End-to-end mineral tracking system

Abstract

Apparatus and associated methods relate to extraction integrity verification of a mineral extraction process. In an illustrative example, a secure mineral authentication and tracking system (SMATS) may include an end-to-end mineral tracking system (EMTS). The EMTS, for example, may be configured to receive a mineral physical characteristics struct (MFCS) at two or more mineral characteristics detection devices (MCDD). For example, each of the MCDD may be disposed at a predetermined stage of an extraction process (e.g., at a cooling gate, at a shipping gate). For example, the MCDD may be configured to automatically access physical attributes of a predefined mineral lot. In some implementations, the SMATS may automatically compare two or more of the MFCS to determine whether the mineral lot is uniform along the extraction process. Various embodiments may advantageously provide an automatic system for tracking and authenticating individual mineral lots within the extraction process.

Description

END-TO-END MINERAL TRACKING SYSTEMTECHNICAL FIELD

[0001] Various embodiments relate generally to systems and methods for automatically tracking and verifying the integrity of mineral output throughout an extraction and / or refining process..BACKGROUND

[0002] Minerals may include natural resources that have economic and / or industrial value. Minerals may be used for various purposes, such as manufacturing, construction, energy, and / or jewelry. To obtain the desired minerals from the earth's crust, they may need to be extracted and refined through various processes. Mineral extraction and refinement processes may vary depending on the type and quality of the ore, as well as the desired end product, for example.

[0003] For example, copper ores may be mined by open-pit and / or underground methods, depending on the depth and grade of the ore. The ores may be crushed and ground to liberate the copper minerals, which may then be concentrated by flotation and / or leaching. The concentrated copper may be smelted, for example, to produce copper matte (e.g., a mixture of copper and iron sulfides). The matte may be further refined by converting, fire refining, and / or electrolytic refining to produce pure copper ingots, for example.

[0004] Iron ores, for example, may be mined by surface and / or underground methods. The ores may be beneficiated by crushing, screening, washing, magnetic separation, gravity separation, and / or flotation, such as, for example, to increase the iron content and / or reduce the impurities. The beneficiated iron ore may be agglomerated into pellets and / or sintered for blast furnace smelting. The molten iron from the blast furnace may be further refined by basic oxygen furnace (BOF), electric arc furnace (EAF), and / or direct reduced iron (DRI) processes.

[0005] Platinum ores may be mined by various methods, such as, for example, open-pit, underground, and / or alluvial mining. The ores may be crushed and milled to separate the platinum group metals (PGMs) from the gangue minerals. The PGMs may be concentrated by flotation, gravity separation, and / or magnetic separation. The concentrated PGMs may be smelted to produce a PGM-rich matte, which may, for example, then be converted to a PGM-rich alloy. The alloy may be further refined, for example, by hydrometallurgical and / or pyrometallurgical processes to produce pure platinum and / or other PGMs.

[0006] Some minerals may be extracted in liquid form. For example, liquid mineral extraction and processing may include methods of obtaining and / or purifying minerals that are dissolved or suspended in water and / or other solvents.100071 Salt mining may include, for example, the process of extracting salt from saline water sources, such as seawater, brine wells, and / or salt lakes. The salt may be obtained by evaporating the water, such as by natural solar radiation and / or by artificial heating. The salt may be further refined by washing, drying, and / or screening to produce various grades of salt for different uses.

[0008] Uranium mining may include a process of extracting uranium from ore deposits that contain uranium-bearing minerals, such as pitchblende, uraninite, and / or carnotite. The uranium may be leached from the ore by using acidic and / or alkaline solutions, which may then be pumped to the surface. The uranium may, for example, be concentrated by solvent extraction, ion exchange, and / or precipitation to produce yellowcake, a semi-refined form of uranium oxide.

[0009] Lithium mining may include a process of extracting lithium from brine pools, spodumene ore, and / or clay deposits. The lithium may be extracted from the brine by using evaporation ponds, membrane filtration, and / or electrolysis. The lithium may, for example, be extracted from the spodumene ore by roasting, leaching, and / or precipitation. The lithium may be extracted from the clay deposits by using acid leaching, solvent extraction, and / or precipitation. The lithium may be further purified, for example, using hydrometallurgical and / or pyrometallurgical processes to produce lithium carbonate, lithium hydroxide, and / or lithium metal.

[0010] Gold mining includes a process of extracting gold ores from the earth's crust. For example, the process may include various techniques. Some gold mining processes may include placer mining. Some gold mining processes may include hard rock mining. Some gold mining processes may include byproduct mining. Some gold mining processes may include gold ore processing. Extracted raw gold ore, in some processes, may undergo multiple stages of processing. For example, some of the processes may be configured to separate gold from other materials in the ore (e.g., using techniques like crushing, grinding, and various chemical treatments).

[0011] Once a mineral (e.g., the raw gold) is extracted, for example, the mineral may be transported to a nearby facility (e.g., from an extraction site) for preliminary processing. In this stage, for example, the raw gold ore may be melted and cast into low-quality gold bars (dore bars). For example, the dore bars may include a mix of gold and other metals (e.g., impurities). In some examples, the casting of the dore bars may advantageously facilitate transportation and subsequent refining of the extracted minerals.

[0012] In some examples, a final step of a mineral process may include refining. For example, a gold refining process may include transporting the low-quality gold bars to a refinery. At the refinery, for example, the low-quality gold bars may be melted. The low-quality gold bars may, for example, undergo further purification configured to remove impurities. In some examples, a result from the refinery process may include a higher purity level gold bar (e.g., from 70% gold to 99%). Some refinery processes may include electrolysis, chemical chlorination, the Miller process,and / or other mechanical / chemical / electrical processes. For example, the resulting high-purity gold may then be cast into high-quality gold bars suitable for transportation and / or use in various industries.SUMMARY

[0013] Apparatus and associated methods relate to extraction integrity verification of a mineral extraction process. In an illustrative example, a secure mineral authentication and tracking system (SMATS) may include an end-to-end mineral tracking system (EMTS). The EMTS, for example, may be configured to receive a mineral physical characteristics struct (MPCS) at two or more mineral characteristics detection devices (MCDD). For example, each of the MCDD may be disposed at a predetermined stage of an extraction process (e.g., at a cooling gate, at a shipping gate). For example, the MCDD may be configured to automatically access physical attributes of a predefined mineral lot. In some implementations, the SMATS may automatically compare two or more of the MPCS to determine whether the mineral lot is uniform along the extraction process. Various embodiments may advantageously provide an automatic system for tracking and authenticating individual mineral lots within the extraction process.

[0014] Various embodiments may achieve one or more advantages. For example, some embodiments may advantageously provide a continuous monitoring and validation system for mineral extraction, refining, and transportation processes. Some embodiments, for example, may advantageously allow processing of a bulk quantity of individual mineral lots within a short period of time. For example, some embodiments may advantageously provide compliance of data accuracy and / or data security. Some embodiments may, for example, allow an owner of the extraction site to individually trace each extracted output of the extraction site down to the mineral lot level across the extraction-refinery process. For example, some embodiments may advantageously provide an automatic and quick process for validating and tracking mineral lots (e.g., raw gold bars) without holding up an on-going extraction process. Some embodiments may, for example, advantageously authenticate each mineral lot individually assessed and / or validated in a timely manner. For example, some embodiments may advantageously improve an efficiency and / or reliability of the mineral extraction process.

[0015] The details of various embodiments are set forth in the accompanying drawings and the description below. Other features and advantages will be apparent from the description and drawings, and from the claims.BRIEF DESCRIPTION OF THE DRAWINGS

[0016] FIG. 1 depicts an exemplary secure mineral authentication and tracking system (SMATS) employed in an illustrative use-case scenario.100171 FIG. 2 depicts the exemplary SMATS as described in FIG. 1 employed in an illustrative second use-case scenario.

[0018] FIG. 3 is a block diagram depicting an exemplary end-to-end mineral tracking system.

[0019] FIG. 4 is a flowchart illustrating an exemplary extracting site mineral integrity tracking method.

