REMOTE MONITORING OF LOAD OF MOVABLE CARRIER

Abstract

A remote monitoring device is provided for monitoring a movable carrier when placed substantially stationary at a delivery location. The movable carrier is adapted for holding a plurality of physical items. The device comprises a wireless communication module, a motion sensor for transducing, into a signal, motion and/or vibrations of the movable carrier caused by exogenous factors in the external environment of the movable carrier, and a processor for determining a characteristic of a signal, and for transmitting the characteristic to a receiver. The signal characteristic includes an estimate of the number or mass of the physical items held by the movable carrier, and/or the signal characteristic provides sufficient information to the receiver such that the receiver can estimate the number or mass of physical items held by the movable carrier. Concepts of the remote monitoring device can be extended to a movable carrier, a system and a method.

Claims

1.-20. (canceled)

21. A remote monitoring device for monitoring a movable carrier when placed substantially stationary at a delivery location, said movable carrier being adapted for holding a plurality of physical items, said device comprising: a wireless communication module, a motion sensor for transducing, into a signal, motion and/or vibrations of the movable carrier caused by exogenous factors in the external environment of the movable carrier, and a processor for determining at least one characteristic of said signal, and for transmitting the at least one characteristic to a receiver using said wireless communication module, wherein said at least one characteristic of the signal comprises an estimate of a measure of the number or mass of the plurality of physical items held by the movable carrier, and/or said at least one characteristic provides sufficient information to said receiver such as to enable the estimation of said measure of the number or mass of the plurality of physical items held by the movable carrier.

22. The device of claim 21, wherein said processor is adapted for determining a spectrum of said signal and for determining said at least one characteristic based on said spectrum.

23. The device of claim 22, wherein said processor is adapted for determining a plurality of spectra corresponding to the signal as acquired at different points in time, and for determining the at least one characteristic based on the plurality of spectra.

24. The device of claim 23, wherein said processor is adapted for calculating an average, a variation and/or a trend over time of the plurality of spectra.

25. The device of claim 21, wherein said at least one characteristic is indicative of said number or mass of the plurality of physical items.

26. The device of claim 21, wherein said processor is adapted for disabling said transmission of said at least one characteristic when a quality metric of said signal is below a predetermined threshold, and for enabling said transmission otherwise.

27. The device of claim 26, in which said quality metric comprises a signal to noise ratio of the signal and/or a power of the signal.

28. The device of claim 21, wherein said processor is adapted for detecting, in said signal, a manipulation signature due to a vibration caused by a loading or unloading of at least one of said physical items, and for determining said at least one characteristic when, or a predetermined time after, said manipulation signature is detected.

29. The device of claim 21, wherein said processor is adapted for acquiring a reference measurement of said signal when said carrier is placed at said delivery location and is holding a predetermined number or a predetermined mass of the physical items.

30. The device of claim 29, wherein said processor is adapted for comparing said at least one reference measurement of said signal, or the at least one characteristic calculated on the basis of the at least one reference measurement, to the signal acquired when said carrier is placed at said delivery location and is holding an unknown number or an unknown mass of the physical items, or to the at least one characteristic calculated on the basis thereof.

31. The device of claim 30, wherein said processor is adapted for said comparing by calculating a correlation.

32. The device of claim 21, comprising a further communication module for transmitting stored information using a high-bandwidth connection when in close proximity to a receiver.

33. The device of claim 21, comprising a position sensor for determining a position of the movable carrier.

34. A movable carrier comprising a device according to claim 21.

35. The movable carrier of claim 34, wherein said movable carrier is a transportable support structure specifically tailored for carrying a specific type of items.

36. A system comprising a plurality of devices according to claim 21, a receiver for receiving the at least one characteristic when transmitted by any of the plurality of devices, and a server, said server being operably connected to the receiver, being adapted for storing and/or processing the at least one characteristic and being adapted for outputting an indication of the measure of the number or mass of the plurality of physical items estimated based on the at least one characteristic received.

