a radar sensor, an ultrasonic sensor, a radiometric sensor, a vibration sensor, a capacitive sensor or a conductive sensor.

[0025] Another aspect relates to a control unit for a possibly self-learning sensor, which control unit is configured to analyze data available to the sensor, in particular to analyze measurement data of the sensor, in order to generate power management data, wherein the power management data are configured for selecting a power saving mode of a wireless module of the sensor from a plurality of available power saving modes and / or for controlling a time of a measurement interval of the sensor and / or for power management of the sensor.

[0026] In particular, the control unit can be arranged remote from the sensor and can exchange data with the sensor via a wired interface or a radio interface.

[0027] Another aspect of the present disclosure relates to a measurement system configured to autonomously generate power management data for a possibly self-learning control of a measurement interval and a self-learning power management of a sensor. The measurement system has one or more self-learning sensors as described above and below and a control unit as described above and below and / or a computing unit as described above and below, which is configured to store power management data and to transfer the stored power management data to a new sensor of the measurement system.

[0028] When a new sensor is added to the measurement system, the sensor can automatically download its individual power management data from the computing unit or the control unit at runtime. In this case, the individual sensor can be relatively weakly constructed and, in the simplest case, can only execute the control commands contained in the imported power management data and carry out corresponding measurements and transmit the measurement results to an external unit at certain times.

[0029] Another aspect of the present disclosure relates to a method for a possibly self-learning planning of a measurement interval and for a possibly self-learning power management of a sensor, in which method data available to the sensor are analyzed, in particular measurement data of the sensor, in order to generate power management data, wherein the power management data are configured for selecting a power saving mode of a wireless module of the sensor from a plurality of available power saving modes and / or for controlling a time of a measurement interval of the sensor and / or for power management of the sensor.

[0030] Another aspect relates to a program element which, when executed on a control unit of a possibly self-learning sensor or on a computing unit as described above and below, instructs the control unit or the computing unit to carry out the above-described steps.

[0031] Another aspect relates to a computer-readable medium having stored the above-described program element.

[0032] Another aspect relates to the use of a computing unit in a measurement system for storing power management data and for transferring the stored power management data to a new sensor in the measurement system.

[0033] The term "process automation in industrial environments" can be understood as a subfield of technology which comprises all measures for operating machines and devices without human involvement. One goal of process automation is to automate the interaction of individual components of a plant in the chemical, food, pharmaceutical, petroleum, paper, cement, shipping or mining industry. For this purpose, a large number of sensors can be used which are particularly suitable for the specific requirements of the process industry, such as mechanical stability, insensitivity to contaminants, extreme temperatures, extreme pressures, etc. The measured values of these sensors are usually transmitted to a control room in which process parameters such as fill level, limit level, flow, pressure or density can be monitored and settings of the entire plant can be changed manually or automatically.

[0034] One subfield of process automation in industrial environments relates to logistics automation. In the field of logistics automation, processes are automated within a building or within individual logistics devices by means of distance sensors and angle sensors. Typical applications are logistics automation systems for example for the field of baggage and cargo handling at airports, the field of traffic monitoring (toll systems), the field of trade, parcel delivery or also the field of building security (access control). The common ground of the previously listed examples is that in each application area the combination of presence detection with precise measurement of object size and position is required. For this purpose, sensors based on optical measurement methods by means of laser, LED, 2D camera or 3D camera can be used which detect distances according to the time-of-flight principle (ToF).

[0035] Another subfield of process automation in industrial environments relates to factory / manufacturing automation. Examples of such applications can be found in many industries such as automotive manufacturing, food manufacturing, pharmaceuticals or generally packaging industries. The goal of factory automation is to automate the production of goods performed by machines, production lines and / or robots, i.e. to run without human involvement. The sensors used here and the specific requirements for measurement accuracy when detecting the position and size of objects are comparable to those in the logistics automation examples described above.

