Description:AUTOMATED DETECTION OF FRESHNESS OF RICE

FIELD OF THE PRESENT DISCLOSURE
[0001] The present invention relates generally to the field of rice quality assessment, and more specifically, to apparatuses and methods for automated detection of freshness of rice based on colorimetric evaluations and image processing techniques.

BACKGROUND
[0002] In rice procurement, ensuring quality and freshness of milled rice is of paramount importance. Rice, being a staple food for a significant portion of the global population, necessitates rigorous quality control to ensure that consumers receive fresh and unadulterated grains. Conventionally, the assessment of rice freshness has been achieved through manual inspections and rudimentary chemical tests. One such prevalent method is the Mixed Indicator Method (MIM), which employs a combination of chemical indicators to discern the age or freshness of milled rice. These conventional methods for detection of freshness of rice have multiple challenges and limitations. These methods, while prevalent, are labour-intensive and often lack the precision and consistency required for large-scale rice processing operations. For instance, manual inspections are susceptible to human error, fatigue, and individual bias. The subjectivity inherent in such inspections can lead to inconsistent assessments, making it challenging to maintain a uniform quality standard across batches. Furthermore, manual methods are time-consuming, hindering the efficiency of rice processing units and delaying the time-to-market for the processed rice.
[0003] To address the challenges and limitations of manual inspections, some technological solutions have been introduced. These range from simple colour detection tools to sample preparation systems. While these technologies have introduced some improvements in enhancing the accuracy of rice freshness detection, they often require specialized training, intricate calibration procedures, and can be expensive to implement on a large scale. Moreover, even with the integration of such technological tools, several challenges persist. Many of the current solutions are not fully automated, still requiring significant human intervention. Additionally, these systems might not account for potential adulterants or contaminants that can artificially alter the perceived freshness of the rice. Moreover, the complexity of some of these systems can make them less accessible to smaller rice producers or suppliers who might not have the resources or expertise to operate them.
[0004] In light of these challenges, there is a need for a comprehensive solution that not only automates the rice freshness detection process but also ensures accuracy, consistency, and scalability. Such a solution should be user-friendly, adaptable to various operational scales, and capable of detecting both the freshness of the rice and potential adulterants.

SUMMARY
[0005] The present disclosure addresses this need for automated detection of freshness of rice, leveraging modern technology and reducing the potential for human error.
[0006] In an aspect, the present disclosure provides an apparatus for automated detection of freshness of rice. The apparatus comprises a collection assembly configured to obtain a rice sample of a predefined weight and transfer the rice sample to a sample processing arrangement. The sample processing arrangement comprises a container adapted to receive the rice sample from the collection assembly. The sample processing arrangement also comprises a dispenser configured to dispense a chemical solution of a predefined volume into the container. The sample processing arrangement further comprises a mixer configured to mix the chemical solution with the rice sample, to generate a sample mixture. The apparatus further comprises a testing arrangement. The testing arrangement comprises a sensor configured to capture a spectrum or an image of the sample mixture. The testing arrangement further comprises a processing module in signal communication with the sensor and configured to analyse the captured spectrum or image of the sample mixture to detect the freshness of the rice sample.
[0007] In one or more embodiments, the processing module is configured to analyse the captured spectrum or image of the sample mixture based on one or more of: a colorimetric value of the sample mixture, a pretrained artificial intelligence model configured to correlate the captured spectrum or image of the sample mixture with rice freshness levels, comparing the captured spectrum or image with reference spectrums or images associated with varying degrees of rice freshness.
[0008] In one or more embodiments, the collection assembly comprises a hopper adapted to hold the rice sample; and a weighing mechanism associated with the hopper, the weighing mechanism configured to generate a signal indicative of the rice sample in the hopper being of the predefined weight.
[0009] In one or more embodiments, the collection assembly further comprises a transfer mechanism configured to transfer the rice sample from the hopper to the container in the sample processing arrangement, the transfer mechanism comprising one or more of: a hopper bottom opening mechanism, a tilted tray, a conveyor, a robotic arm.
[0010] In one or more embodiments, the dispenser comprises an actuator and a dispensing tube, the actuator configured to linearly move the dispensing tube to have a tip thereof being disposed within the container, to allow for the dispensing tube to dispense the chemical solution inside the container.
[0011] In one or more embodiments, the mixer comprises an air supply unit configured to supply pressurized air inside the container for a predefined time-period to achieve mixing of the chemical solution with the rice sample.
[0012] In one or more embodiments, the sensor comprises one or more of: an RGB sensor, an image sensor.
[0013] In one or more embodiments, the apparatus further comprises an adulterant detection sensor configured to detect presence of an adulterant from a group of sodium carbonate, sodium bicarbonate in the rice sample either in the collection assembly or in the container before dispensing of the chemical solution. The adulterant detection sensor further configured to generate a signal indicative of the detected presence of the adulterant.
[0014] In one or more embodiments, the sample processing arrangement further comprises a chemical preparation arrangement configured to dilute a predetermined quantity of concentrated chemical stock solution with a predetermined volume of water, to obtain the chemical solution.
[0015] In one or more embodiments, the apparatus further comprises a drain mechanism configured to drain out the sample mixture from the container post each analysis.
[0016] In one or more embodiments, the apparatus further comprises a cleaning mechanism configured to clean the container post each analysis. The cleaning mechanism utilizes one or more of liquid rinsing and air-jet for cleaning the container.
[0017] In one or more embodiments, the apparatus further comprises a display configured to display a result of the detected freshness of the rice sample.
[0018] In one or more embodiments, the apparatus further comprises a printer configured to generate a report based on a result of the detected freshness of the rice sample.
[0019] In one or more embodiments, the processing module is further configured to store results of the detected freshness of the rice sample in a database. The database is implemented in one or more of an internal memory of the apparatus, a central server, a blockchain.
[0020] In one or more embodiments, the processing module is further configured to generate analytics for the detected freshness of the rice samples over a time-period and/or in a particular geographical region.
[0021] In another aspect, the present disclosure provides a method for automated detection of freshness of rice. The method comprises obtaining a rice sample of a predefined weight. The method further comprises transferring the rice sample to a container. The method further comprises dispensing a chemical solution of a predefined volume into the container containing the rice sample. The method further comprises mixing the chemical solution with the rice sample to generate a sample mixture. The method further comprises capturing a spectrum or an image of the sample mixture. The method further comprises analysing the captured spectrum or image to detect the freshness of the rice sample.
[0022] In one or more embodiments, the method further comprises analysing the captured spectrum or image based on a colorimetric value of the sample mixture, to detect the freshness of the rice sample.
[0023] In one or more embodiments, the method further comprises analysing the captured spectrum or image utilizing a pretrained artificial intelligence model configured to correlate the captured spectrum or image of the sample mixture with rice freshness levels, to detect the freshness of the rice sample.
[0024] In one or more embodiments, the method further comprises analysing the captured spectrum or image by comparing the captured spectrum or image with reference spectrums or images associated with varying degrees of rice freshness, to detect the freshness of the rice sample.
[0025] In one or more embodiments, the method further comprises detecting presence of an adulterant from a group of sodium carbonate, sodium bicarbonate in the rice sample in the container before dispensing of the chemical solution.