37. A method for remotely monitoring a movable carrier when placed substantially stationary at a delivery location, said movable carrier being adapted for holding a plurality of physical items, said method comprising: transducing motion and/or vibrations of the movable carrier caused by exogenous factors in the external environment of the movable carrier into a signal using a motion sensor, determining at least one characteristic of the signal using a processor at the delivery location, transmitting the at least one characteristic to a receiver using a wireless communication module, receiving the at least one characteristic using the receiver at a server location remote from the delivery location, wherein said at least one characteristic of the signal comprises an estimate of a measure of the number or mass of the plurality of physical items held by the movable carrier, and/or said at least one characteristic provides sufficient information to said receiver such as to enable the estimation of said measure of the number or mass of the plurality of physical items held by the movable carrier.

38. The method of claim 37, wherein said at least one characteristic determined at and transmitted from the delivery location is said estimate of the measure of the number or mass of the plurality of physical items held by the movable carrier.

39. The method of claim 37, comprising calculating, using a further processor at the server location, the estimate of the measure of the number or mass of the plurality of physical items held by the movable carrier using the received at least one characteristic.

40. The method of claim 39, in which said at least one characteristic comprises at least one of: a spectrum of said signal, a plurality of spectra of said signal as acquired at different points in time, and/or at least one salient feature of said signal, of said spectrum and/or of said plurality of spectra.

Description

SHORT DESCRIPTION OF THE DRAWINGS

[0041] FIG. 1 shows a remote monitoring device in accordance with embodiments of the present invention.

[0042] FIG. 2 shows a movable carrier in accordance with embodiments of the present invention and a system in accordance with embodiments of the present invention.

[0043] FIG. 3 shows a vibration signal that relates to an example for illustrating embodiments of the present invention.

[0044] FIG. 4 shows a vibration spectrum that relates to an example for illustrating embodiments of the present invention.

[0045] The drawings are schematic and not limiting. Elements in the drawings are not necessarily depicted in realistic proportions or scale. The present invention is not limited to the possible specific embodiments in accordance with the present invention as depicted in the drawings.

DETAILED DESCRIPTION OF EMBODIMENTS

[0046] Notwithstanding the exemplary embodiments described hereinbelow, is the present invention only limited by the attached claims. The attached claims are hereby explicitly incorporated in this detailed description, in which each claim, and each combination of claims as allowed for by the dependency structure defined by the claims, forms a separate embodiment of the present invention.

[0047] The word “comprise,” as used in the claims, is not limited to the features, elements or steps as described thereafter, and does not exclude additional features, elements or steps. This therefore specifies the presence of the mentioned features without excluding a further presence or addition of one or more features.

[0048] In this detailed description, various specific details are presented. Embodiments of the present invention can be carried out without these specific details. Furthermore, well-known features, elements and/or steps are not necessarily described in detail for the sake of clarity and conciseness of the present disclosure.

[0049] In a first aspect, the present invention relates to a remote monitoring device. FIG. 1 shows an exemplary remote monitoring device 1 in accordance with embodiments of the present invention.

[0050] In a second aspect, the present invention relates to a movable carrier in or on which a device in accordance with embodiments of the first aspect of the present invention is installed. FIG. 2 shows an exemplary movable carrier 10 in accordance with embodiments of the present invention.

[0051] The movable carrier may be a trailer, a container, a box, a platform, or any structure adapted for carrying a plurality of physical items therein or thereon and adapted for transportation of the physical items. The movable carrier may comprise a transportable support structure, such as a pallet, a skid or other support base. The transportable support structure may comprise a crate, a cage, sides, and/or a support. The transportable support structure may be specifically tailored to carry a specific type of items. The transportable structure may be (or may not be) stackable. The transportable structure may be adapted for transporting the items without the need to load and unload, for the purpose of transportation, the items being carried. For example, the transportable structure may comprise a support frame. The support frame may be shaped like an upright ‘A’. In this example, the items may be planar items, e.g. panes, which are positioned on the outside of the A-shaped support frame such as to lean inward. For example, the planar items may be conveniently strapped to the support frame to ready the items on the frame for transport.

