Commodity monitoring systems, cable assemblies, cable sensor nodes, and related methods and systems

Abstract

A method of monitoring a commodity within a container includes receiving first temperature data from a hub sensor of a cable hub, receiving second temperature data from a sensor node of a cable coupled to the cable hub, based at least partially on the first temperature data, determining a first entropy value associated with the first temperature data, based at least partially on the second temperature data, determining a second entropy value associated with the second temperature data, comparing the first entropy value with the second entropy value; and based at least partially on the comparison of the first entropy value to the second entropy value, determining whether the sensor node of the cable is in the commodity within the container or out of the commodity within the container.

Description

COMMODITY MONITORING SYSTEMS, CABLE ASSEMBLIES, CABLE SENSOR NODES, AND RELATED METHODS AND SYSTEMSCROSS-REFERENCE TO RELATED APPLICATIONS

[0001] This application claims the benefit of the filing date of United States Provisional Patent Application Serial No. 63 / 581,330, filed September 8, 2023, the disclosure of which is hereby incorporated herein in its entirety by this reference.FIELD

[0002] Embodiments generally relate to grain monitoring. In particular, embodiments relate to sensor nodes secured to cables used in the monitoring of stored commodities (e.g., grain).BACKGROUND

[0003] In the monitoring of commodities within storage bins, it is important to monitor certain parameters to keep the stored commodities cool and dry. Based on the monitored parameters, determinations that the stored commodities need aeration, heating, and / or by churning may be made. In cable-based monitoring, parameters are typically monitored via sensor nodes suspended by cables. Furthermore, knowing the moisture content and temperature of the commodities is important in determining that the stored commodities need aeration, heating, and / or by churning.BRIEF SUMMARY

[0004] Embodiments include a method of monitoring a commodity within a container. The method may include receiving first temperature data from a hub sensor of a cable hub, receiving second temperature data from a sensor node of a cable coupled to the cable hub, based at least partially on the first temperature data, determining a first entropy value associated with the first temperature data, based at least partially on the second temperature data, determining a second entropy value associated with the second temperature data, comparing the first entropy value with the second entropy value, and based at least partially on the comparison of the first entropy value to the second entropyvalue, determining whether the sensor node of the cable is in a commodity within the container or out of the commodity within the container.

[0005] Determining the first entropy value associated with the first temperature data may include defining the first temperature data as first time-series data, and determining and generating a first characteristic matrix representing the first time-series data.

[0006] The method may further include, responsive to a determination as to whether the sensor node is in commodity or out of commodity, adjusting operation of one or more commodity treatment devices of the container.

[0007] The first temperature data may include first temperature measurements captured over a period of time, and the second temperature data may include second temperature measurements captured over the period of time.

[0008] The first temperature data includes a first temperature profile over a period time, and the second temperature data may include a second temperature profile over the period of time.

[0009] The method may also include receiving first relative humidity data from the hub sensor of the cable hub, receiving second relative humidity data from the sensor node of the cable coupled to the cable hub, and determining the first and second entropy values based at least partially on the received first and second relative humidity data.

[0010] Determining the first entropy value associated with the first temperature data may further include determining singular values of the first characteristic matrix, normalizing the determined singular values, and determining the first entropy value based at least partially on the normalized, determined singular values.

[0011] Determining the first entropy value may include determining a first Shannon Entropy value.

[0012] Determining the first Shannon Entropy value may include determining the first Shannon Entropy value via the following:

[0014] The method may also include categorizing the first entropy value as a high entropy value.

[0015] The method may also include categorizing the second entropy value as either a high entropy value or a low entropy value.

[0016] The method may also include, responsive categorizing the second entropy value as a high entropy value, determining that the sensor node is out of commodity.

[0017] The method may also include, responsive categorizing the second entropy value as a low entropy value, determining that the sensor node is in commodity.

[0018] The method may also include, responsive to determining that the sensor node is out of commodity receiving third temperature data from a lower sensor node of the cable, based at least partially on the third temperature data, determining a third entropy value associated with the third temperature data, comparing the first entropy value with the third entropy value, and based at least partially on the comparison of the first entropy value to the second entropy value, determining whether the lower sensor node of the cable is in the commodity within the container or out of the commodity within the container.

[0019] The method may also include where adjusting operation of the one or more commodity treatment devices of the container includes at least one of turning on or off fans, blowers, or heaters, increasing or decreasing air flow through the commodity via fans, blowers, or heaters, turning on or off ch urners, or opening or closing vents of the container.

[0020] Some embodiments include a system including a container and a cable assembly disposed within the container and including at least one cable hub having a hub sensor disposed therein and at least one cable coupled to and hanging from the at least one cable hub, the at least one cable having a plurality of sensor nodes operably coupled to the at least one cable. The system also includes a commodity monitoring system in communication with the cable assembly and including at least one processor and at least one non-transitory computer-readable storage medium storing instructions thereon that, when executed by the at least one processor, cause the commodity monitoring system to determine a first entropy value associated with the hub sensor based at least partially on at least one of first temperature data or first relative humidity data received from the hubsensor of the at least one cable hub, determine a second entropy value associated with a sensor node of the plurality of sensor nodes coupled to the at least one cable based at least partially on at least one of second temperature data or first relative humidity received from the sensor node, compare the first entropy value with the second entropy value, and based at least partially on the comparison of the first entropy value to the second entropy value, determining whether the sensor node of the plurality of sensor nodes coupled to the at least one cable is in the commodity within the container or out of the commodity within the container.

[0021] The system may also include instructions that, when executed by the at least one processor, cause the commodity monitoring system to categorize the first entropy value as a high entropy value, and utilize a clustering algorithm to determine whether to categorize the second entropy value as a high entropy value or a low entropy value.