BRIEF DESCRIPTION OF THE FIGURES
[0026] For a more complete understanding of example embodiments of the present disclosure, reference is now made to the following descriptions taken in connection with the accompanying drawings in which:
FIG. 1 illustrates a diagrammatic perspective view of an apparatus for automated detection of freshness of rice, in accordance with one or more embodiments of the present disclosure;
FIG. 2 illustrates a diagrammatic back planar view of the apparatus of FIG. 1 with cover removed to depict internal components thereof, in accordance with one or more embodiments of the present disclosure;
FIG. 3 illustrates a simplified block diagram of the apparatus of FIG. 1 depicting signal communication between components thereof, in accordance with one or more embodiments of the present disclosure; and
FIG. 4 illustrates a flowchart listing steps involved in a method for automated detection of freshness of rice, in accordance with one or more embodiments of the present disclosure.

DETAILED DESCRIPTION
[0027] In the following description, for purposes of explanation, numerous specific details are set forth in order to provide a thorough understanding of the present disclosure. It will be apparent, however, to one skilled in the art that the present disclosure is not limited to these specific details.
[0028] Reference in this specification to “one embodiment” or “an embodiment” means that a particular feature, structure, or characteristic described in connection with the embodiment is included in at least one embodiment of the present disclosure. The appearance of the phrase “in one embodiment” in various places in the specification are not necessarily all referring to the same embodiment, nor are separate or alternative embodiments mutually exclusive of other embodiments. Further, the terms “a” and “an” herein do not denote a limitation of quantity, but rather denote the presence of at least one of the referenced items. Moreover, various features are described which may be exhibited by some embodiments and not by others. Similarly, various requirements are described which may be requirements for some embodiments but not for other embodiments.
[0029] Furthermore, in the following detailed description of the present disclosure, numerous specific details are set forth in order to provide a thorough understanding of the present disclosure. However, it will be understood that the present disclosure may be practiced without these specific details. In other instances, well-known methods, procedures, components, and circuits have not been described in detail so as not to unnecessarily obscure aspects of the present disclosure.
[0030] Embodiments described herein may be discussed in the general context of computer-executable instructions residing on some form of computer-readable storage medium, such as program modules, executed by one or more computers or other devices. By way of example, and not limitation, computer-readable storage media may comprise non-transitory computer-readable storage media and communication media; non-transitory computer-readable media include all computer-readable media except for a transitory, propagating signal. Generally, program modules include routines, programs, objects, components, data structures, etc., that perform particular tasks or implement particular abstract data types. The functionality of the program modules may be combined or distributed as desired in various embodiments.
[0031] Some portions of the detailed description that follows are presented and discussed in terms of a process or method. Although steps and sequencing thereof are disclosed in figures herein describing the operations of this method, such steps and sequencing are exemplary. Embodiments are well suited to performing various other steps or variations of the steps recited in the flowchart of the figure herein, and in a sequence other than that depicted and described herein. Some portions of the detailed descriptions that follow are presented in terms of procedures, logic blocks, processing, and other symbolic representations of operations on data bits within a computer memory. These descriptions and representations are the means used by those skilled in the data processing arts to most effectively convey the substance of their work to others skilled in the art. In the present application, a procedure, logic block, process, or the like, is conceived to be a self-consistent sequence of steps or instructions leading to a desired result. The steps are those utilizing physical manipulations of physical quantities. Usually, although not necessarily, these quantities take the form of electrical or magnetic signals capable of being stored, transferred, combined, compared, and otherwise manipulated in a computer system. It has proven convenient at times, principally for reasons of common usage, to refer to these signals as transactions, bits, values, elements, symbols, characters, samples, pixels, or the like.
[0032] In some implementations, any suitable computer usable or computer readable medium (or media) may be utilized. The computer readable medium may be a computer readable signal medium or a computer readable storage medium. The computer-usable, or computer-readable, storage medium (including a storage device associated with a computing device) may be, for example, but is not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, device, or any suitable combination of the foregoing. More specific examples (a non-exhaustive list) of the computer-readable medium may include the following: an electrical connection having one or more wires, a portable computer diskette, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or Flash memory), an optical fibre, a portable compact disc read-only memory (CD-ROM), an optical storage device, a digital versatile disk (DVD), a static random access memory (SRAM), a memory stick, a floppy disk, a mechanically encoded device such as punch-cards or raised structures in a groove having instructions recorded thereon, a media such as those supporting the internet or an intranet, or a magnetic storage device. Note that the computer-usable or computer-readable medium could even be a suitable medium upon which the program is stored, scanned, compiled, interpreted, or otherwise processed in a suitable manner, if necessary, and then stored in a computer memory. In the context of the present disclosure, a computer-usable or computer-readable storage medium may be any tangible medium that can contain or store a program for use by or in connection with the instruction execution system, apparatus, or device.
[0033] In some implementations, a computer readable signal medium may include a propagated data signal with computer readable program code embodied therein, for example, in baseband or as part of a carrier wave. In some implementations, such a propagated signal may take any of a variety of forms, including, but not limited to, electro-magnetic, optical, or any suitable combination thereof. In some implementations, the computer readable program code may be transmitted using any appropriate medium, including but not limited to the internet, wireline, optical fibre cable, RF, etc. In some implementations, a computer readable signal medium may be any computer readable medium that is not a computer readable storage medium and that can communicate, propagate, or transport a program for use by or in connection with an instruction execution system, apparatus, or device.