[0020] FIG. 5 is a flowchart illustrating an exemplary refinery site mineral integrity tracking method.

[0021] Like reference symbols in the various drawings indicate like elements.DETAILED DESCRIPTION OF ILLUSTRATIVE EMBODIMENTS

[0022] FIG. 1 depicts an exemplary secure mineral authentication and tracking system (SMATS 100) employed in an illustrative use-case scenario. For example, the SMATS 100 may track (e.g., across multiple locations, multiple time-space, multiple forms) a mineral quality of an output from a mineral ore and / or mineral refinery. In this example, the SMATS 100 includes an extraction site 105 and a refinery 1 10. For example, the extraction site 105 may include a mineral ore. For example, an operator may extract gold from the extraction site 105. For example, an operator may extract silver from the extraction site 105. For example, an operator may extract copper from the extraction site 105. For example, an operator may extract rare earth (e.g., neodymium, lanthanum, cerium) from the extraction site 105.

[0023] For example, the refinery 110 may receive a quantity of mineral ore (e.g., gold, silver, lithium, other materials in the periodic table) from the extraction site 105. In some embodiments, the refinery 110 may refine the received mineral ore from a lower quality form to a high quality (e.g., purer) form. For example, the refinery 110 may produce an output quantum (e.g., lots) of a predefined mineral in a refined form based on a predetermined composition of a received quantum of the mineral. In various embodiments, the SMATS 100 may advantageously provide a continuous monitoring and validation system for mineral extraction, refining, and transportation processes.

[0024] As shown, after a mineral mining process 115, the extraction site 105 may receive a mineral output unit(s) (MOU 120). For example, the MOU 120 may include extracted minerals in various forms (e.g., in bar form, in liquid form contained in a predefined container, and / or in bulk contained in a predefined container). For example, each of the MOU 120 may be uniquely identified with an identifier tag 125 (e.g., using a barcode, a unique identifier, a quick response (QR) code, a radio frequency identifier (RFID), a near field chip (NFC)).

[0025] In some implementations, the extraction site 105 may include a detection location configured to detect physical characteristics of the MOU 120. In this example, the extraction site105 includes a cooling gate 130. In this example, the MOU 120 may pass through the cooling gate 1 0 into a cooling room 135. For example, the MOU 120 may be stored temporarily in the cooling room 135 until a next shipment to the refinery 110.

[0026] As shown, the cooling gate 130 includes a mineral characteristics detection device (MCDD 140). For example, the MCDD 140 may scan the MOU 120 to analyze the quality of each of the MOU 120 to generate a mineral physical characteristics struct (MPCS 145 A). As shown, the MPCS 145A is stored in a mineral physical characteristics storage 145. In some embodiments, the MCDD 140 may include one or more detection modules configured to assess one or more characteristics of the MOU 120. In this example, the MCDD 140 includes a weight 150 and a X- ray Fluorescence machine 155. In some embodiments, other devices for accessing the physical characteristics may be used. For example, the MCDD 140 may include an optical emission spectrometer, a laser-induced breakdown spectroscopy (LIBS) device, a density meter, a hardness tester, an ultrasonic thickness gauge, a surface roughness analyzer, and / or a combination thereof. Each of these devices, for example, may generate a detection signal of a measured physical aspect of the MOU 120.

[0027] In some implementations, the MPCS 145 A may include a grading result (e.g., high, low, intermediate, carat value) associated with the identifier tag 125 of the MOU 120. For example, the MPCS 145A may include a weight of the MOU 120. For example, the MPCS 145A may include a detected dimension of the MOU 120. In some implementations, the grading result, the size, and / or the weight of each of the MOU 120 may be associated with the unique identifier and saved to a secure data store (e.g., an on-premises storage device, a cloud storage device).

[0028] In some implementations, the MPCS 145A may include a camera. For example, the camera may take a picture of the identifier tag 125 on the MOU 120. For example, the MPCS 145 A may include the picture associated with the identifier tag 125. In some examples, a process of detecting physical characteristics of the MOU 120 may last for a short period (e.g., 10 seconds, 20 seconds, 1 minute, less than 10 minutes). Various embodiments may advantageously allow processing of a bulk quantity of the MOU 120 within a short period of time.

[0029] In some embodiments, physical characteristics of the MOU 120 may be detected at multiple locations and / or at different times to ensure unity of the MOU 120 at different time and / or space. In this example, the MOU 120 is measured at a shipping gate 160. For example, the MOU 120 may be transported to a packing room 165 through the shipping gate 160. For example, the MOU 120 may be packed in a parcel 170 in the packing room 165 before shipping to the refinery 110.

[0030] In this example, at the shipping gate 160, the identifier tag 125 of the MOU 120 may each be scanned. For example, the shipping gate 160 may include a second MCDD (e.g., a machinewith same capability as the MCDD 140) to access the physical characteristics of the MOU 120. For example, the MOU 120 may each be weighed individually. For example, the second MCDD may generate a second analysis result including a second MOU physical characteristic struct 145B associated with the identifier tag 125 when the MOU 120 associated with the identifier tag 125 is being transferred into the packing room 165 through the shipping gate 160. In some embodiments, the SMATS 100 may compare the second MOU physical characteristic struct 145B against the stored MPCS 145A (e.g., retrieved from the secure data store). For example, the SMATS 100 may generate an error signal 175 (e.g., an error message, a triggering signal to other system to perform remedial actions) if, for example, a difference between the second MOU physical characteristic struct 145B and the MPCS 145 A is above a predetermined threshold.

[0031] As shown, the parcel 170 includes a parcel identifying PIT 180. For example, the PIT 180 may be associated with the identifier tag 125 of the MOU 120 contained within the error signal 175. In some implementations, the packing room 165 may include characteristics assessment devices to generate a parcel profile 185 associated with the PIT 180. For example, the parcel profile 185 may include a package weight 190.

[0032] In some embodiments, the PIT 180 may include a location tracking device (e.g., Global Positioning System (GPS) device). As shown, the parcel profile 185 may include a current location 195 of the parcel 170. For example, at designated locations (e.g., a receiving port of the refinery 110), the parcel 170 may be weighed to determine whether a weight of the received parcel is the same as the package weight 190.

[0033] In some implementations, the refinery 110 may include a third MCDD configured to scan and detect the physical characteristics of each of the MOU 120 in the parcel 170. For example, the third MCDD may generate a third MOU physical characteristic struct 145C. Based on a difference between the MPCS 145 A, the third MPCS 145C and (optionally, other intermediate MPCS (e.g., the second MPCS)), the SMATS 100 may determine whether the MOU 120 is the same MOU from the extraction site 105. For example, the SMATS 100 may generate the error signal 175 when, for example, a difference between the MPCS 145A and the third MPCS 145C is above a threshold.

[0034] FIG. 2 depicts the exemplary SMATS as described in FIG. 1 employed in an illustrative second use-case scenario. In this example, a post-extraction scenario 200 includes a transportation device 205 (e.g., a truck, a boat, a railway car, an airplane, a helicopter). The transportation device 205 carries the parcel 170. For example, the parcel 170 may contain various precious mineral (types) in a predetermined form (e.g., the MOU 120). In this example, the transportation device 205 is delivering the parcel 170 to the refinery 110. For example, the one or more predetermined locations 210 may include a departure airport. For example, the one or more predeterminedlocations 210 may include an arrival airport. For example, the one or more predetermined locations 210 may include a receiving dock of the refinery 110.