[0022] The system may also include instructions that, when executed by the at least one processor, cause the commodity monitoring system to responsive categorizing the second entropy value as a high entropy value, determining that the sensor node is out of commodity.

[0023] The system may also include instructions that, when executed by the at least one processor, cause the commodity monitoring system to responsive categorizing the second entropy value as a low entropy value, determining that the sensor node is in commodity.

[0024] One or more embodiments include a method of monitoring a commodity within a container. The method may include, based on a comparison of an entropy value associated with a sensor external to a container and additional entropy values associated with sensor nodes of a cable within the container, determining which sensor nodes of the cable are in commodity and which sensor nodes of the cable are out of commodity.

[0025] Other technical features may be readily apparent to one skilled in the art from the following figures, descriptions, and claims.

[0026] Within the scope of this application, it should be understood that the various aspects, embodiments, examples, fand alternatives set out herein, and individual featuresthereof may be taken independently or in any possible and compatible combination. Where features are described with reference to a single aspect or embodiment, it should be understood that such features are applicable to all aspects and embodiments unless otherwise stated or where such features are incompatible.BRIEF DESCRIPTION OF THE DRAWINGS

[0027] While the specification concludes with claims particularly pointing out and distinctly claiming what are regarded as embodiments of the present disclosure, various features and advantages may be more readily ascertained from the following description of example embodiments when read in conjunction with the accompanying drawings, in which:

[0028] FIG. 1 shows a schematic representation of a commodity monitoring system having a cable assembly and sensor nodes according to one or more embodiments of the present disclosure;

[0029] FIG. 2 shows a flowchart of a method of monitoring a commodity within a container according to one or more embodiments of the disclosure; and

[0030] FIG. 3 is a schematic view of a computer device according to embodiments of the disclosure.DETAILED DESCRIPTION

[0031] Illustrations presented herein are not meant to be actual views of any particular storage container, cable assembly, cable, sensor node, component, or system, but are merely idealized representations that are employed to describe embodiments of the disclosure. Additionally, elements common between figures may retain the same numerical designation for convenience and clarity.

[0032] The following description provides specific details of embodiments. However, a person of ordinary skill in the art will understand that the embodiments of the disclosure may be practiced without employing many such specific details. Indeed, the embodiments of the disclosure may be practiced in conjunction with conventional techniques employed in the industry. In addition, the description provided below does not include all the elementsthat form a complete structure or assembly. Only those process acts and structures necessary to understand the embodiments of the disclosure are described in detail below. Additional conventional acts and structures may be used. The drawings accompanying the application are for illustrative purposes only, and are thus not drawn to scale.

[0033] As used herein, the terms "comprising," "including," "containing," "characterized by," and grammatical equivalents thereof are inclusive or open-ended terms that do not exclude additional, unrecited elements or method steps, but also include the more restrictive terms "consisting of" and "consisting essentially of" and grammatical equivalents thereof.

[0034] As used herein, the singular forms following "a," "an," and "the" are intended to include the plural forms as well, unless the context clearly indicates otherwise.

[0035] As used herein, the term "may" with respect to a material, structure, feature, or method act indicates that such is contemplated for use in implementation of an embodiment of the disclosure, and such term is used in preference to the more restrictive term "is" so as to avoid any implication that other compatible materials, structures, features, and methods usable in combination therewith should or must be excluded.

[0036] As used herein, the term "configured" refers to a size, shape, material composition, and arrangement of one or more of at least one structure and at least one apparatus facilitating operation of one or more of the structure and the apparatus in a predetermined way.

[0037] As used herein, any relational term, such as "first," "second," "top," "bottom," "upper," "lower," "above," "beneath," "side," "outer," "inner," etc., is used for clarity and convenience in understanding the disclosure and accompanying drawings, and does not connote or depend on any specific preference or order, except where the context clearly indicates otherwise. For example, these terms may refer to an orientation of elements of a sensor node, a cable, and / or a cable assembly as illustrated in the drawings. Additionally, these terms may refer to an orientation of elements of a sensor node, a cable, and / or a cable assembly when utilized in a conventional manners.

[0038] As used herein, any relational term, such as "first," "second," "top," "bottom," "upper," "lower," "above," "beneath," "side," etc., is used for clarity and convenience in understanding the disclosure and accompanying drawings, and does not connote or depend on any specific preference or order, except where the context clearly indicates otherwise. For example, these terms may refer to an orientation of elements of a cable assembly, cable, and / or sensor node when utilized in a conventional manner. Furthermore, these terms may refer to an orientation of elements of a cable assembly, cable, and / or sensor node when as illustrated in the drawings.

[0039] As used herein, the term "substantially" in reference to a given parameter, property, or condition means and includes to a degree that one skilled in the art would understand that the given parameter, property, or condition is met with a small degree of variance, such as within acceptable manufacturing tolerances. By way of example, depending on the particular parameter, property, or condition that is substantially met, the parameter, property, or condition may be at least 90.0% met, at least 95.0% met, at least 99.0% met, or even at least 99.9% met.

[0040] As used herein, the term "about" used in reference to a given parameter is inclusive of the stated value and has the meaning dictated by the context (e.g., it includes the degree of error associated with measurement of the given parameter, as well as variations resulting from manufacturing tolerances, etc.).

[0041] As used herein, the term "and / or" includes any and all combinations of one or more of the associated listed items.