[0052] The carrier may be adapted for self-powered transport (e.g. a truck or van), may be adapted for facilitating easy movement by wheels or sledge elements when pushed or pulled by an external force (e.g. a trailer or cart), or may be adapted for facilitating movement by being loadable onto an external transporter (e.g. a container or a transportable support structure). The physical items may, for example, comprise building elements, for being used at a delivery location, e.g. a building site. In exemplary embodiments, the physical items may comprise planar items, e.g. panes. The planar items may consist of or comprise a non-crystalline, amorphous solid, e.g. which may be transparent or translucent.

[0053] In a third aspect, the present invention also relates to a system comprising a plurality of devices in accordance with embodiments of the first aspect of the present invention, e.g. installed in or on a plurality of movable carriers, a receiver for receiving the at least one characteristic when transmitted by any of the plurality of devices, and a server. The server is operably connected to the receiver, adapted for storing and/or processing the at least one characteristic received and adapted for outputting an indication of the measure of the number or mass of the plurality of physical items estimated based on the at least one characteristic received.

[0054] The remote monitoring device 1 in accordance with embodiments of the present invention is adapted for monitoring a movable carrier 10, when or while this movable carrier 10 is placed substantially stationary at a delivery location 11, e.g. as illustrated in FIG. 2. The movable carrier 10 is adapted for holding a plurality of physical items 12, e.g. structured products. Particularly, the remote monitoring device 1 is adapted for being installed in or on the movable carrier 10. The device 1 may be integrated in or on the carrier 10, firmly fixed to the carrier 10 or removably attached to the carrier 10. Particularly, the device may be installed such as to allow a good mechanical transmission of vibrations from the carrier to the device.

[0055] The device 1 comprises a wireless communication module 2. For example, the wireless communication module may comprise a global system for mobile communication (GSM) module. The wireless communication module may comprise a second, third, fourth, fifth or subsequent generation of wireless mobile telecommunications (2G, 3G, 4G, 5G, xG) module. The wireless communication module may be adapted for Internet of Things (IoT) ubiquitous communications. Preferably, the wireless communications module is adapted for low-power, low-bandwidth and long-distance (e.g. via a regional or global wireless telecommunications network) transmission of data.

[0056] The device 1 comprises a motion sensor 3, e.g. a vibration sensor, for transducing, in operation of the device, the effects of motion and/or vibrations of the movable carrier 10, due to exogeneous factors in the environment, into a signal S, e.g. when the device is installed in or on the movable carrier. These movements and/or vibrations of the movable carrier 10 are caused by stochastic motion of the movable carrier in its external environment, e.g. due to weather effects, traffic, other external sources of environmental vibrations and/or human manipulation of the items in or on the carrier. ‘Exogeneous’ refers to the motion and/or vibrations being caused, i.e. driven, by an external source of motion and/or vibrations that is not driven, not controlled and not deterministically predictable by the operation of the device 1 nor by the carrier itself, the device itself or the plurality of physical items on the carrier.

[0057] The vibration sensor 3 may comprise an inertial sensor. The vibration sensor may comprise an accelerometer.

[0058] For example, FIG. 3 shows an exemplary signal S in the form of a single directional component of acceleration of the device, and the carrier it is attached to. The signal is acquired as function of time, here represented by a chronological and dimensionless index. It shall be understood that signal may comprise a different component and/or multiple components, e.g. one or more of cartesian X, Y and Z components of linear velocity and/or of linear acceleration and/or angular components of rotational velocity and/or rotational acceleration.

[0059] The device 1 also comprises a processor 4 for determining at least one characteristic of the signal S and for transmitting the at least one characteristic to a receiver 20 using said wireless communication module 2 such as to enable a measure of the number and/or mass of the plurality of physical items held by the movable carrier to be transmitted (e.g. in the form of the at least one characteristic) or to be estimated (e.g. based on the transmitted at least one characteristic). The at least one characteristic may be indicative of the number or mass of the plurality of physical items, or may comprise or consist of data that enables the receiver 20 to estimate the measure of the number and/or mass of the plurality of physical items.

[0060] The processor may comprise a central processing unit, a field-programmable gate array, an application specific integrated circuit or a combination thereof.