[0036] The program element can be loaded and / or stored in a main memory of a data processing device, such as a data processor, which can also be part of an embodiment of the present application. The data processing device can be configured to execute the method steps of the above-described method. The data processing device can also be configured to automatically execute the computer program or method and / or to execute input from a user. The computer program can also be provided via a data network, such as the Internet, and downloaded into the main memory of the data processing device from such a data network. The computer program can also comprise an update for an existing computer program, thereby enabling the existing computer program to execute, for example, the above-described method.

[0037] In particular, the computer-readable (storage) medium can, but does not necessarily, take the form of a non-volatile medium such as a ROM, DVD-ROM, optical storage medium, solid state medium, etc. that is specifically adapted to store and / or distribute computer programs. The computer-readable storage medium can be provided together with other hardware, e.g. as part of a kit, or it can be distributed separately. Alternatively or in addition, the computer-readable storage medium can also be distributed in other forms, e.g. via a data network such as the Internet or other wired or wireless telecommunication systems. To this end, the computer-readable storage medium can for example be embodied as one or more data packets.

[0038] Further embodiments will be explained below with reference to the accompanying drawings. The illustrations in the drawings are schematic and not to scale. Identical or similar elements are referred to by the same reference signs in the following description of the figures. BRIEF DESCRIPTION OF DRAWINGS

[0039] Figure 1 A time diagram of the measurement intervals of two sensors is shown.

[0040] Figure 2 Another time diagram of the measurement intervals is shown.

[0041] Figure 3 An overview of examples of possible data sources for a self-learning sensor is shown.

[0042] Figure 4 A measurement system according to an embodiment is shown.

[0043] Figure 5 A flow chart of a method according to an embodiment is shown. DETAILED DESCRIPTION

[0044] Figure 1 A time diagram of the measurement intervals 105 of a sensor before a self-learning process and of the measurement intervals 106 of the sensor that can be self-learned during or after the above-mentioned self-learning process with intelligent power management is shown.

[0045] The measurement curve 107 shows the time course of the measurement data (e.g. fill level, pressure or flow rate) detected by the sensor. The fill level decreases on the working days from Monday to Friday and remains constant from Friday afternoon to Monday morning.

[0046] The "inexperienced" sensors run in a fixed time pattern with constant time spacing between the individual measurement intervals 105. This leads to intensive energy consumption and can result in regular, premature replacement of the used batteries or accumulators. If the energy stores cannot be replaced, this requires maintenance work or even the purchase or reinstallation of the sensors.

[0047] By means of a possibly self-learning process, the sensors learn not to measure according to a fixed, rigid time pattern, but only when it is necessary to measure. Thus, the energy consumption of the sensors can be significantly reduced.

[0048] In this way, a low-maintenance and energy-saving sensor system (measurement system) with possibly self-learning sensors can be realized, in which each sensor calculates or receives its own power management data, which are regularly adapted to the measurement environment.

[0049] The measurement intervals 106 show that the sensors have "learned" that it is only necessary to measure in those time intervals in which the measurement data also changes, i.e. when the curve 107 has a slope and is equal to zero (because the filling level is falling). No measurement is made during the plateau.

[0050] Figure 2 Another example of the time distribution of the measurement intervals is shown. Here, too, measurements are only made in the time intervals in which the filling level is falling. The lower the filling level (especially on Fridays), the more frequently measurements are made during emptying, so that it can be prevented that the container is emptied.

[0051] The measurements are triggered by intelligent measurement intervals and power management.

[0052] Thus, the energy consumption of the entire measurement point can be significantly reduced. No measurements are made on non-working days or when the storage tank is stored in the silo filling station.

[0053] The possibly self-learning measurement intervals can be generated, for example, by the following data:

[0054] Analysis of the own level measurement data (day, night, rest time, storage tank capacity (less measurement when the tank is full), emptying process (less measurement when small extraction volume));

[0055] Analysis of the measurement data from the sensor network;

[0056] Analysis by an internal or external sensor system (for example, environmental data, location data or position data);

[0057] Analysis by an external signal from an external actuator (for example, a pump), a controller or a mobile terminal;

[0058] Analysis of predetermined settings or calendar (e.g. weekends, public holidays, company holidays).