[0034] In some implementations, computer program code for carrying out operations of the present disclosure may be assembler instructions, instruction-set-architecture (ISA) instructions, machine instructions, machine dependent instructions, microcode, firmware instructions, state-setting data, or either source code or object code written in any combination of one or more programming languages, including an object oriented programming language such as Java, Smalltalk, C++ or the like. Java and all Java-based trademarks and logos are trademarks or registered trademarks of Oracle and/or its affiliates. However, the computer program code for carrying out operations of the present disclosure may also be written in conventional procedural programming languages, such as the “C” programming language, PASCAL, or similar programming languages, as well as in scripting languages such as JavaScript, PERL, or Python. In present implementations, the used language for training may be one of Python, Tensorflow, Bazel, C, C++. Further, decoder in user device (as will be discussed) may use C, C++ or any processor specific ISA. Furthermore, assembly code inside C/C++ may be utilized for specific operation. Also, ASR (automatic speech recognition) and G2P decoder along with entire user system can be run in embedded Linux (any distribution), Android, iOS, Windows, or the like, without any limitations. The program code may execute entirely on the user's computer, partly on the user's computer, as a stand-alone software package, partly on the user’s computer and partly on a remote computer or entirely on the remote computer or server. In the latter scenario, the remote computer may be connected to the user’s computer through a local area network (LAN) or a wide area network (WAN), or the connection may be made to an external computer (for example, through the internet using an Internet Service Provider). In some implementations, electronic circuitry including, for example, programmable logic circuitry, field-programmable gate arrays (FPGAs) or other hardware accelerators, micro-controller units (MCUs), or programmable logic arrays (PLAs) may execute the computer readable program instructions/code by utilizing state information of the computer readable program instructions to personalize the electronic circuitry, in order to perform aspects of the present disclosure.
[0035] In some implementations, the flowchart and block diagrams in the figures illustrate the architecture, functionality, and operation of possible implementations of apparatus (systems), methods and computer program products according to various implementations of the present disclosure. Each block in the flowchart and/or block diagrams, and combinations of blocks in the flowchart and/or block diagrams, may represent a module, segment, or portion of code, which comprises one or more executable computer program instructions for implementing the specified logical function(s)/act(s). These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, or other programmable data processing apparatus to produce a machine, such that the computer program instructions, which may execute via the processor of the computer or other programmable data processing apparatus, create the ability to implement one or more of the functions/acts specified in the flowchart and/or block diagram block or blocks or combinations thereof. It should be noted that, in some implementations, the functions noted in the block(s) may occur out of the order noted in the figures. For example, two blocks shown in succession may, in fact, be executed substantially concurrently, or the blocks may sometimes be executed in the reverse order, depending upon the functionality involved.
[0036] In some implementations, these computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function/act specified in the flowchart and/or block diagram block or blocks or combinations thereof.
[0037] In some implementations, the computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed (not necessarily in a particular order) on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions/acts (not necessarily in a particular order) specified in the flowchart and/or block diagram block or blocks or combinations thereof.
[0038] Referring to FIGS. 1 and 2, illustrated are different views of an apparatus (as represented by reference numeral 100) for automated detection of freshness of rice, in accordance with one or more embodiments of the present disclosure. The apparatus 100, as illustrated, is designed to be portable tailored specifically to cater to application of rice freshness assessment. For this purpose, the apparatus 100 may have an in-built power unit, such as a battery (not shown), to power its components. Herein, the apparatus 100 may have integrated processing capabilities (as discussed later in the description) for on-field applications. The apparatus 100 is further designed to be modular, allowing users to easily upgrade components or replace parts as needed. This modularity ensures longevity and adaptability, catering to evolving needs and technological advancements. With detachable components and a compact design, users can easily transport the apparatus 100 to different locations, ensuring that rice freshness detection can be conducted on-site, whether it is at the farm, storage facility, or the marketplace. Moreover, for rice processors or suppliers who work in challenging environments, the apparatus 100 is be designed to be rugged, dust-proof, and water-resistant. Specialized coatings or encasements may be used to ensure that the apparatus 100 remains operational even in less than ideal conditions. In general, the apparatus 100 is designed to fit seamlessly into both industrial and smaller-scale settings. The design of the apparatus 100 emphasizes user-friendliness ensuring that operators, regardless of their technical expertise, can utilize it with ease, and versatility so it can adapt to varied operational needs, for rice freshness assessment.
[0039] As illustrated in combination of FIGS. 1 and 2, the apparatus 100 includes a collection assembly 110. The collection assembly 110 is specifically configured to obtain a rice sample of a predefined weight. For this purpose, the collection assembly 110 includes a sample collection port 112 located on outside of the apparatus 100 to allow for a user to pour the rice sample inside thereof. The collection assembly 110, via the sample collection port 112, ensures consistency in sample size, which helps in maintaining the accuracy of the test results. Further, the collection assembly 110 includes a hopper 114 adapted to hold the rice sample. The hopper 114 is designed to facilitate easy loading of the rice while ensuring that quantity of the rice sample is consistent. The hopper 114 is further adapted to minimize spillage and wastage.
[0040] The collection assembly 110 further includes a weighing mechanism 116 associated with the hopper 114. In an example embodiment, the weighing mechanism 116 may be in the form of a load cell or the like; however, other suitable types of weighing mechanisms 116 may be employed without any limitations. The weighing mechanism 116 is configured to generate a signal indicative of the rice sample in the hopper 114 being of the predefined weight. In the present implementations, the predefined weight is set to be 5 grams. Herein, when the weight of the rice sample in the hopper 114 reaches the predefined weight, the weighing mechanism 116 may generate a sound or an alarm to alert the user to stop pouring more rice into the sample collection port 112. In an example, an internal volume of the hopper 114 is defined to be such that it may only accommodate rice quantity up to the predefined weight, and any extra rice grains may spill off therefrom.
[0041] The apparatus 100 also includes a sample processing arrangement 120. Herein, the collection assembly 110 is further configured to transfer the rice sample to the sample processing arrangement 120. In particular, the sample processing arrangement 120 includes a container 122. In an example embodiment, the container 122 is in the form of a cuvette (with these terms being interchangeably used hereinafter). The design of the cuvette 122 offers several advantages, especially in the context of rice freshness detection. Traditionally used for holding samples in spectroscopic experiments, the cuvette 122 has precise dimensions and clear, transparent properties. The transparency ensures that any spectrum or image capture is free from distortions, enhancing the accuracy of the readings. Additionally, the standardized size of the cuvette 122 ensures uniform sample volume, which is important for consistency in analysis. The design of the cuvette 122 further aids in ensuring a homogeneous mixture of the rice sample and chemical solution (as discussed later), allowing for an even distribution of particles and eliminating potential dead zones. The utilization of the cuvette as the container 122 increases the reliability and reproducibility of the results.