[0061] The processor may be adapted for disabling (e.g. preventing, not executing) the transmission of the at least one characteristic (and possibly not even calculating the at least one characteristic) when a quality metric of the signal S is below a predetermined threshold, and for enabling (e.g. allowing, executing) the transmission and/or the calculation otherwise. The quality metric may consist of or comprise a signal to noise ratio (SNR) of the signal S and/or a power of the signal, e.g. an integrated value of a spectrum of the signal. The quality metric is not necessarily limited to these examples. For example, the quality metric may be any value that is indicative of an overall strength of the vibrations transduced into the signal, and may optionally comprise other factors or terms, e.g. indicative of a noisiness of the signal. A suitable predetermined threshold can be determined empirically by simple experimentation, or mere trial and error, without requiring any inventive effort of the person skilled in the art. Thus, advantageously, computing resources, power and communication bandwidth can be reserved for handling signals that are of sufficient quality to enable a good characterization of the load on the carrier.

[0062] The processor 4 may also be adapted for detecting, in the signal S, a manipulation signature indicative of a vibration caused by a loading or unloading of at least one of said physical items 12. This signature may be a signal strength that is higher than a predetermined threshold, or may be a more complicated signature, such as a specific spectral fingerprint. The processor may be adapted for processing the at least one characteristic when, or a predetermined time after, the manipulation signature is detected. For example, a positive detection of the manipulation signature may trigger an update action to monitor exogenous vibrations by means of the signal in a time frame after the manipulation signature was detected, such as to provide a new estimate of the load of the carrier. It is an advantage that computing, power and bandwidth resources can be conserved until a change in load of the carrier is assumed due to the detection of the manipulation signature. For example, the device may remain in a dormant or low-power mode until the manipulation signature, which preferably requires few(er) resources to detect, is detected.

[0063] The processor 4 may be adapted for determining a spectrum of the signal S and for determining the at least one characteristic based on the spectrum. However, embodiments are not necessarily limited to computing a Fourier spectrum, e.g. by a Fast Fourier Transform or equivalent operation. Other examples of useful signal transformations that may be implemented include cepstral transformations, Laplace transformations, Z transformations, slant (or slantlet) transformations and wavelet transformations. Generally, any transformation decomposing the signal into different time scales and time offsets, e.g. Fourier frequency and phase or coefficients of a multiresolution wavelet decomposition, may be suitable. Where reference is made to the spectrum of the signal S, it is assumed that this could equally apply to the result of a non-Fourier transformation that results in an encoding of frequency or scale on one hand and time offset or phase on the other hand. It is also to be noted that the time offset or phase components may be relevant for some embodiments of the present invention, but not necessarily relevant in other embodiments of the present invention. For example, a particularly simple implementation may merely process the magnitude of the complex Fourier components, e.g. ignoring phase, while a more complicated implementation may take both frequency or scale and time offset or phase into account. Furthermore, the time offset or phase information may be inherently obtained by the applied transformation, e.g. a wavelet transform or Fourier transform, or may be added by monitoring the signal over time and determining the spectrum at different points in time.

[0064] To summarize, the ‘spectrum’ may relate to a Fourier spectrum, or any other data construct that decomposes the signal into frequency-like or scale-like components. The ‘spectrum’ may also comprise time-like information, such as phase or time offset information. The time-like information may also be obtained by repeatedly determining the spectrum of the signal acquired at different points in time and aggregating the frequency-like or scale-like components for these points in time. For example, the processor 4 may be adapted for determining a plurality of spectra corresponding to acquisitions of the signal S at different points in time. The processor may be adapted for determining the at least one characteristic based on the plurality of spectra.

[0065] The processor 4 may be adapted for calculating an average, a variation and/or a trend over time, such as a first, second or higher temporal derivative, of the spectra.