[0042] Embodiments of the disclosure include a cable assembly for monitoring a commodity (e.g., a grain) within a container (e.g., a storage bin). The cable assembly may include cable hubs from which cables hang and sensor nodes secured to the cables. The cable hubs may include hub sensors. Embodiments further include comparing data acquired from the hub sensors of the cable hubs and data acquired from the sensor nodes of the cables to determine which sensor nodes are within the commodity within the container and which sensor nodes are out of the commodity. Furthermore, based on the determination of which sensor nodes are within the commodity, operation of one or more commoditymanagement devices may be adjusted based on data from the sensor nodes that are within the commodity.

[0043] FIG. 1 shows a schematic diagram of an environment 100 in which a sensor node (e.g., a cable sensor node) and commodity monitoring system may be implemented and operated according to one or more embodiments of the present disclosure. The environment 100 may include a cable assembly 102 having a plurality of cables 104 suspended within a container 106, at least one client device 108, at least one server 122 including the commodity monitoring system 120, and a network 110. The commodity monitoring system 120, the at least one client device 108, and the cable assembly 102 may communicate via the network 110. Although FIG. 1 illustrates a particular arrangement of the at least one client device 108, the at least one server 122, the cable assembly 102, and the network 110, various additional arrangements are possible. For example, the at least one server 122 and, accordingly, the commodity monitoring system 120, can communicate directly with the at least one client device 108, and / or the cable assembly 102, thereby bypassing the network 110.

[0044] The container 106 may include a grain storage bin. Furthermore, while a particular geometry is depicted in FIG. 1, it understood that the container 106 may include one or more containers of other geometries, for the same contents (e.g., grain) or other contents, with a different arrangement and / or quantity of inlet, outlet, and / or side ports.

[0045] The cable assembly 102 may include a plurality of cables 104 coupled to and suspended from one or more top structures of a container 106. In some embodiments, one or more of the plurality of cables 104 may be coupled to a floor of the container 106 via, for instance, a floor anchor. In some embodiments, the plurality of cables 104 may each be operably coupled to and hanging from a respective cable hub 112. Each cable hub 112 may include one or more hub sensors 124 and may be in communication (e.g., via wired and / or wireless communication) with a communications gateway 114, which in turn may be in communication with the network 110, and as a result, the at least one client device 108 and / or the commodity monitoring system 120 of the at least one server 122. The one or more hub sensors 124 may include one or more of humidity sensors, relative humiditysensors, temperature sensors, moisture sensors, and / or carbon dioxide (CO2) sensors. Additionally, the environment 100 may include one or more external sensors that may include one or more of humidity sensors, relative humidity sensors, temperature sensors, moisture sensors, and / or carbon dioxide (CO2) sensors.

[0046] The cable assembly 102 may be utilized to monitor contents (e.g., a commodity) within the container 106. For example, each cable 104 of the cable assembly 102 may include a plurality of sensor nodes 116 coupled (e.g., secured) to the cable 104. The plurality of sensor nodes 116 of each cable 104 may include an uppermost sensor node 126 (i.e., a highest sensor node vertically) and one or more lower sensor nodes 128 (i.e., sensor nodes below the uppermost sensor node 126 on the cable 104). In some embodiments, the plurality of sensor nodes 116 of each cable 104 may be spaced apart from each along a longitudinal length of the given cable 104. As a result, when a commodity (e.g., a grain) is stored within the container 106, the plurality of sensor nodes 116 of each cable 104 may be vertically distributed throughout the commodity.

[0047] The plurality of sensor nodes 116 may include one or more of humidity sensors, relative humidity sensors, temperature sensors, moisture sensors, and / or carbon dioxide (CO2) sensors. Spacing between sensor nodes 116 of the plurality of sensor nodes 116 may be selected based on the type of sensors and / or type of commodity. Additionally, a quantity of cables 104 may be selected based at least partially on one or more of a region (e.g., climate) in which the container 106 is located, a type of commodity stored, a size of the container 106, air flow conditions within the container 106, and the types of sensors of the sensor nodes 116.

[0048] As is described in great detail below, the commodity monitoring system 120 may utilize measurements from the uppermost sensor nodes 126 of the cables 104 and measurements from the lower sensor nodes 128 of the cables 104 to determine statuses of the lower sensor nodes 128 of each cable 104. As used herein, the term "status," when referring to the lower sensor nodes 128 of the cables 104, may refer to whether a given lower sensor node 128 is "in commodity" (e.g., in contact with the commodity (e.g., the contents) within the container 106) or "out of commodity" (e.g., not in contact with thecommodity within the container 106). Furthermore, based at least partially on a determination of which lower sensor nodes 128 of the cable assembly 102 are in commodity or out of commodity, the commodity monitoring system 120 may adjust operation of commodity management devices 118 of the container 106 to affect conditions of the commodity. In some embodiments, the commodity management devices 118 may include one or more of heaters, fans, blowers, churners, vents, etc. Furthermore, based at least partially on a determination of which lower sensor nodes 128 of the cable assembly 102 are in commodity or out of commodity, the commodity monitoring system 120 may determine (e.g., estimate) one or more upper surface profiles of the commodity within the container 106.

[0049] In some embodiments, a user can interface with the at least one client device 108, for example, to communicate with the at least one server 122 and to utilize the commodity monitoring system 120 to monitor contents of the container 106. The user may include one or more operators of the container 106 and / or commodity monitoring system 120. Although FIG. 1 shows a single client device 108, the environment 100 can include any number of client devices 108, in communication with the network 110, the at least one server 122, and / or the cable assembly 102.

[0050] In some embodiments, the client device 108 may include a client application installed thereon. In one or more embodiments, the client application can be associated with the commodity monitoring system 120. For example, the client application may allow the client device 108 to directly or indirectly interface with other elements the commodity monitoring system 120 and the cable assembly 102. The client application also enables a user (e.g., an operator) to initiate measurements via the commodity monitoring system 120 and observe any results of the measurements (e.g., measured humidity, measured temperatures, measured moisture levels, etc.).