[0059] The sensor can be configured to learn the optimal time of measurement independently by drawing on experience from the above-mentioned data.

[0060] Thereby, the battery life and / or the sensor life can be prolonged.

[0061] The sensor becomes more intelligent through its self-learning process and the increasingly longer self-learning times and saves energy more effectively.

[0062] The sensor can automatically adjust the time and length of the measurement interval and the measurement frequency in this measurement interval accordingly when unforeseen changes in the filling level occur. An example of this is a temporary Saturday work. Measurements are carried out on the following Saturdays until the filling level changes no longer occur on Saturdays.

[0063] In particular, the experience values of the sensor can be transmitted to other sensors of the customer. The experience values of one / more sensors can be stored locally or scattered in the cloud for further processing. The way of triggering measurements by intelligent measurement intervals and power management can be used for self-sufficient sensors with energy stores as well as for wired sensors. The sensors can be installed fixedly or used in a mobile manner.

[0064] The module for generating intelligent measurement intervals and power management can be integrated permanently in the sensor or used as an extension to existing measurement points.

[0065] Figure 3 Examples of possible data sources for a possibly self-learning sensor 100 are shown.

[0066] Possible data sources for the sensor usable data for the analysis are the sensor's own data, for example measurement values, information about emptying processes and filling processes.

[0067] Another example is data available in an external data memory, for example data available in the cloud. In this case, the data is, for example, calendar entries, calendar data or data from other sensors.

[0068] Another example is data and signals from external actuators (e.g. "pump is running" or "factory control").

[0069] Another example is environmental data such as temperature, wind, rain, snow, etc.

[0070] Another example is position and orientation data, for example information about whether the sensor is installed horizontally or vertically, or whether the container is placed horizontally or vertically, or whether the container is in a construction site or in a warehouse.

[0071] Another example is data from a mobile device, for example the presence of an operator or a trigger signal emitted by an application (App).

[0072] Figure 4 A measurement system is shown, which has a plurality of possibly self-learning sensors 100, a new sensor 300, a control unit 101 located in one of the possibly self-learning sensors, another control unit 101 located outside the possibly self-learning sensors and a central processing unit 200.

[0073] The processing unit is configured to receive data from all sensors and to evaluate these data centrally. In addition, the processing unit can also be configured to collect data about Figure 3 The data described are collected and included in the analysis in order to generate individual power management data for each sensor, which can then be transmitted to the sensors. In particular, the sensors 100 have a wireless module 103 for transmitting measurement data.

[0074] A self-sufficient sensor 100 with a mobile radio module (mobile radio modem, mobile radio chip for e.g. "NB-IoT", "LTE-M1", etc.) has to dial in to the network operator before the first transmission of data. In this case, a data connection and registration with the respective network operator takes place via a mobile radio mast. As long as the device is registered in the network, there is no need to dial in again, whereby energy is saved. In this case, the wireless module 103 has to be permanently supplied with power in order to be able to communicate regularly with the radio mast.

[0075] If no data communication is required for a long time, the wireless module can be set to a power saving mode (e.g. eDRX, PSM, etc.), whereby the power required for the wireless module can be reduced from a few milliamps to a few microamps. In these modes, there is also no need to dial in to the cellular network again.

[0076] Thus, in the case of a self-sufficient sensor, the battery life is significantly improved. In the case of a grid-powered (230 V) or interface-powered (4-20 mA) sensor, the power consumption is reduced.

[0077] If the sensor 100 is not required for a very long time, it is advantageous to completely deactivate the wireless module 103 in order to save the power requirement of a few microamps in the power saving mode. However, this makes it necessary to register again in the cellular network before data is transmitted.

[0078] Self-supplied sensors usually send data via mobile communication only at specified times. For example, every two hours from 8:00 a.m. to 4:00 p.m. on weekdays. However, at night and on weekends, no or only every eight hours. It is therefore advantageous to switch off or deactivate the mobile radio module during long periods of inactivity.