[0042] Herein, the container 122 is adapted to receive the rice sample from the collection assembly 110. Specifically, the collection assembly 110 includes a transfer mechanism 124 configured to transfer the rice sample from the hopper 114 to the container 122 in the sample processing arrangement 120. The transfer mechanism 124 plays a role in ensuring that the rice sample from the hopper 114 is efficiently moved to the container 122 within the sample processing arrangement 120. The integration of the transfer mechanism 124 eliminates manual interventions, thereby reducing the chances of errors or inconsistencies during the transfer process. The design of the transfer mechanism 124 ensures minimal spillage and maintains the integrity of the sample, ensuring that the exact quantity of rice originally measured in the hopper 114 reaches the container 122 for further processing.
[0043] In an example, the transfer mechanism 124 may include one or more of components such as a hopper bottom opening mechanism, a tilted tray, a conveyor, or even a robotic arm. For instance, the hopper bottom opening mechanism may be employed, which releases the rice sample from the hopper 114 by leveraging gravity, ensuring a smooth and consistent flow. Further, a tilted tray may be utilized, where the inclination assists in guiding the rice grains towards the container 122. In more advanced setups, a conveyor system may be employed to provide a continuous and controlled movement of the rice sample from the hopper 114 to the container 122. Alternatively, a robotic arm may be integrated into the transfer mechanism 124 to pick, hold, and accurately place the rice sample into the container 122, ensuring precision and minimizing human intervention. With inclusion of such component(s), the transfer mechanism 124 ensures that the transfer of the rice sample is seamless, reducing the potential for spillage or contamination.
[0044] The sample processing arrangement 120, in the apparatus 100, further includes a dispenser 126. The dispenser 126 is configured to dispense a chemical solution of a predefined volume into the container 122. That is, the dispenser 126 is designed to cater to the precise needs of the rice freshness detection process by introducing the chemical solution into the container 122, ensuring that the volume of the dispensed solution remains consistent and predefined. For this purpose, the dispenser 126 may be calibrated to dispense this chemical solution in the predefined volume into the container 122. The precision with which the dispenser 126 operates ensures that the rice sample within the container 122 is exposed to a consistent quantity of the chemical solution, which is crucial for achieving reproducible and accurate results. It may be understood that variation in the amount of this chemical solution may lead to skewed assessments of rice freshness.
[0045] The chemical solution, as utilized in the apparatus 100, is a specially formulated mixture designed to interact with the rice sample in a manner that facilitates the detection of its freshness. Herein, the chemical solution is derived from a combination of specific indicators, primarily methyl red and bromothymol blue. To prepare the stock solution, 0.05 g of methyl red and 0.15 g of bromothymol blue are dissolved in 75 ml of ethyl alcohol, with the volume then made up to 100 ml using distilled water. This stock solution is stored in a cool, dark place, preferably in an amber-coloured flask to preserve its integrity. For the actual testing process, a working solution is prepared by mixing such concentrated chemical stock solution and diluting it with distilled water. Given the perishable nature of this working solution, it is typically prepared in-situ with consideration to the number of rice samples to be tested, ensuring its consumption either on the same day or the next.
[0046] In some embodiments, the sample processing arrangement 120 further includes a chemical preparation arrangement (not shown) configured to dilute a predetermined quantity of the concentrated chemical stock solution with a predetermined volume of water, to obtain the chemical solution. In an example, the chemical solution for testing purposes is prepared by taking an aliquot of the stock solution and diluting it with distilled water in a volume ratio of 1:50. Such operation of the chemical preparation arrangement is automatic to minimize human intervention in operation of the apparatus 100. In an example, the chemical preparation arrangement, which prepares the chemical solution, may be equipped with sensors and feedback mechanisms to ensure the consistency of the chemical solution. Any deviations in the concentration or quality of the chemical solution can be immediately detected and corrected, ensuring that the sample mixture is always consistent.
[0047] In the present non-limiting configuration, the dispenser 126 may include an actuator 128 and a dispensing tube 130. These components work in tandem to ensure the accurate and consistent dispensing of the chemical solution into the container 122. The actuator 128 serves as the driving force behind the operation of the dispenser 126. The actuator 128 facilitates the linear movement of the dispensing tube 130, positioning its tip within the container 122. This precise positioning ensures that when the chemical solution is released, it is dispensed directly into the container 122, minimizing spillage or wastage. The dispensing tube 130 may be in the form of a conduit that carries the chemical solution from its storage or preparation area to the container 122. The dispensing tube 130, given its design, can hold and release the chemical solution with high accuracy, adhering to the predefined volume specifications. By ensuring a controlled and accurate dispensation of the chemical solution, the dispenser 126 helps in the overall operation of the apparatus 100 for consistent and reliable rice freshness detection.
[0048] The sample processing arrangement 120, in the apparatus 100, further includes a mixer 132 configured to mix the chemical solution with the rice sample, to generate a sample mixture. As may be understood, once the chemical solution is dispensed into the container 122 containing the rice sample, it may be required that the two components be uniformly combined to facilitate the intended chemical reactions and interactions. Herein, the mixer 132 ensures that the chemical solution permeates through the rice sample, allowing for an even distribution and interaction between the rice grains and the chemical solution. In an example, the mixer 132 may be equipped with various mixing modes, allowing for the adjustment of mixing intensity and duration. This adaptability ensures that regardless of the rice type or sample size, the mixing process can be optimized for the best results. For instance, the mixer 132 may operate using mechanisms that create a swirling or agitating motion within the container 122. This motion ensures that the rice grains and the chemical solution are continuously moved and turned, leading to a homogeneous sample mixture. Such uniform mixing is important as it ensures that most of the rice grains in the rice sample are exposed to the chemical solution. This sample mixture is then employed for the subsequent analysis, as the interaction between the chemical solution and the rice will reveal the freshness of the rice.
[0049] In an exemplary configuration, as illustrated, the mixer 132 may be combined with the dispensing tube 130 of the dispenser 126. By merging the functionalities of the mixer 132 and the dispensing tube 130, the apparatus 100 achieves a streamlined process flow. As the chemical solution is dispensed from the dispensing tube 130 into the container 122, the mixer 132, being part of the same unit, immediately initiates the mixing process. This ensures that the rice sample begins interacting with the chemical solution almost instantaneously, reducing any lag time or potential settling of the components. Furthermore, this combined design minimizes the number of moving parts within the apparatus 100, leading to reduced wear and tear, lesser maintenance requirements, and enhanced reliability. The integrated nature of the mixer 132 and the dispensing tube 130 also ensures that the entire mixing process is contained, reducing the risk of spillage or external contamination. It may be appreciated that this configuration is exemplary only, and shall not be construed as limiting to the present disclosure.