[0051] Both the at least one client device 108 and the at least one server 122 (and the commodity monitoring system 120) can represent various types of computing devices with which operators can interact. For example, the at least one client device 108 and / or the at least one server 122 may include a mobile device (e.g., a cell phone, a smartphone, aPDA, a tablet, a laptop, a watch, a wearable device, etc.). In some embodiments, however, the at least one client device 108, and / or at least one server 122 can be a non-mobile device (e.g., a desktop or server). In some embodiments, the at least one server 122 may include a cloud computing platform and may be configured to perform processing required to implement the commodity monitoring system 120. In one or more embodiments, the at least one server 122 may include a web server that provides a web site that can be used by operators monitoring the contents of the container 106 via a remote client device 108. Additional details with respect to the client device 108 and the server 122 are discussed below with respect to FIG. 3.

[0052] Referring still to FIG. 1, while the commodity monitoring system 120 is depicted as being a portion of (e.g., implemented by) the server 122, the disclosure is not so limited. Rather, in some embodiments, the commodity monitoring system 120 may be implemented at one or more of the client device 108, the cable assembly 102, cable hubs 112, or the server 122. In some embodiments, the commodity monitoring system 120 may be implemented at a computing device that is local to the container 106 (e.g., edge computing). In some embodiments, the commodity monitoring system 120 may be implemented at different devices of the environment 100 operating according to a primarysecondary configuration or peer-to-peer configuration. For purposes of illustration and convenience, implementation of the commodity monitoring system 120 is described herein as being implemented by the server 122, with the understanding that functionality may be implemented in other and / or additional devices.

[0053] The network 110 may include one or more networks, such as the Internet, and can use one or more communications platforms or technologies suitable for transmitting data and / or communication signals. As a non-limiting example, the network 110 may utilize one or more of near field communication (NFC), BLUETOOTH ©, wireless / cellular networks, wide area networks (WAN), LoRa, wired communications, or any other conventional network for transmitting data and / or communication signals between the cable assembly 102, the client device 108, and the server 122.

[0054] Referring still to FIG. 1, in some embodiments, one or more of the at least one client device 108, the cable assembly 102, or the at least one server 122 may include a display for displaying data regarding measurements obtained via the cable assembly 102. In some embodiments, the data may include one or more parameters of commodity within the container 106. The parameters may include one or more of temperature, humidity, relative humidity, moisture, or carbon dioxide. In some embodiments, the commodity monitoring system 120 may utilize the parameters to determine when to actuate commodity management devices 118 of the container 106 to affect conditions of the commodity. As noted above, the commodity management devices 118 may include one or more of heaters, fans, blowers, churners, vents, etc.

[0055] FIG. 2 shows a flowchart of a method 200 for monitoring the contents (e.g., grain) within a container 106 according to one or more embodiments of the present disclosure. The method 200 may include receiving first temperature data (xi) from a hub sensor 124 of a cable hub 112 of the cable assembly 102 to which a cable 104 is coupled, as is shown in act 202 of FIG. 2. In some embodiments, the commodity monitoring system 120 may receive the first temperature data from the hub sensor 124. In one or more embodiments, the commodity monitoring system 120 may receive the first temperature data from the hub sensor 124 via the gateway 114 and the network 110.

[0056] In one or more embodiments, the first temperature data may have been captured via the hub sensor 124. Furthermore, in some embodiments, the commodity monitoring system 120 may initiate (e.g., may have previously initiated) capturing the first temperature data. In other words, the commodity monitoring system may have caused the hub sensor 124 to capture the first temperature data.

[0057] In some embodiments, the first temperature data may include first temperature measurements (e.g., a first temperature profile) captured over a period of time. In one or more embodiments, the first temperature measurements may be captured at least substantially continuously over the period of time. In additional embodiments, the first temperature measurements may be captured at regular intervals (e.g., every minute, every second, every 10 milliseconds, etc.) over the period of time.

[0058] The method 200 may further include receiving second temperature data (yi) from a sensor node 116 of the cable 104 coupled to the cable hub 112, as shown in act 204 of FIG. 2. In some embodiments, the commodity monitoring system 120 may receive the second temperature data from the sensor node 116. In some embodiments, the sensor node 116 may include an uppermost sensor node 116 of the cable 104. In one or more embodiments, the commodity monitoring system 120 may receive the second temperature data from the sensor node 116 via the gateway 114 and the network 110.

[0059] In one or more embodiments, the second temperature data may have been captured via the sensor node 116. Furthermore, in some embodiments, the commodity monitoring system 120 may initiate (e.g., may have previously initiated) capturing the second temperature data. In other words, the commodity monitoring system may have caused the sensor node 116 to capture the second temperature data.

[0060] In some embodiments, the second temperature data may include second temperature measurements (e.g., a second temperature profile) captured over the period of time (e.g., at least substantially the same period of time over which the first temperatures measurements were captured). In one or more embodiments, the second temperature measurements may be captured at least substantially continuously over the period of time. In additional embodiments, the second temperature measurements may be captured at regular intervals (e.g., every minute, every second, every 10 milliseconds, etc.) over the period of time. In one or more embodiments, the first temperature measurements and the second temperature measurements may be captured at the same intervals over the period of time.

[0061] The period of time may include a window of time, such as, for example, three hours, four hours, five hours, ten hours, twenty hours, thirty hours, forty hours, or more. As a non-limiting example, the period of time may include a window of time of at least nine hours. As another example, the period of time may include a window of time of at least twelve hours.