[0035] As shown, the transportation device 205 may pass through one or more predetermined locations 210 before arriving at the refinery 110. Each of the one or more predetermined locations 210 includes a MCDD 215. In some implementations, the MCDD 215 may be configured to detect various physical characteristics (e.g., weight, color, reflection coefficients, refraction coefficients, composition, purity, size) using various measurement devices and / or sensors. For example, the MCDD 215 may include an XRF device configured to analyze elemental compositions of each MOU within the parcel 170. For example, the XRF device may measure fluorescent X-rays emitted from each MOU when it is excited by a primary X-ray source. In some examples, the MCDD 215 may include other devices (e.g., a digital scale for precise weight measurement, a colorimeter for color analysis, a spectrometer for measuring reflection and refraction coefficients, a laser scanner for size and shape analysis). In some embodiments, the MCDD 215 at each of the one or more predetermined locations 210 may be substantially the same. In other embodiments, the MCDD 215 at each of the one or more predetermined locations 210 may include different measurement devices to detect same, partially the same, or different physical characteristics of the MOU 120 within the parcel 170.

[0036] In this example, the MCDD 215 at each of the one or more predetermined locations 210 transmits detected physical characteristics to the SMATS 100 by generating a MPCS 220. For example, the MPCS 220 may include a data structure of various characteristics detected by the MCDD 215 at a corresponding one or more predetermined locations 210. For example, the MPCS 220 may be generated in an Extensible Markup Language (XML) format. For example, the MPCS 220 may be generated in other data formats (e.g., in JavaScript Object Notation (JSON), in Comma-Separated Values (CSV), binary format). In some embodiments, the MPCS 220 may be transmitted to the SMATS 100 over a data network (e.g., the Internet). In some embodiments, the MPCS 220 may be transmitted through a secure communication channel of the data network. For example, transmitting the MPCS 220 through the secure communication channel may advantageously provide compliance of data accuracy and / or data security. For example, a user may be provided a reliable “snapshot” of the physical characteristics of each MOU in the parcel 170 at each stage of the extraction and refining process.

[0037] In some implementations, the parcel 170 may be configured to continuously communicate with the SMATS 100. In this example, the parcel 170 includes a parcel identifying tag (PIT 180). For example, the PIT 180 may be configured to transmit a location signal to the SMATS 100 representing a location (e.g., a GPS coordinate) to the SMATS 100. The SMATS 100 includes a MOU location tracking engine (MLTE 230) to receive the location signal from the PIT 180.|0038| In some embodiments, the parcel 170 may include other communication devices. For example, the parcel 170 may include a sensor network connected to a communication device configured to transmit various sensing data (e.g., speed, temperature, atmospheric pressure) to the SMATS 100. For example, the SMATS 100 may store the sensing data received from the parcel 170. For example, a user may determine a current situation or a historical situation of the parcel 170 during the transportation process. In some examples, these current and historical situations may be useful for, for example, an investigation process.

[0039] The SMATS 100 includes a structs comparison engine (DCE 235). For example, the DCE 235 may receive the MPCS 220 generated at the one or more predetermined locations 210. In some implementations, the DCE 235 may compare the MPCS 220 with an MPCS received from the extraction site 105 (e.g., the MPCS 145A-C, and / or other MPCS generated at one or more predetermined locations in the extraction site 105). For example, the MLTE 230 may generate a signal indicating a pass or fail of an MPCS comparison. For example, if a difference between a composition indicated in the MPCS 220 and any one or more of the MPCS 145 A-C in the mineral physical characteristics storage 145 is larger than a predetermined threshold (e.g., 70% gold in the MPCS 145A vs 10% gold in the MPCS 220), the MLTE 230 may generate a fail signal. For example, the MLTE 230 may generate a fail signal if both (or either of) the composition of the MOU and a weight of the MOU is less than the MPCS 145B by a predetermined threshold (e.g., an absolute difference, a percentage difference). In various examples, the SMATS 100 may transmit the failed signal to a third party device (e.g., an extraction site owner’s device).

[0040] As shown, the refinery 110 includes a proceed generation unit (PGU 240) and a storage level 245. For example, the storage level 245 may include a stock level of refined minerals (e.g., gold, silver, copper, petroleum, lithium). The PGU 240 may be configured to generate a proceed based on refined minerals transferred out of the refinery 110. For example, the proceeds may be generated as a function of output minerals and a market price of the minerals.

[0041] In this example, the refinery 110 includes a refinery status generation unit (RSGU 250). For example, the RSGU 250 may be configured to generate a refinery status 225 of the refinery 110 to the SMATS 100. As shown, the RSGU 250 may generate refinery status 225 including a transfer data 255, a current storage level 260, and a proceed feedback 265. For example, the transfer data 255 may include information related to a change in the storage level 245 based on refined minerals being transferred out of the refinery 110. For example, the transfer data 255 may include unique identifiers of MOU transferred into the refinery 110.

[0042] The current storage level 260, for example, may include the storage level 245 of various minerals in the refinery 110 at a time of generation. The proceed feedback 265 may, for example,include information of proceeds generated by the transfer of the refined minerals out of the refinery 110.

[0043] The SMATS 100 includes a stock level prediction engine (SLPE 270) and a proceed prediction engine (PPE 275) to receive the refinery status 225. In some implementations, the RSGU 250 may generate the refinery status 225 using a digital format. In some implementations, the RSGU 250 may generate the refinery status 225 using a paper (e.g., a report) format. In some examples, the SMATS 100 may include an optical character recognition (OCR) system. For example, the OCR system may receive, and associate documents related to the refinery status 225.

[0044] After receiving the refinery status 225, for example, the SLPE 270 may be configured to validate whether the current storage level 260 is matching to a predicted storage level. In this example, the SLPE 270 may access a MOU database 280 and a historical storage level 285 to generate the predicted storage level. For example, the MOU database 280 may include the MPCS 145A-C of each of the MOU transferred into the refinery 110. For example, based on the MPCS 145A-C, the SLPE 270 may determine a composition and weight of each of the MOU 120 transferred into the refinery 110 within a period of time (e.g., between a current time and a time last receiving the refinery status 225). In various implementations, the SLPE 270 may include a data analyzing engine configured to compare data included in the MPCS 145A-C to determine and / or identify whether there is an abnormality during an extraction process.

[0045] As an illustrative example without limitation, the SLPE 270 may add a predicted refined minerals to a historical storage level of the mineral subtracting a quantity of the mineral being transferred out of the refinery 110 indicated by the transfer data 255. For example, the SLPE 270 may generate a warning signal when the predicted storage level is different from the current storage level 260 by, for example, a predetermined threshold (e.g., an absolute threshold, a percentage threshold).

[0046] In some implementations, the PPE 275 may generate a predicted proceed based on the transfer data 255 and a conversion coefficient. For example, the conversion coefficient may be a fixed coefficient. For example, the conversion coefficient may be generated dynamically. For example, the PPE 275 may determine the conversion coefficient based on information retrieved from one or more external sources (e.g., accessed via the Internet). For example, the PPE 275 may generate a warning signal when the predicted proceed is different from the proceed feedback 265 by, for example, a predetermined threshold (e.g., an absolute threshold, a percentage threshold).

[0047] In various implementations, a mineral tracking system (e.g., the SMATS 100) may include a method to automatically and uniquely identifying each mineral output unit (e.g., the MOU 120) of mineral (e.g., using the identifier tag 125). For example, the method may include grading the MOU at each user-defined first plurality of processing stages (e.g., the cooling gate 130, theshipping gate 160). For example, the method may generate the grading as the MPCS 145 A. For example, the method may include packaging one or more MOU into a package (e.g., the parcel 170). For example, the method may include authenticating the package by weight and / or other physical characteristics at a second user-defined plurality of processing stages (e.g., at the one or more predetermined locations 210).

[0048] As an illustrative example, an owner of the extraction site 105 may hire a first operator to operate the extraction site 105 and a second operator to operate the refinery 110. For example, the owner may receive a return based on minerals being transferred out of the refinery 110. For example, the owner may have a need to track minerals extracted from the extraction site 105 from one location to another (e.g., to prevent theft, loss of return).

[0049] In one example, the owner may send human inspectors to inspect the extraction site 105 and the refinery 110. In some cases, it may be impossible to uniquely inspect and trace all MOU produced by the first operator due to time and manpower limitations. As a result, for example, the inspector may produce inspection results that are prone to error. For example, the inspector may select lower quality MOU that generate a lower predicted return. Additionally, the inspector may produce an inspection report that is prone to human errors (e.g., typographical errors, calculation errors).