[0050] In an embodiment, the mixer 132 includes an air supply unit (not shown) configured to supply pressurized air inside the container 122 for a predefined time-period to achieve mixing of the chemical solution with the rice sample. Herein, the force of the incoming air agitates the chemical solution and the rice sample, creating a turbulent environment inside the container 122. This turbulence ensures that the rice grains in the rice sample are continuously swirled and turned, allowing for an even distribution and interaction of the chemical solution with each grain. Secondly, the pressurized air creates micro-bubbles within the chemical solution, further enhancing the mixing efficiency. The use of the air supply unit for mixing eliminates the need for mechanical agitators or mixers, which can wear out or introduce contaminants into the sample. The air-based mixing is also gentle on the rice grains, reducing the risk of breaking or damaging them, which could otherwise impact the accuracy of the freshness detection.
[0051] The apparatus 100 further includes a testing arrangement 140. The testing arrangement 140 is configured to assess the sample mixture and derive meaningful data that indicates the freshness of the rice. Herein, once the rice sample and the chemical solution have been thoroughly mixed within the container 122 of the sample processing arrangement 120, the resultant sample mixture is evaluated by the testing arrangement 140. To achieve this, the testing arrangement 140 is equipped with advanced sensors and analytical modules designed to capture and interpret the characteristics of the sample mixture.
[0052] Specifically, for the detection process, the testing arrangement 140 includes a sensor 142 configured to capture a spectrum or an image of the sample mixture. For this purpose, the sensor 142 is located in the apparatus 100 so as to be able to capture readings related to the sample mixture present in the container 122. In an example configuration, the sensor 142 may be disposed in direct contact with outside of the container 122. Alternatively, the sensor 142 may be disposed remote to the container 122 but oriented in a manner to achieve the said purpose. The sensor 142 operates on advanced optical principles, ensuring high-resolution data capture. When capturing a spectrum, the sensor 142 measures the light intensity as a function of its wavelength, offering a spectrum (spectral fingerprint) of the sample mixture. On the other hand, when capturing an image, the sensor 142 provides a high-definition visual representation of the sample mixture, enabling the apparatus 100 to discern colour changes, clarity, and other visual indicators that might signify the freshness level of the rice sample. Depending on the specific embodiment of the apparatus 100, this sensor 142 may be an RGB sensor, an image sensor, or even other specialized sensing devices. The choice of the sensor 142 ensures that the apparatus 100 can accurately discern the subtle colour or spectral changes in the sample mixture, which are indicative of freshness of the rice sample.
[0053] In some examples, the sensor 142 in the testing arrangement 140 may be equipped with features that compensate for external light interference, ensuring that the captured data is consistent and reliable. Furthermore, the sensor 142 might be complemented by auxiliary components, such as light sources or filters, to enhance the clarity and accuracy of the data capture. The sensor 142 may also be enhanced to include thermal imaging capabilities. This additional feature can provide insights into the temperature variations within the sample mixture, offering another dimension to the freshness detection process.
[0054] In an embodiment, the apparatus 100 may also include an adulterant detection sensor (not shown) configured to detect presence of an adulterant from a group of sodium carbonate, sodium bicarbonate in the rice sample either in the collection assembly 110 or in the container 122 before dispensing of the chemical solution. That is, the adulterant detection sensor is configured to detect the presence of specific adulterants, such as sodium carbonate or sodium bicarbonate, which are sometimes added to rice to mimic freshness, using electrochemical analysis. The adulterant detection sensor can be placed either in the collection assembly 110 for such detection, or may be implemented for detection within the container 122 before the chemical solution is dispensed. The adulterant detection sensor is further configured to generate a signal (electrochemical sensor response) indicative of the detected presence of the adulterant. That is, upon detecting such adulterant, the adulterant detection sensor generates a signal, alerting the user of the potential contamination. Such integrated adulterant detection sensor offers a safeguard against potential rice contamination, ensuring that consumers receive genuine, fresh rice. In some examples, in addition to the described adulterant detection sensor, the apparatus 100 may incorporate a multi-sensor system capable of detecting a broader range of adulterants or contaminants. This comprehensive detection system ensures that the rice is not only fresh but also free from harmful or unwanted substances.
[0055] The testing arrangement 140, in the apparatus 100, further includes a processing module 144 in signal communication with the sensor 142. The processing module 144 is configured to analyse the captured spectrum or image of the sample mixture to detect the freshness of the rice sample. That is, the processing module 144 acts as the computational and analytical hub of the apparatus 100, interpreting and analysing the data captured by the sensor 142 to provide a clear and accurate assessment of freshness of the rice sample. Herein, upon capturing either a spectrum or an image of the sample mixture by the sensor 142, this data is transmitted to the processing module 144. The processing module 144 is equipped with advanced algorithms and computational capabilities to process the data from the sensor 142, extracting information that corresponds to the freshness of the rice. In particular, in the present embodiments, the processing module 144 is configured to analyse the captured spectrum or image of the sample mixture based on one or more of: a colorimetric value of the sample mixture, a pretrained artificial intelligence model configured to correlate the captured spectrum or image of the sample mixture with rice freshness levels, comparing the captured spectrum or image with reference spectrums or images associated with varying degrees of rice freshness.
[0056] In one embodiment, the processing module 144 is configured to analyse the captured spectrum or image based on the colorimetric value of the sample mixture. Colorimetry, in this context, involves the quantitative assessment of the colour or hue of the sample mixture. This is implemented as the colour of the mixture can offer direct insights into the freshness of the rice. When rice interacts with the chemical solution within the container 122, it results in a coloured sample mixture. For instance, in present implementation with use of the specified chemical solution, specific colour shades or intensities corresponding to ‘Green’ may correlate with particular stages of rice freshness. This is because, during the course of the rice’s storage or aging process, certain chemical reactions can occur which might influence the colour of the mixture when subjected to the chemical solution. The processing module 144, equipped with advanced colour detection algorithms, may accurately detect and quantify these colour variations from the sensor data. For instance, a shade of bright green or avocado green may indicate freshly milled rice, whereas other colours like yellow, yellow orange, or orange may suggest that the rice has been stored for a longer period.
[0057] In another embodiment, the processing module 144 utilizes artificial intelligence (AI) to enhance its analytical capabilities. Herein, the processing module 144 employs a pretrained AI model, specifically designed to correlate the captured spectrum or image of the sample mixture with varying levels of rice freshness. The utilization of AI ensures a high degree of precision, as the model can recognize subtle patterns, variations, or anomalies in the captured data that might be indicative of freshness of the rice sample. Furthermore, over time, the AI model may also adapt and refine its analytical processes, leveraging previous evaluations to enhance future assessments.