[0062] Referring generally to FIG. 2 and method 200, in some embodiments, relative humidity measurements may be captured via the hub sensor 124 and sensor nodes 116instead of or in addition to temperature measurements. For ease of explanation, method 200 is described utilizing only temperature measurements; however, the disclosure is not so limited, and in each instance where temperature measurements are described or mentioned, relative humidity measurements may be utilized instead of or in addition to the temperature measurements.

[0063] The method 200 may further include determining and generating a characteristic matrix for each of the first temperature data and the second temperature data, as shown in act 206 of FIG. 2. For example, the commodity monitoring system 120 may determine and generate a characteristic matrix for each of the first and second temperature data. For clarity, and for ease of explanation, an example method of determining and generating a characteristic matrix (e.g., a first characteristic matrix) for the first temperature data is described herein; however, a characteristic matrix (e.g., a second characteristic matrix) for the second temperature data may be determined and generated via any of the manners described herein.

[0064] Determining and generating a first characteristic matrix for the first temperature data (xi) may include defining the first temperature data as time-series data (e.g., a sequence of data points (e.g., temperature measurements) indexed in time order). In particular, each of the columns of the characteristic matrix may represent a given time at which a temperature measurement of the first temperature data was captured. For instance, a first column may represent a first, sequentially, temperature measurement (xi) taken within a time period, a second column, adjacent to the first column, may represent a second (e.g., a next), sequentially, temperature measurement (X2) taken after the first temperature measurement and within the time period, a third column, adjacent to the second column, may represent a third, sequentially, temperature measurement (X3) taken after the second temperature measurement and within the time period, and so on and so forth. In particular, from an original set of n measurements, a collection of sub-sequences may be built up using the sampling window size (m). The first of these subsequences may be defined as the first 1 to n-m+1 measurements. The next sub-sequence may move the window forward by an element, gathering measurements 2 to n-m+2, and so on and so forth until all n measureddata are used. In this way, the collected m samples may be arranged each as a column of the characteristic matrix A, which is an array of (n-m+1) x m elements . As noted above, a second characteristic matrix of the second temperature data may be determined via a same manner.

[0065] The method 200 also includes determining and normalizing singular values for each of the first characteristic matrix and the second characteristic matrix, as shown in act 208 of FIG. 2. For example, the commodity monitoring system 120 may determine and normalize singular values for each of the first characteristic matrix and the second characteristic matrix.

[0066] In some embodiments, the singular values of the first characteristic matrix and the second characteristic matrix may be determined by determining the square roots of positive eigenvalues of a scaled symmetric matrix (e.g., a Gram matrix) of each of the first and second characteristic matrices. As a non-limiting example, if the first characteristic matrix is represented by matrix A, m may be a time window length in hours from a first temperature measurement to a last temperature measurement within the sequence (e.g., time series), and n may be the number of temperature measurements within the sequence. Furthermore, the first scaled Gram matrix of the first characteristic matrix may be represented by:ATA

[0067] G = or n-m+l

[0069] F urthermore, the singular values of the first characteristic matrix would be the square root of positive, non-zero eigenvalues of the first scaled Gram matrix (G), where an eigenvalue of the first scaled Gram matrix (G) is a scalar A such that de t(G — l) = 0 or det( I — G) = 0 . Accordingly, the singular values of matrix A are: . The singular values of the second characteristic matrix may be determined via a same manner.

[0070] F urthermore, the singular values of the first characteristic matrix and the second characteristic matrix may be normalized via any conventional manner. In some embodiments, the singular values may be normalized in terms of the largest singular value. For example, by normalizing the largest singular value arof the first characteristic matrix,the largest singular value is disregarded in further calculations according to P(cti) = 1 and ln(l) = 0, described in further detail below.

[0071] The method 200 further includes determining an entropy value associated with each of the first temperature data and the second temperature data based on the determined, normalized singular values of the first temperature data and the second temperature data, as shown in act 210 of FIG. 2. For example, the commodity monitoring system 120 may determine an entropy value associated with each of the first temperature data and the second temperature data. In some embodiments, the entropy value may include a Shannon Entropy value (i.e., information entropy value). For the following example, normalized singular values of the first temperature data may be represented as signal a(t). In such an example, the Shannon Entropy (H) (i.e., information entropy) may be determined using the following equation:

[0073] where H is the Shannon Entropy of the normalized singular values of the first temperature data (e.g., the Shannon Entropy of the first temperature data), P(a / ) is the probability of obtaining the value a / , and 5 is the number of normalized singular values. The foregoing equation is a measure of signal complexity. The Shannon Entropy of the normalized singular values of the second temperature data (e.g., the Shannon Entropy of the second temperature data) may be determined in the same way.

[0074] Additionally, the method 200 includes categorizing each of the determined entropy values associated with the temperature measurements (e.g., the first temperature data and the second temperature data) as a high entropy value or a low entropy value, as shown in act 212 of FIG. 2. For example, the commodity monitoring system 120 may categorize each of the determined entropy values as a high entropy value or a low entropy value. In some embodiments, the commodity monitoring system 120 may utilize one or more cluster methods for categorizing determined entropy values as a high entropy value or a low entropy value. For example, categorizing each of the determined entropy values as a high entropy value or a low entropy value may include utilizing one or more of threshold clustering, k-means clustering, differential clustering, or any other known clusteringalgorithm to categorize the determined entropy values as a high entropy value or a low entropy value. In embodiments described herein, the entropy value associated with the hub sensor 124 will be considered a high entropy value.