[0050] In some embodiments, the SMATS 100 may provide a technical solution to a technical problem of tracking a quality and location of each of the MOU uniquely to individually validate an integrity of each MOU at multiple predetermined stages in an extraction-refinery process. For example, the SMATS 100 may apply a unique identifier to each of the MOU. For example, the SMATS 100 may generate an MPCS at multiple predetermined locations. For example, each MPCS may include a quality characteristic (e.g., mineral composition), a weight characteristic, and / or an outlook characteristic (e.g., an image) of each MPCS associated with the unique identifier. In some embodiments, the MPCSs produced at each of the multiple predetermined locations may be independently verified. For example, if the verification failed, the SMATS 100 may generate an error signal to the owner. Various embodiments may advantageously allow the owner of the extraction site to individually trace each extracted output of the extraction site down to the MOU level across the extraction-refinery process.

[0051] FIG. 3 is a block diagram depicting an exemplary end-to-end mineral tracking system (EMTS 300). For example, the EMTS 300 may be embedded in the SMATS 100. For example, the EMTS 300 may be configured to receive the MPCS 145 A, the second MOU physical characteristic struct 145B, and / or the third MPCS 145C, and the MPCS 220. For example, the EMTS 300 may be configured to generate an error signal when one or more of the MOU 120 in the SMATS 100 fails an authentication and / or validation process.100521 In this example, the EMTS 300 includes a processor 305. The processor 305 may, for example, include one or more processing units. The processor 305 is operably coupled to a communication module 310. The communication module 310 may, for example, include wired communication. The communication module 310 may, for example, include wireless communication. In the depicted example, the communication module 310 is operably coupled to a display module 315, a cloud network 320, the PIT 180, the MOU database 280 and the historical storage level 285. For example, the display module 315 may receive a display signal from the EMTS 300 to display status (e.g., location, image, composition) of one or more of the MOU 120. In some examples, the display signal may include a refinery status 225 received from the refinery 110.

[0053] The cloud network 320, for example, may include a public network (e.g., the Internet). In some embodiments, the cloud network 320 may include a private network. For example, the cloud network 320 may include a private network configured to provide proprietary information of prices in precious metals.

[0054] The processor 305 is operably coupled to a memory module 325. The memory module 325 may, for example, include one or more memory modules (e.g., random-access memory (RAM)). The processor 305 includes a storage module 330. The storage module 330 may, for example, include one or more storage modules (e.g., non-volatile memory). In the depicted example, the storage module 330 includes the MLTE 230, the DCE 235, the SLPE 270, the PPE 275, and a document processing engine (DPE 335). For example, the DPE 335 may be configured to receive various documents from the refinery 110 and / or the extraction site 105.

[0055] In some implementations, the DPE 335 may include an OCR module to identify text within a document. For example, the DPE 335 may include an artificial intelligence module to identify text and images in various documents. In some embodiments, the DPE 335 may receive a shipping document (e.g., a packing list, a bill of lading) from the extraction site 105. For example, the DPE 335 may identify a quantity of shipment from the extraction site 105 based on the shipping document. For example, the DPE 335 may update the MOU database 280 based on the shipping document. In some embodiments, the DPE 335 may be configured to process a sales document received from the refinery 110. For example, based on the sales document, the DPE 335 may update the historical storage level 285.

[0056] The processor 305 is further operably coupled to a data store 340. The data store 340 includes an output estimation model 345 , a proceed prediction model 350, and an error threshold(s) 355. For example, the DCE 235 may retrieve the threshold(s) 355 while comparing two MPCSs. For example, the DCE 235 may generate an error signal when a difference between the two MPCSs is greater than the threshold(s) 355. The SLPE 270, for example, may apply a composition andweight of each of the MOU 120 transferred to the refinery 110 to the output estimation model 345 to generate the predicted stock level. For example, the output estimation model 345 may include a yield ratio between an input of a mineral from the MOU and an output of the mineral. For example, the PPE 275 may apply the proceed prediction model 350 to the refinery status 225 to generate a predicted proceed. For example, the PPE 275 may generate an error signal when a difference between the predicted proceed and the proceed feedback 265 is larger than a threshold defined in the threshold(s) 355.

[0057] FIG. 4 is a flowchart illustrating an exemplary extracting site mineral integrity tracking method 400. For example, the method 400 may be performed by SMATS 100 at an extraction site as described in FIG. 1. In this example, the method 400 begins in step 405 when a first unique identifying tag is applied to a mineral output unit (MOU). For example, the first unique identifying tag may be a barcode, RFID tag, or QR code applied to the MOU 120.

[0058] In step 410, a first mineral physical characteristic struct (MPCS) associated with the first unique identifying tag of the MOU is generated. For example, the MPCS 145A may be generated by the MCDD 140 at the cooling gate 130. For example, the MPCS 145A may include physical characteristics such as weight, size, and mineral composition data of the MOU 120, detected by a first mineral characteristics detection device. In some examples, the first MPCS of the MOU may be generated based on a detection signal generated from a first MCDD. For example, the first mineral characteristics detection device may be configured to detect physical characteristics of the MOU. For example, the physical characteristics comprises mineral composition data and at least one of weight data and size data of the MOU.

[0059] In a decision point 415, it is determined whether the MOU is approaching a validation location. For example, the SMATS 100 may detect whether the MOU 120 is near the packing room 165 based on a signal transmitted from the identifier tag 125. If the MOU is not approaching a validation location, a location signal of the MOU is generated in step 420.

[0060] If the MOU is approaching a validation location, a second MPCS associated with the first unique identifying tag of the MOU is generated in step 425. For example, the second MPCS 145B may be generated when the MOU passes through a second MCDD at or before the shipping gate 160. In some examples, the second MPCS 145B may include mineral composition data and at least one of weight data and size data in response to receiving a signal indicating that the first unique identifying tag is within a proximity to a second predetermined location of the extraction process including a second MCDD.

[0061] In a decision point 430, it is determined whether the difference between the first MPCS and the second MPCS is below a predefined threshold. For example, the DCE 235 may compare the first MPCS and the second MPCS. If the difference between the first MPCS and the secondMPCS is below the threshold, the MOU is transferred into a packing room to generate a package in step 435. For example, one or more of the MOU 120 may be transferred to the packing room 165 to be combined into the parcel 170. For example, the MOU 120 may be packed for shipment to the refinery 110 in the packing room 165.

[0062] Next, a third MOU physical characteristic struct is integrated to a MOU package struct in step 440. For example, the SMATS 100 may generate the third MPCS 145C. For example, the SMATS 100 may generate a weight for each of the MOU to be included in the parcel 170. For example, the SMATS 100 may generate the parcel profile 185 by aggregating all of the weight of the MOU within the parcel 170. At a destination point, in step 445, the package is processed by comparing a weight of the package and the weight attribute in the MOU package struct, and the method 400 ends.

[0063] If, at the decision point 430, the difference between the first MPCS and the second MPCS exceeds the threshold, an error signal is generated in step 450. After the error signal is generated, in step 455, the MOU is transferred into an investigation room for further inspection, and the method 400 ends.

[0064] FIG. 5 is a flowchart illustrating an exemplary refinery site mineral integrity tracking method 500. For example, the method 500 may be performed by PPE 275 and / or the PPE 275 of the SMATS 100. In this example, the method 500 begins when refinery data (e.g., the refinery status 225) is received from a refinery site, including a current storage level (CSL) of a mineral type, transfer data of the mineral type, and proceed feedback in a time period based on the transfer data, in step 505. For example, the SMATS 100 may receive the refinery status 225 from the RSGU 250. In some implementations, the refinery status 225 may include the transfer data 255, the current storage level 260, and the proceed feedback 265.

[0065] In step 510, an expected storage level (ESL) of the mineral type is generated as a function of the refinery data. For example, the SLPE 270 may generate an expected storage level of the refinery 110 based on the transfer data 255, and the third MPCS 145C that is associated with each MOU transferred into the refinery 110 and that is stored in the MOU database 280.