[0058] In yet another embodiment, the processing module 144 is configured to compare the captured spectrum or image against a repository of reference spectrums or images. These references represent established benchmarks associated with various degrees of rice freshness. Each reference spectrum or image in this repository may be derived from extensive empirical studies and testing. For instance, a reference image might depict the exact shade or pattern expected from a rice sample that is few months old, while another might represent a rice sample that's been stored for several years. By comparing the captured data against these references, the processing module 144 may determine where the sample stands in terms of freshness. Through this comparative analysis, the processing module 144 may determine the degree of alignment or deviation of the captured data from the established benchmarks. For instance, if the captured spectrum closely aligns with a reference spectrum corresponding to freshly milled rice, the processing module 144 can infer that the rice sample is fresh, otherwise it may be inferred that the rice sample is not fresh.
[0059] In other embodiments, the processing module 144 offers a multi-faceted approach to data analysis. The processing module 144 may leverage a combination of colorimetry, artificial intelligence, and comparative analytics, it ensures that the freshness assessment of the rice is comprehensive, accurate, and reliable. Through the colorimetric evaluation, the processing module 144 provides a quick yet accurate gauge of rice freshness. The implementation of one or more of the AI models and the comparative analysis offers additional layer(s) of verification, ensuring that the assessment is not only based on standalone data but is also contextualized, and thereby increasing the accuracy and reliability of the rice freshness assessment by the apparatus 100 of the present disclosure.
[0060] In the present implementations, to enhance the adaptability and effectiveness of the apparatus 100, several additional features can be integrated, each contributing to a more comprehensive solution for rice freshness detection. For instance, it may be appreciated that post-analysis, it is essential to prepare the apparatus 100 for the next sample. For this purpose, the apparatus 100 includes a drain mechanism (as represented by reference numeral 160) configured to drain out the sample mixture from the container 122 post each analysis. In the present configuration, the drain mechanism 160 may employ a drain tray which is disposed at an angle with respect to the container 122, and herein, the container 122 may be tilted to allow the sample mixture to flow out effortlessly, utilizing gravity to facilitate the draining process. Additionally, the apparatus 100 includes a cleaning mechanism (as represented by reference numeral 162) configured to clean the container post each analysis. Herein, the cleaning mechanism 162 is implemented in the form of a pipe. The cleaning mechanism 162 may utilize one or more of liquid rinsing and air-jet for cleaning the container 122. This ensures that the container 122 is thoroughly cleaned post-analysis, and thereby the apparatus 100 is ready to receive the next rice sample for further analysis.
[0061] In some embodiments, the apparatus 100 further includes a display 150 configured to display a result of the detected freshness of the rice sample. As illustrated in FIG. 1, the display 150 may be mounted on outer body of the apparatus 100. The display 150 serves as the primary medium for conveying the results derived from the evaluations performed by the processing module 144, transforming complex analytical data into easily comprehensible visuals or text. Designed for clarity and ease of interpretation, the display 150 can present the results in a variety of formats. For instance, once the freshness of the rice sample has been determined, the display might show a simple textual message such as “Fresh” or “Stored for 3 months”. In more advanced scenarios, the display 150 can utilize color-coded systems, where specific colours correspond to certain freshness levels. A green indicator might signify fresh rice, whereas a yellow or red might indicate older rice. Additionally, the display 150 may come equipped with touch-responsive features, allowing users to interact with the displayed results, delve deeper into the analysis, or even recalibrate settings if required. Such interactivity ensures that users can tailor the apparatus 100 to their specific needs and preferences.
[0062] In some embodiments, the apparatus 100 further includes a printer 152 configured to generate a report based on a result of the detected freshness of the rice sample. As illustrated in FIG. 1, the printer 152 may also be mounted on the outer body of the apparatus 100. The printer 152 offers a tangible representation of the results obtained from the testing process. The printed report can serve several purposes. For instance, in commercial settings, where rice is procured in bulk, such reports can act as certificates of quality, authenticating the freshness of the rice batch and thereby facilitating trust between sellers and buyers.
[0063] Referring to FIG. 3, illustrated is a simplified block diagram of the apparatus 100 depicting signal communication between the components, in accordance with one or more embodiments of the present disclosure. This representation is in alignment with one or more embodiments described in the present disclosure. As illustrated, the sensor 142 is in active signal communication with the processing module 144. Furthermore, external devices like the display 150 and the printer 152, although not directly involved in the analysis, are also interconnected, receiving processed data from the processing module 144. These connections between the various components of the apparatus 100, emphasize the intricacies with which they operate in tandem to achieve the objective of rice freshness detection.
[0064] In an embodiment, the processing module 144 is further configured to store results of the detected freshness of the rice sample in a database 300 (as shown in FIG. 3). This storage (archival) function plays a role in ensuring the continuity, traceability, and accountability of the testing processes. Each record in the database 300 may include information such as the date and time of the evaluation, the unique identifier of the rice batch, the captured spectrum or image, the derived colorimetric value and/or the comparative benchmark used, and the final freshness determination. Herein, the database 300 is implemented in one or more of an internal memory of the apparatus 100, a central server, a blockchain. The internal memory of the apparatus 100 offers a quick-access storage solution, ideal for temporary or short-term data retention. This internal memory ensures that results are instantly accessible for quick reviews or subsequent evaluations. For more long-term storage and for remote access purposes, the central server and/or the blockchain may be implemented. The ability to store and analyse data over time provides rice producers and suppliers with invaluable insights, allowing for continuous improvement in their processes. In particular, herein, storing the results on the blockchain ensures that once a record is added, it becomes immutable and tamper-proof, which increases trustworthiness of the data and also establishes an unbroken chain of custody for each rice sample evaluation.
[0065] In an embodiment, the processing module 144 is further configured to generate analytics for the detected freshness of the rice samples over a time-period and/or in a particular geographical region. By analysing the results over the predefined time-period, be it months, or even years, the processing module 144 can identify trends in rice quality. For instance, the processing module 144 may determine if a particular batch of rice tends to degrade faster during specific months or seasons, offering valuable information that can guide storage or procurement decisions. Such temporal analytics can be invaluable for businesses or individuals keen on ensuring consistent rice quality throughout the year. Furthermore, by correlating the freshness results with specific geographical regions, the processing module 144 can identify areas that produce consistently fresh rice or regions where the rice tends to degrade faster. Such geographical analytics may guide procurement strategies, helping businesses identify the best regions to source their rice grains. It may be appreciated that such analysis may take place within the integrated processing module 144 of the apparatus 100, or a remote server while the process is facilitated by the processing module 144.