[0066] FIG. 4 shows Fourier spectra of four such signals S acquired at different time intervals (e.g. disjoint intervals in time) for the same system, e.g. the same device installed in or on the same carrier loaded with the same load. As can be seen, due to the random nature of the exogenous vibrations, these different signals S may differ in overall amplitude and/or level of noise. However, specific frequencies 41 or frequency bands may be particularly pronounced in each of the signals S. Such specific frequencies may correspond to eigenfrequencies of the system, which may be influenced by the carrier, the device, the physical items loaded in or on the carrier and the contact of the carrier to its surroundings, e.g. the surface on which it rests. Therefore, the at least one characteristic from which the load in or on the carrier can be estimated may comprise the spectrum of the signal, a combination of multiple spectra obtained at different times, e.g. an average, spread or a temporal derivative, salient features of the spectrum (e.g. detected frequency peaks) and/or salient features of the combination of multiple spectra obtained at different times. Furthermore, a quality metric, as discussed hereinabove, may be used to reject spectra of poor quality, e.g. in which the bandwidth of the spectral peaks is wide relative to their peak intensity.

[0067] The processor 4 may be adapted for acquiring a reference measurement of the signal at a time when the carrier is placed at the delivery location 11 and is holding a predetermined, i.e. a known, number or a predetermined, i.e. a known, mass of the physical items 12. Thus, this reference measurement (or a plurality of such reference measurements) can be used in order to accurately estimate an a-priori unknown number or mass of the physical items at a later time. Furthermore, by acquiring the reference measurement at the delivery location, characteristics of the local environment, such as the type of surface on which the carrier is placed, can be taken into account. For example, the type of surface may influence the spectral characteristics as function of load.

[0068] The predetermined number or mass of the physical items may, for example, correspond to a full load of the carrier or to an empty load of the carrier. A plurality of reference measurements may be acquired, e.g. for both a full and an empty load of the carrier. Furthermore, alternatively or additionally, one or more reference measurements may be acquired when the carrier is placed at a different location than the delivery location, such as in a controlled testing environment. For example, reference measurements for one or more predetermined loads of the carrier can be acquired on a number of different types of surface and/or different environmental conditions. In an exemplary embodiment, a reference measurement performed at the delivery location may be compared to reference measurements performed in the controlled testing environment to determine a suitable processing scenario and/or a suitable algorithm and/or suitable algorithmic parameters.

[0069] The reference measurement may be used to calculate a reference spectrum, and/or a reference value of the at least one characteristic. The reference measurement, reference spectrum and/or reference value of the at least one characteristic may be stored for later use.

[0070] The processor 4 may be adapted for comparing the reference measurement of the signal (or the spectrum or reference value calculated on the basis of the reference measurement) to the signal S acquired when the carrier is placed at the delivery location 11 and is holding an unknown number or an unknown mass of the physical items 12 (or to the spectrum or the at least one characteristic calculated on the basis of that signal). The processor 4 may be adapted for comparing a plurality of such reference measurements (or spectra or reference values) corresponding to different known loads and/or different known environmental conditions, e.g. types of supporting surfaces, to the signal S (or its spectrum or its corresponding characteristic). Such comparison or comparisons may comprise calculating a correlation, or a different measure of similarity (or, equivalently, a measure of dissimilarity). Examples of such measures of similarity or dissimilarity may include correlation, covariance, mutual information, Kullback-Leibler divergence measures, distance metrics, such as the sum of squared difference, and/or scaled scalar products.

[0071] However, embodiments of the present invention are not necessarily limited thereto. For example, a comparison between a plurality of reference measurements, spectra or reference values to a signal, spectrum or characteristic for which the corresponding physical load is to be determined may comprise a classification algorithm or regression algorithm, in which respectively the best matching reference to the entity to be tested is determined or a corresponding load is interpolated, extrapolated or inferred based on the references and their corresponding known loads. Such classification or regression algorithms may comprise machine learning algorithms, such as neural networks and related methods, deep learning algorithms, Bayesian networks, support vector machines, support tensor machines, Markov chains and/or random tree or forest methods.

[0072] Following table shows an example of pairwise correlations between accelerometer spectra obtained for an ‘A’-shaped support structure loaded with panes of a transparent non-crystalline amorphous solid, e.g. comprising a silicon dioxide material, in a fully loaded condition (a, b, c), a half-empty condition (d, e) and an empty condition (f, g, h), under random exogenous vibrational excitations (e.g. uncontrolled, e.g. due to random environmental factors). As will be seen, the different spectra obtained for the same condition are highly correlated, while being substantially less correlated to the other conditions. This shows that even a simple implementation based on comparison to reference spectra for predetermined loading conditions by means of, for example, a correlation, could be sufficient to estimate the load on the carrier at least sufficiently to determine when the carrier will be substantially empty.