[0079] One or more of the following factors can be taken into account when deciding which power saving mode to use or switch off. Not only the current value of a factor can be taken into account, but also one / more historical / old values and values that can be expected in the future:

[0080] 1. Available power saving modes (eDRX, PSM, etc.)

[0081] 2. Energy required for the respective power saving mode; this can be measured / determined during operation or be an expected value (default value).

[0082] 3. Mobile communication technology used (NB-IoT, LTE-M1, etc.).

[0083] 4. Desired / planned time in the power saving mode.

[0084] 5. Maximum allowed duration in the respective power saving mode before communication must take place again (determined by the network operator).

[0085] 6. Frequency band used for communication (is the frequency band to be used known? Number of frequency bands tested by dialing; different power requirements for different frequency bands).

[0086] 7. Energy required for new registration / dial-in (measured / determined during operation; expected value (default value); in short, here the time required for the dial-in procedure can be used (measured or predetermined)).

[0087] 8. Transmission power during dial-in.

[0088] 9. Reception quality of the mobile radio link.

[0089] 10. Which power saving mode is more advantageous for the power supply? Is the power supply designed for the low power requirement in the power saving mode or is it efficient (efficient)? Is it possible to prevent passivation of a lithium thionyl chloride battery, for example?

[0090] 11. External influences, such as temperature, utilization of the radio channel, movement of the sensor and associated radio unit changes. Is the sensor currently moving? Is it possible or certain that the sensor will move?

[0091] The factors listed above can also change the selection of the power saving mode (eDRX, PSM, etc.) to be used.

[0092] Thus, a method is provided for making a decision when to select a power saving mode or to deactivate the mobile radio module in order to optimize the run-time of a self- sufficient sensor or to reduce the power consumption of a continuously powered sensor.

[0093] For example, the control unit 101 is programmed as follows: from 8:00 to 16:00 on weekdays, data is transmitted by mobile radio every two hours. From 16:00 to 8:00 on weekdays, data is transmitted every four hours. On weekends and public holidays, the rhythm between data transmissions is eight hours.

[0094] By using a plurality of the above factors, the sensor and the control unit calculate that the power saving mode PSM in the two-hour rhythm has an energy advantage. In the four-hour rhythm, the device is operated in the power saving mode eDRX. After the transmission break of six hours, the radio module is deactivated in order to save the static current of a few microamperes.

[0095] Figure 5 A flowchart of the method according to the embodiment is shown. In step 501, various data are collected. In step 502, these data are analyzed centrally (or by the sensor) and, in step 503, power management data are generated therefrom. These power management data have commands for selecting a power saving mode of the radio module from a plurality of available power saving modes and / or for controlling the time of the measurement interval of the sensor and / or for the power management of the sensor.

[0096] Furthermore, it is to be noted that "comprising" and "including" do not exclude other elements or steps, and "a" or "an" does not exclude a plurality. Also, it is to be noted that a feature or step described with reference to one of the above exemplary embodiments can also be used with reference to another of the above exemplary embodiments. Reference signs in the claims are not to be construed as limiting the respective claims.

Claims

1. A sensor (100) comprising: A control unit (101) is configured to analyze data available from the sensor, including measurement data from the sensor and data from an external data storage device, and the control unit (101) generates power management data based on the analysis of the measurement data from the sensor and the data from the external data storage device. A wireless module (103) is configured to transmit measurement data; The control unit is configured to select a power-saving mode for the wireless module (103) from a plurality of available power-saving modes using the power management data, and to control the measurement interval of the sensor. If the wireless module (103) of the sensor (100) does not need to perform data communication for the desired duration of a first time interval, the control unit is configured to select either an extended discontinuous reception mode or an energy-saving mode as a power-saving mode. If the desired duration for which the wireless module (103) of the sensor (100) does not need to perform data communication is longer than the first time interval, the control unit is configured to select deactivation of the wireless module (103) as a power-saving mode. The control unit (101) is configured to reduce or increase the frequency of future measurement intervals within a specific time interval based on the analysis of data available to the sensor, and when analyzing the data available to the sensor and when selecting the power-saving mode from the plurality of available power-saving modes, to consider the energy required to run the power-saving mode, to consider the maximum permissible duration in the power-saving mode before communication must be resumed, and / or to consider the energy required for re-registration or re-dialing in the communication network.