[0066] Further, in one or more embodiments, the apparatus 100 may be equipped with mobile connectivity, allowing for real-time data syncing and remote access. For instance, the apparatus 100 may feature connectivity to mobile applications or web platforms, allowing users to monitor the rice freshness detection process remotely, receive notifications, and even access detailed reports on their mobile devices or computers. Such features enable stakeholders at every level, from rice farmers to wholesalers, to stay informed and make timely interventions as needed. Additionally, the apparatus 100 may feature remote troubleshooting capabilities. In case of any malfunctions or operational issues, experts can remotely access the apparatus 100, diagnose the problem, and provide real-time solutions, ensuring minimal downtime. Also, the apparatus 100 may incorporate a user-friendly interface on the display 150, offering step-by-step guidance throughout the freshness detection process. This interface can include visual cues, prompts, and feedback, ensuring that even individuals without prior experience can operate the apparatus 100 effectively. The apparatus 100 may also be equipped with a user authentication system, ensuring that only authorized personnel can operate it. This feature adds an additional layer of security and accountability to the rice freshness detection process.
[0067] For rice suppliers or processors who deal with different varieties of rice, the apparatus 100 can be designed with customizable settings. Depending on the rice variety, the user can select the appropriate detection algorithm or reference database, ensuring that the results are tailored to the specific rice type. Further, in some scenarios, such as for environments where multiple samples need to be processed simultaneously, the apparatus 100 can be designed to accommodate multiple containers 122 and dispensers 126, allowing for parallel processing. Such a design of the apparatus 100 is particularly beneficial for large-scale operations, drastically reducing the time required for rice freshness detection. For larger scale operations, the apparatus 100 may also be integrated into a production line, automating the rice freshness detection process for bulk samples. In such setups, the apparatus 100 may be paired with additional modules, such as rice sorting and packaging units, offering an end-to-end solution for rice processing plants. Herein, the processing module 144 may be configured to sync with other digital tools, such as Enterprise Resource Planning (ERP) systems, Supply Chain Management (SCM) systems, and Customer Relationship Management (CRM) systems to allow for real-time data sharing, enabling holistic management and optimization of the entire rice supply chain.
[0068] Referring to FIG. 4, illustrated is a flowchart listing steps involved in a method 400 for automated detection of freshness of rice, in accordance with one or more embodiments of the present disclosure. Various embodiments and variants disclosed above, with respect to the aforementioned apparatus 100, apply mutatis mutandis to the present method 400. Herein, at step 402, the method 400 comprises obtaining a rice sample of a predefined weight. At step 404, the method 400 further comprises transferring the rice sample to a container (such as, the container 122). At step 406, the method 400 further comprises dispensing a chemical solution of a predefined volume into the container containing the rice sample. At step 408, the method 400 further comprises mixing the chemical solution with the rice sample to generate a sample mixture. At step 410, the method 400 further comprises capturing a spectrum or an image of the sample mixture. At step 412, the method 400 comprises analysing the captured spectrum or image to detect the freshness of the rice sample.
[0069] In the present embodiments, the method 400 comprises analysing the captured spectrum or image based on a colorimetric value of the sample mixture, to detect the freshness of the rice sample. Alternatively, or additionally, the method 400 comprises analysing the captured spectrum or image utilizing a pretrained artificial intelligence model configured to correlate the captured spectrum or image of the sample mixture with rice freshness levels, to detect the freshness of the rice sample. Alternatively, or additionally, the method 400 comprises analysing the captured spectrum or image by comparing the captured spectrum or image with reference spectrums or images associated with varying degrees of rice freshness, to detect the freshness of the rice sample. Further, in one or more embodiments, the method 400 further comprises detecting presence of an adulterant from a group of sodium carbonate, sodium bicarbonate in the rice sample in the container before dispensing of the chemical solution.
[0070] The apparatus 100 and the method 400 of the present disclosure represents a significant advancement in the field of rice freshness detection. By leveraging modern technology, the apparatus 100 offers a rapid, consistent, and objective method for determining the freshness of rice, ensuring that consumers receive the highest quality product. The present apparatus 100 offers numerous advantages over traditional methods and known prior art. The apparatus 100 provides ability to provide rapid, consistent, and objective results. Traditional methods of determining rice freshness are often subjective, relying on human judgment, which can be inconsistent and error-prone. The present apparatus 100 eliminates this variability by using standardized procedures and objective measurements. Further, the automation of the detection process ensures rapid, consistent, and objective results, eliminating the variability introduced by manual methods. Also, most conventional methods require grinding of rice grains before any kind of automated testing. The present apparatus 100 eliminates this need, providing a non-destructive approach for automated rice freshness detection. In the present apparatus 100, the use of a pretrained artificial intelligence model and a database of reference spectrums or images adds another layer of accuracy and reliability to the detection process. Another advantage is ability of the apparatus 100 to detect potential adulterants, such as sodium carbonate or sodium bicarbonate. Adulteration of rice can compromise its quality and can have adverse health effects. By being able to detect such adulterants, the apparatus 100 ensures that only fresh, unadulterated rice reaches consumers. Further, the apparatus 100 offers the advantage of data storage and analysis. By storing results and analysing them over time, producers can gain insights into the quality of their rice, allowing for continuous improvement in their farming practices.
[0071] The foregoing description of the specific embodiments will so fully reveal the general nature of the embodiments herein that others can, by applying current knowledge, readily modify and/or adapt for various applications such specific embodiments without departing from the generic concept, and, therefore, such adaptations and modifications should and are intended to be comprehended within the meaning and range of equivalents of the disclosed embodiments. It is to be understood that the phraseology or terminology employed herein is for the purpose of description and not of limitation. Therefore, while the embodiments herein have been described in terms of preferred embodiments, those skilled in the art will recognize that the embodiments herein can be practiced with modification within the spirit and scope of the present disclosure.
, C , Claims:WE CLAIM:
1. An apparatus for automated detection of freshness of rice, the apparatus comprising:
a collection assembly configured to obtain a rice sample of a predefined weight and transfer the rice sample to a sample processing arrangement;
the sample processing arrangement comprising:
a container adapted to receive the rice sample from the collection assembly;
a dispenser configured to dispense a chemical solution of a predefined volume into the container; and
a mixer configured to mix the chemical solution with the rice sample, to generate a sample mixture; and
a testing arrangement comprising:
a sensor configured to capture a spectrum or an image of the sample mixture; and
a processing module in signal communication with the sensor and configured to analyse the captured spectrum or image of the sample mixture to detect the freshness of the rice sample.