[0066] In decision point 515, it is determined whether the difference between the ESL and the CSL is less than a predefined threshold. For example, the SLPE 270 may determine whether the current storage level 260 reported from the refinery 110 is less than the predicted storage level generated in the step 510.

[0067] If the difference between the ESL and the CSL is above the threshold, an error signal is generated in step 520, and the method 500 ends. For example, the SMATS 100 may generate a signal to a third party computing device to indicate a discrepancy that may need further investigation.|0068| If the difference between the ESL and the CSL is below the threshold, in step 525, an expected proceed of the refinery is generated as a function of the refinery data. For example, the PPE 275 may generate the expected proceeds as a function of the refinery status 225 and, for example, a market price of the material type during a period of time.

[0069] In decision point 530, it is determined whether the difference between the expected proceed and the proceed feedback is below a predefined threshold. If the difference between the expected proceed and the proceed feedback exceeds the threshold, the method 500 proceeds to the step 520. If the difference does not exceed the threshold, the method 500 ends. For example, the method 500 may optionally generate a pass signal if the difference does not exceed the threshold, indicating that the data is consistent and accurate.

[0070] Although various embodiments have been described with reference to the figures, other embodiments are possible. For example, the SMATS 100 may include two locations configured to access physical attributes of the MOU 120. In some embodiments, one or more intermediate locations may be included in the extraction site 105 to cross-check the MPCS 145 A of each of the MOU 120 before the MOU 120 is packed for shipment.

[0071] In some embodiments, the extraction site 105 may include a conveyor belt system for transporting the MOU(s) 120 through various stages of the extraction and validation process. For example, the conveyor belt system may transport raw gold bars (the MOUs) sequentially along different processing checkpoints of the extraction site 105.

[0072] The conveyor belt system, for example, may include multiple checkpoints. In some implementations, each of the checkpoints may include the MCDD 140 configured to physically detect, validate, and / or test the MOU 120. At these checkpoints, the MOU may, for example, be temporarily stopped. For example, the MCDD 140 may perform a series of assessments to detect physical attributes of the MOU 120.

[0073] In some embodiments, the MCDD 140 may, at each of the checkpoints, generate the MPCS 145A within one minute. For example, the MPCS 145A may include data on the weight, composition, purity, and other relevant attributes of the gold bar. Once the MPCS 145 A is generated, the SMATS 100 may determine whether the MOU meets the predefined quality criteria (e.g., one or more predefined variation thresholds). If the MOU passes the validation, in some implementations, the SMATS 100 may transmit a signal to the conveyor belt system to transfer the MOU to a next stage of the extraction process. If the gold bar fails the validation, for example, the SMATS 100 may transmit a fail signal to the conveyor belt system to transfer the MOU (e.g., to another designated area) for further investigation and / or inspection.

[0074] Various embodiments may advantageously provide an automatic and quick process for validating and tracking MOU (e.g., raw gold bars) without holding up an on-going extractionprocess. By incorporating checkpoints with MCDD 140 along the conveyor belt, in various examples, the SMATS 100 may advantageously authenticate each MOU to be individually assessed and / or validated in a timely manner. In some cases, the SMATS 100 may advantageously improve an efficiency and / or reliability of the mineral extraction process.

[0075] Although an exemplary system has been described with reference to FIGS. 1-2, other implementations may be deployed in other industrial, scientific, medical, commercial, and / or residential applications.

[0076] In various embodiments, some bypass circuits implementations may be controlled in response to signals from analog or digital components, which may be discrete, integrated, or a combination of each. Some embodiments may include programmed, programmable devices, or some combination thereof (e.g., PLAs, PLDs, ASICs, microcontroller, microprocessor), and may include one or more data stores (e.g., cell, register, block, page) that provide single or multi-level digital data storage capability, and which may be volatile, non-volatile, or some combination thereof. Some control functions may be implemented in hardware, software, firmware, or a combination of any of them.

[0077] Computer program products may contain a set of instructions that, when executed by a processor device, cause the processor to perform prescribed functions. These functions may be performed in conjunction with controlled devices in operable communication with the processor. Computer program products, which may include software, may be stored in a data store tangibly embedded on a storage medium, such as an electronic, magnetic, or rotating storage device, and may be fixed or removable (e.g., hard disk, floppy disk, thumb drive, CD, DVD).

[0078] Although an example of a system, which may be portable, has been described with reference to the above figures, other implementations may be deployed in other processing applications, such as desktop and networked environments.

[0079] Temporary auxiliary energy inputs may be received, for example, from chargeable or single use batteries, which may enable use in portable or remote applications. Some embodiments may operate with other DC voltage sources, such as batteries, for example. Alternating current (AC) inputs, which may be provided, for example from a 50 / 60 Hz power port, or from a portable electric generator, may be received via a rectifier and appropriate scaling. Provision for AC (e.g., sine wave, square wave, triangular wave) inputs may include a line frequency transformer to provide voltage step-up, voltage step-down, and / or isolation.

[0080] Although particular features of an architecture have been described, other features may be incorporated to improve performance. For example, caching (e.g., LI, L2, . . .) techniques may be used. Random access memory may be included, for example, to provide scratch pad memory and or to load executable code or parameter profile stored for use during runtime operations. Otherhardware and software may be provided to perform operations, such as network or other communications using one or more protocols, wireless (e.g., infrared) communications, stored operational energy and power supplies (e.g., batteries), switching and / or linear power supply circuits, software maintenance (e.g., self-test, upgrades), and the like. One or more communication interfaces may be provided in support of data storage and related operations.

[0081] Some systems may be implemented as a computer system that can be used with various implementations. For example, various implementations may include digital circuitry, analog circuitry, computer hardware, firmware, software, or combinations thereof. Apparatus can be implemented in a computer program product tangibly embodied in an profile carrier, e.g., in a machine-readable storage device, for execution by a programmable processor; and methods can be performed by a programmable processor executing a program of instructions to perform functions of various embodiments by operating on input data and generating an output. Various embodiments can be implemented advantageously in one or more computer programs that are executable on a programmable system including at least one programmable processor coupled to receive data and instructions from, and to transmit data and instructions to, a data storage system, at least one input device, and / or at least one output device. A computer program is a set of instructions that can be used, directly or indirectly, in a computer to perform a certain activity or bring about a certain result. A computer program can be written in any form of programming language, including compiled or interpreted languages, and it can be deployed in any form, including as a stand-alone program or as a module, component, subroutine, or other unit suitable for use in a computing environment.

[0082] Suitable processors for the execution of a program of instructions include, by way of example, both general and special purpose microprocessors, which may include a single processor or one of multiple processors of any kind of computer. Generally, a processor will receive instructions and data from a read-only memory or a random-access memory or both. The essential elements of a computer are a processor for executing instructions and one or more memories for storing instructions and data. Generally, a computer will also include, or be operatively coupled to communicate with, one or more mass storage devices for storing data files; such devices include magnetic disks, such as internal hard disks and removable disks; magneto-optical disks; and optical disks. Storage devices suitable for tangibly embodying computer program instructions and data include all forms of non-volatile memory, including, by way of example, semiconductor memory devices, such as EPROM, EEPROM, and flash memory devices; magnetic disks, such as internal hard disks and removable disks; magneto-optical disks; and CD-ROM and DVD-ROM disks. The processor and the memory can be supplemented by, or incorporated in, ASICs (applicationspecific integrated circuits).|0083 | In some implementations, each system may be programmed with the same or similar profile and / or initialized with a substantially identical profile stored in volatile and / or non-volatile memory. For example, one data interface may be configured to perform auto configuration, auto download, and / or auto update functions when coupled to an appropriate host device, such as a desktop computer or a server.