TABLE-US-00001 a b c d e f g h a 1.00 0.91 0.92 0.58 0.57 0.11 0.09 0.11 b 0.91 1.00 0.93 0.62 0.62 0.15 0.15 0.17 c 0.92 0.93 1.00 0.64 0.65 0.18 0.15 0.17 d 0.58 0.62 0.64 1.00 0.97 0.25 0.30 0.32 e 0.57 0.62 0.65 0.97 1.00 0.26 0.33 0.35 f 0.11 0.15 0.18 0.25 0.26 1.00 0.93 0.95 g 0.09 0.15 0.15 0.30 0.33 0.93 1.00 0.99 h 0.11 0.17 0.17 0.32 0.35 0.95 0.99 1.00

[0073] The device 1 may also comprise a further communication module 5 for transmitting stored information using a high-bandwidth connection when in close proximity to a receiver. For example, the stored information may comprise the signal S as acquired over a long period of time and/or the corresponding spectra. It is an advantage that such information may be stored and delivered to a server for detailed analysis and adjustment of algorithms to estimate the load of the same carrier or another similar carrier in the future more accurately. Power and bandwidth of the wireless communication module 2 can thus be conserved when the device is in or on the carrier at the delivery location, while useful information can be recovered using the further communication module 5 when the carrier and device are returned to a service location. The further communication module may, for example, comprise a wired communication information, e.g. an ethernet connection or bus interface, such as an UART, CAN or LIN bus interface. The further communication module may comprise a further wireless communication module, such as a WiFi module or a Bluetooth module.

[0074] The device 1 may also comprise a position sensor 6 for determining a position of the movable carrier, when the device 1 is installed therein or thereon. For example, the position sensor 6 may comprise a global positioning system (GPS) receiver. The processor 4 may be adapted for transmitting a position determined by the position sensor 6 to the receiver via the wireless communication module 2. The processor may be adapted for detecting a substantial movement of the movable carrier based on the position determined by the position sensor 6. For example, the device may suspend operation of the motion sensor until the position determined by the position sensor remains substantially constant. For example, the device may initiate a calibration after such detected relocation of the carrier, e.g. to account for different vibrational properties of the carrier when placed on a different type of surface and/or in a different type of external environment.

[0075] In a device 1 in accordance with embodiments of the first aspect of the present invention, the processor 4 may be adapted for estimating the number or mass of the plurality of physical items (generally referred to as estimating ‘the load’) based on the signal S. This may comprise calculating a spectrum, or a plurality of spectra over time, of the signal S. This may comprise detecting salient features of the signal, the spectrum or a time series of spectra. This may comprise comparing the signal, the spectrum, the spectra and/or the salient features to stored information, e.g. in a storage memory of the device. The stored information may correspond to the reference measurement(s) or information derived therefrom. The stored information may correspond to parameters of an algorithm, e.g. a trained algorithm by machine learning techniques. The stored information may correspond to such parameters selected from a plurality of sets of such parameters, in which the selection is based on the reference measurement(s). The at least one characteristic may comprise the estimate of the load, which may be transmitted to the receiver 21. Thus, the measure of the number or mass of the plurality of physical items held by the movable carrier may be estimated by the device 1 and may be made available to the receiver 21.

[0076] Alternatively, in a system in accordance with embodiments of the third aspect of the present invention, the at least one characteristic may comprise the signal S, the spectrum thereof, a plurality of spectra over time determined from the signal S, salient features of the signal S, salient features of the spectrum and/or salient features of the plurality of spectra over time, and/or any information directly derived from any of the aforementioned or from any combination of the aforementioned. The server 20 may be adapted for calculating a spectrum from the received signal, or calculating a plurality of spectra over time of the received signals. The sever 20 may be adapted for detecting salient features of the signal, the spectrum or the time series of spectra. The server 20 may be adapted for comparing the signal, the spectrum, the spectra and/or the salient features to stored information. The stored information may correspond to the reference measurement(s) or information derived therefrom, e.g. which may be previously transmitted by the device 1 to the receiver 21 and accordingly stored by the server 20. The stored information may correspond to parameters of an algorithm, e.g. a trained algorithm by machine learning techniques. The stored information may correspond to such parameters selected from a plurality of sets of such parameters, in which the selection is based on the reference measurement(s). The server may be adapted for estimating of the load based on the at least one characteristic received from the device 1. Thus, the measure of the number or mass of the plurality of physical items held by the movable carrier may be estimated by the server 20 based on information received from the device 1.