2. The apparatus as claimed in claim 1, wherein the processing module is configured to analyse the captured spectrum or image of the sample mixture based on one or more of: a colorimetric value of the sample mixture, a pretrained artificial intelligence model configured to correlate the captured spectrum or image of the sample mixture with rice freshness levels, comparing the captured spectrum or image with reference spectrums or images associated with varying degrees of rice freshness.

3. The apparatus as claimed in claim 1, wherein the collection assembly comprises:
a hopper adapted to hold the rice sample; and
a weighing mechanism associated with the hopper, the weighing mechanism configured to generate a signal indicative of the rice sample in the hopper being of the predefined weight.

4. The apparatus as claimed in claim 3, wherein the collection assembly further comprises a transfer mechanism configured to transfer the rice sample from the hopper to the container in the sample processing arrangement, the transfer mechanism comprising one or more of: a hopper bottom opening mechanism, a tilted tray, a conveyor, a robotic arm.

5. The apparatus as claimed in claim 1, wherein the dispenser comprises an actuator and a dispensing tube, the actuator configured to linearly move the dispensing tube to have a tip thereof being disposed within the container, to allow for the dispensing tube to dispense the chemical solution inside the container.

6. The apparatus as claimed in claim 1, wherein the mixer comprises an air supply unit configured to supply pressurized air inside the container for a predefined time-period to achieve mixing of the chemical solution with the rice sample.

7. The apparatus as claimed in claim 1, wherein the sensor comprises one or more of: an RGB sensor, an image sensor.

8. The apparatus as claimed in claim 1 further comprising an adulterant detection sensor configured to detect presence of an adulterant from a group of sodium carbonate, sodium bicarbonate in the rice sample either in the collection assembly or in the container before dispensing of the chemical solution, the adulterant detection sensor further configured to generate a signal indicative of the detected presence of the adulterant.

9. The apparatus as claimed in claim 1, wherein the sample processing arrangement further comprises a chemical preparation arrangement configured to dilute a predetermined quantity of concentrated chemical stock solution with a predetermined volume of water, to obtain the chemical solution.

10. The apparatus as claimed in claim 1 further comprising a drain mechanism configured to drain out the sample mixture from the container post each analysis.

11. The apparatus as claimed in claim 1 further comprising a cleaning mechanism configured to clean the container post each analysis, the cleaning mechanism utilizing one or more of liquid rinsing and air-jet for cleaning the container.

12. The apparatus as claimed in claim 1 further comprising a display configured to display a result of the detected freshness of the rice sample.

13. The apparatus as claimed in claim 1 further comprising a printer configured to generate a report based on a result of the detected freshness of the rice sample.

14. The apparatus as claimed in claim 1, wherein the processing module is further configured to store results of the detected freshness of the rice sample in a database, the database being implemented in one or more of an internal memory of the apparatus, a central server, a blockchain.

15. The apparatus as claimed in claim 1, wherein the processing module is further configured to generate analytics for the detected freshness of the rice samples over a time-period and/or in a particular geographical region.

16. A method for automated detection of freshness of rice, the method comprising:
obtaining a rice sample of a predefined weight;
transferring the rice sample to a container;
dispensing a chemical solution of a predefined volume into the container containing the rice sample;
mixing the chemical solution with the rice sample to generate a sample mixture;
capturing a spectrum or an image of the sample mixture; and
analysing the captured spectrum or image to detect the freshness of the rice sample.

17. The method as claimed in claim 15 further comprising analysing the captured spectrum or image based on a colorimetric value of the sample mixture, to detect the freshness of the rice sample.

18. The method as claimed in claim 15 further comprising analysing the captured spectrum or image utilizing a pretrained artificial intelligence model configured to correlate the captured spectrum or image of the sample mixture with rice freshness levels, to detect the freshness of the rice sample.

19. The method as claimed in claim 15 further comprising analysing the captured spectrum or image by comparing the captured spectrum or image with reference spectrums or images associated with varying degrees of rice freshness, to detect the freshness of the rice sample.

20. The method as claimed in claim 15 further comprising detecting presence of an adulterant from a group of sodium carbonate, sodium bicarbonate in the rice sample in the container before dispensing of the chemical solution.