[0075] The method 200 may further include determining of a status of the sensor node 116 of the cable 104, as shown in act 214 of FIG. 2. In some embodiments, the commodity monitoring system 120 may determine the status of the sensor node 116 of the cable 104. As mentioned above, the status of the sensor node 116 may refer to whether the sensor node 116 is "in commodity" (e.g., in contact with the commodity (e.g., the contents) within the container 106) or "out of commodity" (e.g., not in contact with the commodity within the container 106). As is described below, in some embodiments, act 214 may include determining the statuses of all of the sensor nodes 116 of a given cable 104 at least substantially simultaneously.

[0076] The status of the sensor node 116 of the cable 104 may be determined based on whether the entropy value associated with the sensor node 116 is categorized as a low entropy value or a high entropy value, as categorized in act 212 of FIG. 2. For example, if the entropy value associated with the sensor node 116 is categorized as a high entropy value, the sensor node 116 will be determined to be out of commodity. Alternatively, if the entropy value associated with the sensor node 116 is categorized as a low entropy value, the sensor node 116 will be determined to be in commodity.

[0077] Responsive to a determination that the sensor node 116 is out of commodity, the method 200 may include repeating acts 204 through 214 for a vertically adjacent sensor node 116 of the cable 104, as shown in act 216 of FIG. 2. For example, the method 200 may begin with an uppermost sensor node 116 (e.g., a top-most sensor node 116 in a vertical direction) of the cable 104, and responsive to determination that the uppermost sensor node 116 is out of commodity, a status of a second-uppermost sensor node 116 may be analyzed via acts 202 through 230. Furthermore, the method 200 may include analyzing the status of each consecutive sensor node 116 of the cable 104 in a downward direction until a sensor node 116 of the cable 104 is determined to be in commodity or until a status of each sensor node 116 of the cable 104 is determined. Additionally, responsive to a determination that agiven sensor node 116 is in commodity, each sensor node 116 of the cable 104 below the given sensor node 116 is assumed and determined to be in commodity.

[0078] Referring still to act 216, alternatively, each sensor node 116 of a given cable 104 will be analyzed at least substantially simultaneously via acts 204 through 214. Accordingly, the determined entropy values associated with each sensor node 116 of the given cable 104 may be categorized as a high entropy value or a low entropy value via a same clustering algorithm and process. Additionally, the status of each sensor node 116 of the given cable 104 may be determined at least substantially simultaneously based on whether the entropy value associated with each sensor node 116 is categorized as a low entropy value or a high entropy value, as described above in regard to act 214.

[0079] Referring still to FIG. 2, in some embodiments, each cable 104 of the cable assembly 102 may be analyzed independently via method 200. In additional embodiments, two or more of the cables of the cable assembly 102 may be analyzed at least substantially simultaneously via method 200.

[0080] In some embodiments, the method 200 may further optionally include adjusting operation of one or more commodity management devices 118, as shown in act 218 of FIG. 2. For example, the commodity monitoring system 120 may adjust operation of one or more commodity management devices 118. In one or more embodiments, the commodity monitoring system 120 may adjust operation of one or more commodity management devices 118 based at least partially on the determined statuses of the sensor nodes 116 of the cable assembly 102. For example, which sensor nodes 116 of the cable assembly 102 are determined to be in commodity and which sensor nodes 116 of the cable assembly 102 are determined to be out of commodity may influence operation of the one or more commodity management devices 118. As noted above, the one or more commodity management devices 118 may include one or more of heaters, fans, blowers, churners, vents, etc.

[0081] Referring still to act 218 of FIG. 2, knowing which sensor nodes 116 of the cable assembly 102 are in commodity and which sensor nodes 116 of the cable assembly 102 are out of commodity may improve data (e.g., provide more accurate data) utilized tooperate the one or more commodity management devices 118. For example, in drying operations, fans, blowers, and / or heaters draw and / or blow air from outside the container 106 into the container 106. The incoming air will have a certain humidity (e.g., moisture content) and temperature. When the commodity is exposed to the air, a moisture and a temperature of the commodity will eventually reach an equilibrium point approaching the moisture content and the temperature of the air. As a non-limiting example, the air may have an equilibrium moisture content of about 14%, and prolonged exposure to the air causes the commodity to approach a moisture content of about 14%. However, in typical operations, fans, blowers, and / or drier are set to dry (e.g., bring in air from out outside of the container 106) as long the incoming air is within a target range of temperatures and moisture contents for the commodity or as long as the incoming air is at a temperature and / or a moisture content that will cause the commodity to approach the target range of temperatures and moisture contents. Accordingly, accurate data from the commodity can be critical to know when fans, blowers, and / or heaters should be operating. In view of the foregoing, by knowing which sensor nodes 116 are in commodity, only data from those incommodity sensor nodes 116 may be utilized in determining moisture contents and temperatures of the commodity, and the data from the sensor nodes 116 out of commodity can be disregarded or not captured. Accordingly, the commodity monitoring system 120 and methods of the present disclosure result in more accurate data than conventional commodity monitoring systems. Furthermore, having more accurate data can result in faster and more accurate commodity treatments (e.g., drying).

[0082] In some embodiments, adjusting operation of one or more commodity management devices 118 may include one or more of turning on or off fans, blowers, and / or heaters, increasing or decreasing air flow through the commodity via fans, blowers, and / or heaters, turning on or off churners, and / or opening or closing vents of the container 106.