[0084] In some implementations, one or more user-interface features may be custom configured to perform specific functions. Various embodiments may be implemented in a computer system that includes a graphical user interface and / or an Internet browser. To provide for interaction with a user, some implementations may be implemented on a computer having a display device. The display device may, for example, include an LED (light-emitting diode) display. In some implementations, a display device may, for example, include a CRT (cathode ray tube). In some implementations, a display device may include, for example, an LCD (liquid crystal display). A display device (e.g., monitor) may, for example, be used for displaying profile to the user. Some implementations may, for example, include a keyboard and / or pointing device (e.g., mouse, trackpad, trackball, joystick), such as by which the user can provide input to the computer.

[0085] In various implementations, the system may communicate using suitable communication methods, equipment, and techniques. For example, the system may communicate with compatible devices (e.g., devices capable of transferring data to and / or from the system) using point-to-point communication in which a message is transported directly from the source to the receiver over a dedicated physical link (e.g., fiber optic link, point-to-point wiring, daisy-chain). The components of the system may exchange profile by any form or medium of analog or digital data communication, including packet-based messages on a communication network. Examples of communication networks include, e.g., a LAN (local area network), a WAN (wide area network), MAN (metropolitan area network), wireless and / or optical networks, the computers and networks forming the Internet, or some combination thereof. Other implementations may transport messages by broadcasting to all or substantially all devices that are coupled together by a communication network, for example, by using omni-directional radio frequency (RF) signals. Still other implementations may transport messages characterized by high directivity, such as RF signals transmitted using directional (i.e., narrow beam) antennas or infrared signals that may optionally be used with focusing optics. Still other implementations are possible using appropriate interfaces and protocols such as, by way of example and not intended to be limiting, USB 2.0, Firewire, ATA / IDE, RS-232, RS-422, RS-485, 802.11 a / b / g, Wi-Fi, Ethernet, IrDA, FDDI (fiber distributed data interface), token-ring networks, multiplexing techniques based on frequency, time, or code division, or some combination thereof. Some implementations may optionally incorporatefeatures such as error checking and correction (ECC) for data integrity, or security measures, such as encryption (e.g., WEP) and password protection.

[0086] In various embodiments, the computer system may include Internet of Things (loT) devices. loT devices may include objects embedded with electronics, software, sensors, actuators, and network connectivity which enable these objects to collect and exchange data. loT devices may be in-use with wired or wireless devices by sending data through an interface to another device. loT devices may collect useful data and then autonomously flow the data between other devices.

[0087] Various examples of modules may be implemented using circuitry, including various electronic hardware. By way of example and not limitation, the hardware may include transistors, resistors, capacitors, switches, integrated circuits, other modules, or some combination thereof. In various examples, the modules may include analog logic, digital logic, discrete components, traces and / or memory circuits fabricated on a silicon substrate including various integrated circuits (e.g., FPGAs, ASICs), or some combination thereof. In some embodiments, the module(s) may involve execution of preprogrammed instructions, software executed by a processor, or some combination thereof. For example, various modules may involve both hardware and software.

[0088] In an illustrative aspect, a system may include a data store including a program of instructions. For example, the system may include a processor operably coupled to the data store. For example, when the processor executes the program of instructions, the processor causes operations to be performed to automatically track a physical location and process an integrity of extracted mineral output extracted from an extraction site.

[0089] For example, the operations may include, at a first predetermined location of an extraction process, for each mineral output unit (MOU) of mineral extracted from the extraction site, apply a first unique identifying tag configured to uniquely identifying the MOU. For example, the operations may include generate a first MOU physical characteristic struct of the MOU based on a detection signal generated from a first mineral characteristics detection device.

[0090] For example, the first mineral characteristics detection device may be configured to detect physical characteristics of the MOU. For example, the physical characteristics may include mineral composition data of the MOU and at least one of weight data and size data of the MOU.

[0091] For example, the operations may include, in response to receiving a signal indicating that the first unique identifying tag may be within a proximity to a second predetermined location of the extraction process may include a second mineral characteristics detection device, generate a second MOU physical characteristic struct based on a second detection signal generated from the second mineral characteristics detection device. For example, the second MOU physicalcharacteristic struct may include the mineral composition data and at least one of the weight data and the size data.

[0092] For example, the operations may include compare the second MOU physical characteristic struct with respect to the first MOU physical characteristic struct to generate a unity signal corresponding to the MOU. For example, the operations may include, when a difference between the first and the second MOU physical characteristic structs may be within a predetermined threshold, integrate a third MOU physical characteristic struct to a MOU package struct. For example, the MOU package struct may include a weight attribute may include the MOU integrated and associated to a package to be transported out of the extraction site.

[0093] For example, the operations may include, at a destination point, process the package by comparing an actual weight of the package and the weight attribute of the MOU package struct associated with the package. In some implementations, the system may include one or more of the following features:• For example, the first predetermined location of the extraction process may include a first gate of the extraction site, and the second predetermined location may include a second gate. For example, the MOU may be transferred through the second gate into a quality intact room when the first and the second MOU physical characteristic structs may be within the predetermined threshold.• For example, the first unique identifying tag may include a barcode tag, and the second mineral characteristics detection device may include a barcode scanner.• For example, after the MOU package struct may be generated, apply a second unique identifying tag to the package. For example, the second unique identifying tag may include a global positioning system (GPS) tag. For example, the package’s location may be imminently retrievable between the extraction site to the destination point.• For example, the first and the second mineral characteristics detection devices each may include an X-ray fluorescence spectroscopy device.• For example, the operations further may include, at a predetermined time period, retrieve from the data store a mineral refinery data from a mineral refinery of the MOU. For example, the mineral refinery data may include (1) a current storage level of each mineral type at the mineral refinery, (2) a transfer data including an output data that may include a total weight of extracted mineral each mineral type being transferred out of the mineral refinery during the predetermined time period, and an input data may include a total weight of the MOU being received from the extraction site during the predetermined time period, and / or (3) a proceed feedback resulting based on a quantity of the output data. For example, the operations may include generate an expected storage level of each extracted mineralunit as a function of the transfer data, and a historical storage level at the mineral refinery. For example, the operations may include an expected proceeds as a function of the output data and a predefined conversion value per weight unit of each mineral type. For example, the operations may include generate an error signal when a difference between the expected storage level and the current storage level in the mineral refinery data may be greater than a threshold, or a difference between the expected proceeds and the proceed feedback may be greater than the threshold.

[0094] In an illustrative aspect, a computer-implemented method performed by at least one processor to automatically track a physical location and process an integrity of extracted mineral output extracted from an extraction site, the method may include, at a first predetermined location of an extraction process, for each mineral output unit (MOU) of mineral extracted from the extraction site. For example, the method may include apply a first unique identifying tag configured to uniquely identify the MOU. For example, For example, the method may include generate a first MOU physical characteristic struct of the MOU based on a detection signal generated from a first mineral characteristics detection device. For example, the first mineral characteristics detection device may be configured to detect physical characteristics of the MOU. For example, the physical characteristics may include mineral composition data of the MOU and at least one of weight data and size data of the MOU.

[0095] For example, the method may include, in response to receiving a signal indicating that the first unique identifying tag may be within a proximity to a second predetermined location of the extraction process that may include a second mineral characteristics detection device, generate a second MOU physical characteristic struct based on a second detection signal generated from the second mineral characteristics detection device. For example, the second MOU physical characteristic struct may include the mineral composition data and at least one of the weight data and the size data.

[0096] For example, the method may include compare the second MOU physical characteristic struct with respect to the first MOU physical characteristic struct to generate a unity signal corresponding to the MOU. the method may include, when a difference between the first and the second MOU physical characteristic structs may be within a predetermined threshold, integrate a third MOU physical characteristic struct to a MOU package struct. For example, the MOU package struct may include a weight attribute may include the MOU integrated and associated to a package to be transported out of the extraction site.