[0077] In a fourth aspect, the present invention also relates to a method for remotely monitoring a movable carrier when placed substantially stationary at a delivery location. The movable carrier is adapted for holding a plurality of physical items. The method comprises transducing motion and/or vibrations of the movable carrier caused by stochastic motion of the movable carrier induced by external vibrations in its environment into a signal using a motion sensor, e.g. a vibration sensor. The method further comprises determining at least one characteristic of the signal using a processor at the delivery location, and transmitting the at least one characteristic to a receiver using a wireless communication module. The method comprises receiving the at least one characteristic using the receiver at a server location remote from the delivery location such as to obtain an estimate of a measure of the number or mass of the plurality of physical items held by the movable carrier.

[0078] In a method in accordance with embodiments of the present invention, the at least one characteristic determined at and transmitted from the delivery location may be the estimate of the measure of the number or mass of the plurality of physical items held by the movable carrier.

[0079] A method in accordance with embodiments of the present invention may comprise calculating, using a further processor, at the server location, the estimate of the measure of the number or mass of the plurality of physical items held by the movable carrier using the received at least one characteristic.

[0080] The at least one characteristic may comprise a spectrum of the signal. The at least one characteristic may comprise a plurality of spectra of the signal as acquired at different points in time. The at least one characteristic may comprise at least one salient feature of signal, of the spectrum and/or of the plurality of spectra, such as one or more peak frequencies or spectral locations, one or more peak bandwidths, one or more time averages, one or more time variations, and/or one or more trends over time of spectral components.

[0081] The method may comprise, using the processor, determining a spectrum of the signal and determining the at least one characteristic based on the spectrum. The method may comprise determining a plurality of spectra corresponding to the signal as acquired at different points in time, and determining the at least one characteristic based on the plurality of spectra, using the processor. Determining the at least one characteristic based on the plurality of spectra may comprise calculating an average, a variation and/or a trend over time of the plurality of spectra.

[0082] The step of determining and transmitting the at least one characteristic may be performed conditionally, in a method in accordance with embodiments of the present invention, if and only if a quality metric of the signal is above a predetermined threshold. The quality metric may comprise a signal to noise ratio of the signal and/or a power of the signal.

[0083] The method may comprise detecting, based on the signal, a signature, referred to as manipulation signature, of a vibration caused by a loading or unloading of at least one of the physical items onto or off the carrier. The method may comprise determining the at least one characteristic when, or at a predetermined time after, the manipulation signature is detected.

[0084] The method may comprise acquiring at least one reference measurement of the signal when the carrier is placed at the delivery location and is holding a predetermined number or a predetermined mass of the physical items.

[0085] The method may comprise acquiring at least one reference measurement of the signal when the carrier is placed in a testing environment characterized by predetermined environmental characteristics, such as a predetermined type of ground surface, and is holding a predetermined number or a predetermined mass of the physical items.

[0086] The method may comprise comparing the at least one reference measurement of the signal, or at least one characteristic calculated on the basis of the at least one reference measurement, to the signal acquired when the carrier is placed at the delivery location and is holding an unknown number or an unknown mass of the physical items, or to the at least one characteristic calculated on the basis thereof. This step of comparing may comprise calculating a correlation.

[0087] The method may also comprise determining a position of the delivery location using a position sensor, and transmitting the position to the receiver.

[0088] Other features, or details of the features described hereinabove, of a method in accordance with embodiments of the present invention shall be clear in view of the description provided hereinabove relating to a device, carrier and/or system in accordance with embodiments of the present invention.