[0083] Referring still to FIG. 2, in some embodiments, the method 200 may optionally include determining (e.g., estimating) one or more profiles of an upper surface of the commodity, as shown in act 220. For example, the commodity monitoring system 120 may determine (e.g., estimate) one or more profiles of an upper surface of the commodity, asshown in act 220. In some embodiments, by determining, for each sensor node 116 of each cable 104 of the cable assembly 102, whether the sensor node 116 is in commodity or out of commodity and based on known elevations (e.g., vertical locations) and known locations of the sensor nodes 116 of the cable assembly 102, the commodity monitoring system 120 may determine heights of the commodity at each of the cables 104 of the cable assembly 102.

[0084] In some embodiments, determining heights of the commodity at each of the cables 104 of the cable assembly 102 may include determining the heights of the commodity based at least partially on a known time period since a given sensor node 116 was determined to change from being in commodity to out of commodity. For example, determining heights of the commodity at each of the cables 104 of the cable assembly 102 may include estimating how much the height of the commodity has changed relative to an elevation of given sensor node 116, previously determined to be in commodity, based at least partially on one or more of 1) a known time period since the given sensor node 116 was determined to be in commodity, 2) a known amount of commodity (e.g., grain) added to the container 106, 3) a known amount of commodity (e.g., grain) removed from the container 106, and / or 4) a known rate at which the height of the contents has changed previously.

[0085] Determining heights of the commodity at each of the cables 104 of the cable assembly 102 may enable the commodity monitoring system 120 to determine (e.g., estimate) one or more profiles of an upper surface of the commodity. Furthermore, determining (e.g., estimating) one or more profiles of an upper surface of the commodity may enable the commodity monitoring system 120 to determine a volume of the commodity within the container 106.

[0086] Additionally, the method 200 may include outputting determined heights, the determined upper surface profiles, and / or determined volumes of the commodity to the client device 108. For example, the commodity monitoring system 120 may cause the determined heights, the determined upper surface profiles, and / or the determined volumes of the commodity to be displayed on the client device 108. Additionally, the method 200may include outputting the determined heights, the determined upper surface profiles, and / or the determined volumes of the commodity to one or more third party systems.

[0087] FIG. 3 is a schematic view of a computer device 314. In some embodiments, one or more of the commodity management device 118, the client device 108, and / or the server 122 may include a computer device such as the computer device 314 of FIG. 3. The computer device 314 may include a communication interface 302, a processor 304, a memory 306, a storage device 308, an input / output device 310, and a bus 312.

[0088] In some embodiments, the processor 304 includes hardware for executing instructions, such as those making up a computer program. As an example, and not by way of limitation, to execute instructions, the processor 304 may retrieve (or fetch) the instructions from an internal register, an internal cache, the memory 306, or the storage device 308 and decode and execute them. In some embodiments, the processor 304 may include one or more internal caches for data, instructions, or addresses. As an example, and not by way of limitation, the processor 304 may include one or more instruction caches, one or more data caches, and one or more translation look aside buffers (TLBs). Instructions in the instruction caches may be copies of instructions in the memory 306 or the storage device 308.

[0089] The memory 306 may be coupled to the processor 304. The memory 306 may be used for storing data, metadata, and programs for execution by the processor(s). The memory 306 may include one or more of volatile and non-volatile memories, such as Random-Access Memory ("RAM"), Read-Only Memory ("ROM"), a solid state disk ("SSD"), Flash, Phase Change Memory ("PCM"), or other types of data storage. The memory 306 may be internal or distributed memory.

[0090] The storage device 308 may include storage for storing data or instructions. As an example, and not by way of limitation, storage device 308 can comprise a non- transitory storage medium described above. The storage device 308 may include a hard disk drive (HDD), Flash memory, an optical disc, a magneto-optical disc, magnetic tape, or a Universal Serial Bus (USB) drive or a combination of two or more of these. The storage device 308 may include removable or non-removable (or fixed) media, where appropriate. Thestorage device 308 may be internal or external to the computing storage device 308. In one or more embodiments, the storage device 308 is non-volatile, solid-state memory. In other embodiments, the storage device 308 includes read-only memory (ROM). Where appropriate, this ROM may be mask programmed ROM, programmable ROM (PROM), erasable PROM (EPROM), electrically erasable PROM (EEPROM), electrically alterable ROM (EAROM), or Flash memory or a combination of two or more of these.

[0091] The input / output device 310 may allow an operator of the commodity monitoring system 120 to provide input to, receive output from, and otherwise transfer data to and receive data from computer device 314. The input / output device 310 may include a mouse, a keypad or a keyboard, a joystick, a touch screen, a camera, an optical scanner, network interface, modem, other known I / O devices, or a combination of such I / O interfaces. The input / output device 310 may include one or more devices for presenting output to an operator, including, but not limited to, a graphics engine, a display (e.g., a display screen), one or more output drivers (e.g., display drivers), one or more audio speakers, and one or more audio drivers. In certain embodiments, the input / output device 310 is configured to provide graphical data to a display for presentation to an operator. The graphical data may be representative of one or more graphical user interfaces and / or any other graphical content as may serve a particular implementation. As is described above, the computer device 314 and the input / output device 310 may be utilized to display data (e.g., images and / or video data) regarding the contents of the container 106.

[0092] The communication interface 302 can include hardware, software, or both. The communication interface 302 may provide one or more interfaces for communication (such as, for example, packet-based communication) between the computer device 314 and one or more other computing devices or networks (e.g., a server). As an example, and not by way of limitation, the communication interface 302 may include a network interface controller (NIC) or network adapter for communicating with an Ethernet or other wire-based network or a wireless NIC (WNIC) or wireless adapter for communicating with a wireless network, such as a WI-FI.

[0093] In some embodiments, the bus 312 (e.g., a Controller Area Network (CAN) bus) may include hardware, software, or both that couples components of computer device 314 to each other and to external components.