[0097] For example, the method may include, at a destination point, process the package by comparing an actual weight of the package and the weight attribute of the MOU package structassociated with the package. In some implementations, the computer-implemented method may include one or more of the following features:• For example, the first predetermined location of the extraction process may include a first gate of the extraction site, and the second predetermined location may include a second gate. For example, the MOU may be transfer through the second gate into a quality intact room when the first and the second MOU physical characteristic structs within the predetermined threshold.• For example, the first unique identifying tag may include a barcode tag, and the second mineral characteristics detection device may include a barcode scanner.• For example,, after the MOU package struct may be generated, apply a second unique identifying tag to the package. For example, the second unique identifying tag may include a global positioning system (GPS) tag. For example, the package’s location may be imminently retrievable between the extraction site to the destination point.• For example, the first and the second mineral characteristics detection devices each may include an X-ray fluorescence spectroscopy device.• For example, the method may include transfer the package to a mineral refinery configured to transform the MOU into refined unit of the extracted minerals.• For example, the method may include, at a predetermined time period, receive a mineral refinery data from a mineral refinery of the MOU. For example, the mineral refinery data may include:(1) a current storage level of each mineral type at the mineral refinery;(2) a transfer data that may include an output data may include a total weight of extracted mineral each mineral type being transferred out of the mineral refinery during the predetermined time period, and, an input data may include a total weight of the MOU being received from the extraction site during the predetermined time period; and,(3) a proceed feedback resulting based on a quantity of the output data;For example, the method may include generate an expected storage level of each extracted mineral unit as a function of the transfer data, and a historical storage level at the mineral refinery. For example, the method may include an expected proceeds as a function of the output data and a predefined conversion value per weight unit of each mineral type. For example, the method may include generate an error signal when a difference between the expected storage level and the current storage level in the mineral refinery data may be greater than a threshold, or a difference between the expected proceeds and the proceed feedback may be greater than the threshold.[00981 In an illustrative aspect, a computer program product may include a program of instructions tangibly embodied on a computer readable medium wherein when the instructions may beexecuted on a processor , the processor causes operations to be performed to automatically track a physical location and process an integrity of the extracted mineral output extracted from an extraction site, the operations may include, at a first predetermined location of an extraction process, for each mineral output unit (MOU) of mineral extracted from the extraction site, apply a first unique identifying tag configured to uniquely identifying the MOU.

[0099] For example, the operations may include generate a first MOU physical characteristic struct of the MOU based on a detection signal generated from a first mineral characteristics detection device. For example, the first mineral characteristics detection device may be configured to detect physical characteristics of the MOU. For example, the physical characteristics may include mineral composition data of the MOU and at least one of weight data and size data of the MOU.

[0100] For example, the operations may include in response to receiving a signal indicating that the first unique identifying tag may be within a proximity to a second predetermined location of the extraction process may include a second mineral characteristics detection device, generate a second MOU physical characteristic struct based on a second detection signal generated from the second mineral characteristics detection device. For example, the second MOU physical characteristic struct may include the mineral composition data and at least one of the weight data and the size data.

[0101] For example, the operations may include compare the second MOU physical characteristic struct with respect to the first MOU physical characteristic struct to generate a unity signal corresponding to the MOU. For example, the operations may include, when a difference between the first and the second MOU physical characteristic streets may be within a predetermined threshold, integrate a third MOU physical characteristic struct to a MOU package struct. For example, the MOU package struct may include a weight attribute may include the MOU integrated and associated to a package to be transported out of the extraction site.

[0102] For example, the operations may include, at a destination point, process the package by comparing an actual weight of the package and the weight attribute of the MOU package struct associated with the package. In some implementations, the computer program product may include one or more of the following features:• For example, the first predetermined location of the extraction process may include a first gate of the extraction site, and the second predetermined location may include a second gate. For example, the MOU may be transferred through the second gate into a quality intact room when the first and the second MOU physical characteristic streets may be within the predetermined threshold.• For example, the first unique identifying tag may include a bar code tag, and the second mineral characteristics detection device may include a bar code scanner.• For example, after the MOU package struct may be generated, apply a second unique identifying tag to the package. For example, the second unique identifying tag may include a global positioning system (GPS) tag, such that the package’ s location may be imminently retrievable between the extraction site to the destination point.• For example, the first and the second mineral characteristics detection devices each may include an X-ray fluorescence spectroscopy device.• For example, the operations further may include transfer the package to a mineral refinery configured to transform the MOU into refined unit of the extracted minerals.• For example, the operations further may include, at a predetermined time period, receive a mineral refinery data from a mineral refinery of the MOU. For example, the mineral refinery data may include (1) a current storage level of each mineral type at the mineral refinery, (2) a transfer data may include an output data may include a total weight of extracted mineral each mineral type being transferred out of the mineral refinery during the predetermined time period, and an input data may include a total weight of the MOU being received from the extraction site during the predetermined time period, and (3) a proceed feedback resulting based on a quantity of the output data. For example, the operations may include generate an expected storage level of each extracted mineral unit as a function of the transfer data, and a historical storage level at the mineral refinery, and an expected proceeds as a function of the output data and a predefined conversion value per weight unit of each mineral type. For example, the operations may include generate an error signal when a difference between the expected storage level and the current storage level in the mineral refinery data may be greater than a threshold, or a difference between the expected proceeds and the proceed feedback may be greater than the threshold.

[0103] In some implementations, the system may include the computer program product and some or all or none of the listed features. In some implementations, the system may include the computer- implemented method and some or all or none of the listed features.

[0104] For example, the computer-implemented method may include the system and some or all or none of the listed features. In some implementations, the computer-implemented method may include the computer program product and some or all or none of the listed features.

[0105] In some implementations, the computer program product may include the system and some or all or none of the listed features. In some implementations, the computer program product may include the computer-implemented method and some or all or none of the listed features.

[0106] A number of implementations have been described. Nevertheless, it will be understood that various modifications may be made. For example, advantageous results may be achieved if the steps of the disclosed techniques were performed in a different sequence, or if components of thedisclosed systems were combined in a different manner, or if the components were supplemented with other components. Accordingly, other implementations are contemplated within the scope of the following claims.

Claims

CLAIMSWhat is claimed is:

1. A system comprising: a data store (330) comprising a program of instructions; and, a processor (305) operably coupled to the data store such that, when the processor executes the program of instructions, the processor causes operations to be performed to automatically track a physical location and process an integrity of extracted mineral output extracted from an extraction site (105), the operations comprising: at a first predetermined location (130) of an extraction process, for each mineral output unit (MOU) (120) of mineral extracted from the extraction site, apply a first unique identifying tag (125) configured to uniquely identifying theMOU (405), and, generate a first MOU physical characteristic struct (145A) of the MOU based on a detection signal generated from a first mineral characteristics detection device (140), wherein the first mineral characteristics detection device is configured to detect physical characteristics of the MOU (410), wherein the physical characteristics comprises mineral composition data of the MOU and at least one of weight data and size data of the MOU; in response to receiving a signal indicating that the first unique identifying tag is within a proximity to a second predetermined location (160) of the extraction process comprising a second mineral characteristics detection device, generate a second MOU physical characteristic struct (145B) based on a second detection signal generated from the second mineral characteristics detection device (425), wherein the second MOU physical characteristic struct comprises the mineral composition data and at least one of the weight data and the size data; compare the second MOU physical characteristic struct with respect to the first MOU physical characteristic struct to generate a unity signal corresponding to the MOU (430);when a difference between the first and the second MOU physical characteristic structs is within a predetermined threshold, integrate a third MOU physical characteristic struct (145C) to a MOU package struct (440), wherein the MOU package struct (180) comprises a weight attribute comprising the MOU integrated and associated to a package to be transported out of the extraction site; and, at a destination point, process the package by comparing an actual weight of the package and the weight attribute of the MOU package struct associated with the package (445).

2. The system of claim 1, wherein the first predetermined location of the extraction process comprises a first gate of the extraction site, and the second predetermined location comprises a second gate, wherein the MOU is transferred through the second gate into a quality intact room when the first and the second MOU physical characteristic structs are within the predetermined threshold.

3. The system of claim 1, wherein the first unique identifying tag comprises a barcode tag, and the second mineral characteristics detection device comprises a barcode scanner.