2. The sensor (100) according to claim 1, in, The control unit (101) takes into account external influences when analyzing the data available from the sensor and when selecting the power-saving mode from the plurality of available power-saving modes.

3. The sensor (100) according to claim 2, in, The external influences are temperature, use of the radio channel, or movement of the sensor.

4. The sensor (100) according to claim 1 or 2, in, The control unit (101) considers the frequency of the current measurement when analyzing the data available from the sensor and when selecting the power-saving mode from the plurality of available power-saving modes.

5. The sensor (100) according to claim 1 or 2, in, The data available from the sensor is the sensor's measurement data.

6. A control unit (101) for a sensor (100), the control unit being configured to analyze data available to the sensor to generate power management data, the data including measurement data of the sensor and data from an external data storage device; in, The control unit (101) is configured to analyze data available from the sensor to generate power management data based on the analysis of the measurement data from the sensor and the data from the external data storage. The control unit (101) is configured to select a power-saving mode from a plurality of available power-saving modes of the wireless module (103) of the sensor using the power management data and to control the measurement interval of the sensor. If the wireless module (103) of the sensor (100) does not need to perform data communication for the expected duration of the first time interval, the control unit is configured to select an extended discontinuous reception mode or an energy-saving mode as a power-saving mode. If the desired duration for which the wireless module (103) of the sensor (100) does not need to perform data communication is longer than the first time interval, the control unit is configured to select deactivation of the wireless module (103) as a power-saving mode; and The control unit (101) is configured to reduce or increase the frequency of future measurement intervals within a specific time interval based on the analysis of data available to the sensor, and when analyzing the data available to the sensor and when selecting the power-saving mode from the plurality of available power-saving modes, to consider the energy required to run the power-saving mode, to consider the maximum permissible duration in the power-saving mode before communication must be resumed, and / or to consider the energy required for re-registration or re-dialing in the communication network.

7. The control unit (101) according to claim 6, in, The control unit (101) is arranged remotely from the sensor (100).

8. A measurement system configured to autonomously generate power management data for controlling measurement intervals and for power management of sensors (100, 300), said measurement system comprising: The sensor (100) according to any one of claims 1 to 5; According to claim 6 or 7, the control unit (101) and / or the computing unit (200) are both configured to store the power management data and transmit the stored power management data to a new sensor (300) of the measurement system.

9. A method for planning measurement intervals and for power management of a sensor (100), the method comprising the steps of: Analyze the data available from the sensor, including the sensor's measurement data and data from an external data storage device, and generate power management data based on the analysis of the sensor's measurement data and the data from the external data storage device; The power management data is used to select a power-saving mode from multiple available power-saving modes of the sensor's wireless module and to control the measurement interval of the sensor. If the wireless module of the sensor (100) does not need to perform data communication for the expected duration of the first time interval, the extended discontinuous reception mode or the power saving mode is selected as the power saving mode. If the expected duration for which the wireless module of the sensor (100) does not need to perform data communication continues for a second time interval longer than the first time interval, the wireless module is disabled as a power-saving mode; and The control unit is configured to reduce or increase the frequency of future measurement intervals within a specific time interval based on the analysis of data available to the sensor, and when analyzing the data available to the sensor and when selecting the power-saving mode from the plurality of available power-saving modes, to consider the energy required to run the power-saving mode, to consider the maximum permissible duration in the power-saving mode before communication must be resumed, and / or to consider the energy required for re-registration or re-dial-in in the communication network.

10. A computer-readable medium storing program elements that, when executed on a control unit (101) or computing unit (200) of a sensor (100), instruct the control unit or computing unit to perform the method according to claim 9.

11. Use of a computing unit (200) in the measurement system according to claim 8, the computing unit being used to store the power management data and transmit the stored power management data to a new sensor (300) of the measurement system.

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