[0094] All references cited herein are incorporated herein in their entireties. If there is a conflict between definitions herein and in an incorporated reference, the definition herein shall control.

[0095] The embodiments of the disclosure described above and illustrated in the accompanying drawings do not limit the scope of the disclosure, which is encompassed by the scope of the appended claims and their legal equivalents. Any equivalent embodiments are within the scope of this disclosure. Indeed, various modifications of the disclosure, in addition to those shown and described herein, such as alternate useful combinations of the elements described, will become apparent to those skilled in the art from the description. Such modifications and embodiments also fall within the scope of the appended claims and equivalents.

Claims

CLAIMSWhat is claimed is:

1. A method of monitoring a commodity within a container, the method comprising: receiving first temperature data from a hub sensor of a cable hub; receiving second temperature data from a sensor node of a cable coupled to the cable hub; based at least partially on the first temperature data, determining a first entropy value associated with the first temperature data; based at least partially on the second temperature data, determining a second entropy value associated with the second temperature data; comparing the first entropy value with the second entropy value; and based at least partially on the comparison of the first entropy value to the second entropy value, determining whether the sensor node of the cable is in a commodity within the container or out of the commodity within the container.

2. The method of claim 1, wherein determining the first entropy value associated with the first temperature data comprises: defining the first temperature data as first time-series data; and determining and generating a first characteristic matrix representing the first timeseries data.

3. The method of claim 2, wherein determining the first entropy value associated with the first temperature data further comprises: determining singular values of the first characteristic matrix; normalizing the determined singular values; and determining the first entropy value based at least partially on the normalized, determined singular values.

4. The method of claim 3, wherein determining the first entropy value comprises determining a first Shannon Entropy value.

5. The method of claim 4, wherein determining the first Shannon Entropy value comprises determining the first Shannon Entropy value via the following:

6. The method of claim 4 or 5, further comprising categorizing the first entropy value as a high entropy value.

7. The method of claim 6, further comprising categorizing the second entropy value as either a high entropy value or a low entropy value.

8. The method of claim 7, responsive categorizing the second entropy value as a high entropy value, determining that the sensor node is out of commodity.

9. The method of claim 7, responsive categorizing the second entropy value as a low entropy value, determining that the sensor node is in commodity.

10. The method of claim 7, further comprising, responsive to determining that the sensor node is out of commodity: receiving third temperature data from a lower sensor node of the cable; based at least partially on the third temperature data, determining a third entropy value associated with the third temperature data; comparing the first entropy value with the third entropy value; and based at least partially on the comparison of the first entropy value to the second entropy value, determining whether the lower sensor node of the cable is in the commodity within the container or out of the commodity within the container.

11. The method of any one of any one of claims 1 to 10, further comprising, responsive to a determination as to whether the sensor node is in commodity or out of commodity, adjusting operation of one or more commodity treatment devices of the container.

12. The method of claim 11, wherein adjusting operation of the one or more commodity treatment devices of the container comprises at least one of turning on or off fans, blowers, or heaters, increasing or decreasing air flow through the commodity via fans, blowers, or heaters, turning on or off ch urners, or opening or closing vents of the container.

13. The method of any one of claims 1 to 12, wherein the first temperature data comprises first temperature measurements captured over a period of time, and wherein the second temperature data comprises second temperature measurements captured over the period of time.

14. The method of any one of claims 1 to 12, wherein the first temperature data comprises a first temperature profile over a period time, and wherein the second temperature data comprises a second temperature profile over the period of time.

15. The method of claim 1, further comprising: receiving first relative humidity data from the hub sensor of the cable hub; receiving second relative humidity data from the sensor node of the cable coupled to the cable hub; and determining the first and second entropy values based at least partially on the received first and second relative humidity data.

16. A system, comprising: a container; a cable assembly disposed within the container and comprising: at least one cable hub having a hub sensor disposed therein; and at least one cable coupled to and hanging from the at least one cable hub, the at least one cable having a plurality of sensor nodes operably coupled to the at least one cable; and a commodity monitoring system in communication with the cable assembly and comprising: at least one processor; and at least one non-transitory computer-readable storage medium storing instructions thereon that, when executed by the at least one processor, cause the commodity monitoring system to: determine a first entropy value associated with the hub sensor based at least partially on at least one of first temperature data or first relative humidity data received from the hub sensor of the at least one cable hub; determine a second entropy value associated with a sensor node of the plurality of sensor nodes coupled to the at least one cable based at least partially on at least one of second temperature data or first relative humidity received from the sensor node; compare the first entropy value with the second entropy value; and based at least partially on the comparison of the first entropy value to the second entropy value, determining whether the sensor node of the plurality of sensor nodes coupled to the at least one cable is in the commodity within the container or out of the commodity within the container.

17. The system of claim 16, further comprising instructions that, when executed by the at least one processor, cause the commodity monitoring system to: categorize the first entropy value as a high entropy value; and utilize a clustering algorithm to determine whether to categorize the second entropy value as a high entropy value or a low entropy value.

18. The system of claim 17, further comprising instructions that, when executed by the at least one processor, cause the commodity monitoring system to: responsive categorizing the second entropy value as a high entropy value, determining that the sensor node is out of commodity.

19. The system of claim 17, further comprising instructions that, when executed by the at least one processor, cause the commodity monitoring system to: responsive categorizing the second entropy value as a low entropy value, determining that the sensor node is in commodity.

20. A method of monitoring a commodity within a container, the method comprising based on a comparison of an entropy value associated with a sensor external to a container and additional entropy values associated with sensor nodes of a cable within the container, determining which sensor nodes of the cable are in commodity and which sensor nodes of the cable are out of commodity.

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