4. The system of claim 1, wherein, after the MOU package struct is generated, apply a second unique identifying tag to the package, wherein the second unique identifying tag comprises a global positioning system (GPS) tag, such that the package’s location is imminently retrievable between the extraction site to the destination point.

5. The system of claim 1, wherein the first and the second mineral characteristics detection devices each comprise an X-ray fluorescence spectroscopy device.

6. The system of claim 1, wherein the operations further comprise: at a predetermined time period, retrieve from the data store a mineral refinery data from a mineral refinery of the MOU, wherein the mineral refinery data comprises:(1) a current storage level of each mineral type at the mineral refinery;(2) a transfer data comprising: an output data comprises a total weight of extracted mineral each mineral type being transferred out of the mineral refinery during the predetermined time period; and, an input data comprises a total weight of the MOU being received from the extraction site during the predetermined time period; and,(3) a proceed feedback resulting based on a quantity of the output data; generate: an expected storage level of each extracted mineral unit as a function of the transfer data, and a historical storage level at the mineral refinery; and, an expected proceeds as a function of the output data and a predefined conversion value per weight unit of each mineral type; and, generate an error signal when a difference between the expected storage level and the current storage level in the mineral refinery data is greater than a threshold, or a difference between the expected proceeds and the proceed feedback is greater than the threshold.

7. A computer-implemented method performed by at least one processor to automatically track a physical location and process an integrity of extracted mineral output extracted from an extraction site, the method comprising: at a first predetermined location of an extraction process, for each mineral output unit (MOU) of mineral extracted from the extraction site, apply a first unique identifying tag configured to uniquely identifying the MOU (405), and, generate a first MOU physical characteristic struct of the MOU based on a detection signal generated from a first mineral characteristics detection device, wherein the first mineral characteristics detection device is configured to detect physical characteristics of the MOU (410), wherein the physical characteristics comprises mineral composition data of the MOU and at least one of weight data and size data of the MOU; in response to receiving a signal indicating that the first unique identifying tag is within a proximity to a second predetermined location of the extraction process comprising a second mineral characteristics detection device, generate a second MOU physical characteristic struct based on a second detection signal generated from the second mineral characteristics detection device (425), wherein the second MOU physical characteristic struct comprises the mineral composition data and at least one of the weight data and the size data; compare the second MOU physical characteristic struct with respect to the first MOU physical characteristic struct to generate a unity signal corresponding to the MOU (430); when a difference between the first and the second MOU physical characteristic structs is within a predetermined threshold, integrate a third MOU physical characteristic struct to a MOU package struct (440), wherein the MOU package struct comprises a weight attribute comprising the MOU integrated and associated to a package to be transported out of the extraction site; and, at a destination point, process the package by comparing an actual weight of the package and the weight attribute of the MOU package struct associated with the package (445).

8. The computer-implemented method of claim 7, wherein the first predetermined location of the extraction process comprises a first gate of the extraction site, and the second predetermined location comprises a second gate, wherein the MOU is transferred through the second gate into a quality intact room when the first and the second MOU physical characteristic streets within the predetermined threshold.

9. The computer-implemented method of claim 7, wherein the first unique identifying tag comprises a barcode tag, and the second mineral characteristics detection device comprises a barcode scanner.

10. The computer-implemented method of claim 7, wherein, after the MOU package struct is generated, apply a second unique identifying tag to the package, wherein the second unique identifying tag comprises a global positioning system (GPS) tag, such that the package’s location is imminently retrievable between the extraction site to the destination point.

11. The computer-implemented method of claim 7, wherein the first and the second mineral characteristics detection devices each comprises an X-ray fluorescence spectroscopy device.

12. The computer-implemented method of claim 7, further comprise transfer the package to a mineral refinery configured to transform the MOU into refined unit of the extracted minerals.

13. The computer-implemented method of claim 7, further comprise: at a predetermined time period, receive a mineral refinery data from a mineral refinery of the MOU, wherein the mineral refinery data comprises:(1) a current storage level of each mineral type at the mineral refinery;(2) a transfer data comprising: an output data comprises a total weight of extracted mineral each mineral type being transferred out of the mineral refinery during the predetermined time period; and, an input data comprises a total weight of the MOU being received from the extraction site during the predetermined time period; and,(3) a proceed feedback resulting based on a quantity of the output data; generate: an expected storage level of each extracted mineral unit as a function of the transfer data, and a historical storage level at the mineral refinery; and, an expected proceeds as a function of the output data and a predefined conversion value per weight unit of each mineral type; and, generate an error signal when a difference between the expected storage level and the current storage level in the mineral refinery data is greater than a threshold, or a difference between the expected proceeds and the proceed feedback is greater than the threshold.

14. .A computer program product comprising: a program of instructions tangibly embodied on a computer readable medium (330) wherein when the instructions are executed on a processor (305), the processor causes operations to be performed to automatically track a physical location and process an integrity of the extracted mineral output extracted from an extraction site, the operations comprising: at a first predetermined location of an extraction process, for each mineral output unit (MOU) of mineral extracted from the extraction site, apply a first unique identifying tag configured to uniquely identifying the MOU (405), and, generate a first MOU physical characteristic struct of the MOU based on a detection signal generated from a first mineral characteristics detection device, wherein the first mineral characteristics detection device is configured to detect physical characteristics of the MOU (410), wherein the physical characteristics comprises mineral composition data of the MOU and at least one of weight data and size data of the MOU; in response to receiving a signal indicating that the first unique identifying tag is within a proximity to a second predetermined location of the extraction process comprising a second mineral characteristics detection device, generate a second MOU physical characteristic struct based on a second detection signal generated from the second mineral characteristics detection device (425), wherein the second MOU physical characteristic struct comprises the mineral composition data and at least one of the weight data and the size data; compare the second MOU physical characteristic struct with respect to the first MOU physical characteristic struct to generate a unity signal corresponding to the MOU (430); when a difference between the first and the second MOU physical characteristic streets is within a predetermined threshold, integrate a third MOU physical characteristic struct to a MOU package struct (440), wherein the MOU package struct comprises a weight attribute comprising the MOU integrated and associated to a package to be transported out of the extraction site; and,at a destination point, process the package by comparing an actual weight of the package and the weight attribute of the MOU package struct associated with the package (445).

15. The computer program product of claim 14, wherein the first predetermined location of the extraction process comprises a first gate of the extraction site, and the second predetermined location comprises a second gate, wherein the MOU is transferred through the second gate into a quality intact room when the first and the second MOU physical characteristic structs are within the predetermined threshold.

16. The computer program product of claim 14, wherein the first unique identifying tag comprises a bar code tag, and the second mineral characteristics detection device comprises a bar code scanner.

17. The computer program product of claim 14, wherein, after the MOU package struct is generated, apply a second unique identifying tag to the package, wherein the second unique identifying tag comprises a global positioning system (GPS) tag, such that the package’s location is imminently retrievable between the extraction site to the destination point.

18. The computer program product of claim 14, wherein the first and the second mineral characteristics detection devices each comprises an X-ray fluorescence spectroscopy device.

19. The computer program product of claim 14, wherein the operations further comprise transfer the package to a mineral refinery configured to transform the MOU into refined unit of the extracted minerals.

20. The computer program product of claim 19, wherein the operations further comprise: at a predetermined time period, receive a mineral refinery data from a mineral refinery of the MOU, wherein the mineral refinery data comprises:(1) a current storage level of each mineral type at the mineral refinery;(2) a transfer data comprising: an output data comprises a total weight of extracted mineral each mineral type being transferred out of the mineral refinery during the predetermined time period; and, an input data comprises a total weight of the MOU being received from the extraction site during the predetermined time period; and,(3) a proceed feedback resulting based on a quantity of the output data; generate: an expected storage level of each extracted mineral unit as a function of the transfer data, and a historical storage level at the mineral refinery; and, an expected proceeds as a function of the output data and a predefined conversion value per weight unit of each mineral type; and, generate an error signal when a difference between the expected storage level and the current storage level in the mineral refinery data is greater than a threshold, or a difference between the expected proceeds and the proceed feedback is greater than the threshold.

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