Description:FIELD OF INVENTION
[0001] The embodiments of the present disclosure generally relate to food safety management systems. More particularly, the present disclosure relates to a method and a system for monitoring a food safety risk associated with a plurality of food products in an electronic commerce (e-commerce) environment.

BACKGROUND
[0002] The following description of the related art is intended to provide background information pertaining to the field of the disclosure. This section may include certain aspects of the art that may be related to various features of the present disclosure. However, it should be appreciated that this section be used only to enhance the understanding of the reader with respect to the present disclosure, and not as admissions of the prior art.
[0003] Generally, public interests, documentaries, reports, and media broadcasts in food safety management may have led to a need for eliminating consumer anxiety regarding a safety of distribution or sale of food products and to establish measures to secure reliability of food safety management protocols associated with government regulations. Recently, many issues may be reported regarding food adulterant / food fraudulent items being sold illegally in e-commerce platforms. For example, food products listed by some sellers in an e-commerce marketplace may likely include food fraudulent or adulterant items which may be prohibited for sale by the government regulation. In some instances, food fraudulent items may be sold to a consumer, which may lead to safety risks for the consumer and in turn implies non-compliance of legal and statutory requirements.
[0004] Further, the food fraud may occur when the seller or a food supplier intentionally deceive its customer regarding the quality and contents of the foods the consumers are purchasing. While the food fraud may often be motivated by profit, some forms of food fraud can also pose a direct threat to the health of customers and consumers. Detecting food fraud may be a challenge because consumers alone cannot detect them, and food fraudsters are usually innovative in the ways they avoid detection. To ensure the safety of the consumers and to comply with regulations, there is a need for real time identification, monitoring and restricting of the adulterants or prohibited food items.
[0005] Currently, the adulterants or prohibited food items may be manually checked and identified, which may lead to time consuming and possibility of manual errors. Conventional method may provide an online food safety management method for real-time transmission and reception of information on website, investigation, and information sharing. The conventional method may enable food related investigation, report, and follow-up measures. Another conventional method may provide a method for detecting a food fraud. The conventional method may use handheld portable devices for testing from the laboratory to the field and nuclear techniques, such as stable isotope analysis to detect various kinds of fraud, including mislabeling of origin and production process. Further, the conventional method includes a Deoxyribonucleic acid (DNA) barcoding to identify species substitution, and a blockchain and other digital traceability solutions for transparency of food supply chains. However, the conventional method may not instantly identify, in real time, the fraudulent food items as a whole or as an ingredient in the food product. Further, the conventional methods may not ensure that the fraudulent food product is not been listed in the e-commerce platform/marketplace, for avoiding fraudulent food items available on platform for the consumers and assuring regulatory compliance.
[0006] Therefore, there may be a need for a method and a system for solving the shortcomings of the conventional methods, by providing a method and a system for monitoring a food safety risk associated with a plurality of food products in an electronic commerce (e-commerce) environment.

SUMMARY
[0007] This section is provided to introduce certain objects and aspects of the present invention in a simplified form that are further described below in the detailed description. This summary is not intended to identify the key features or the scope of the claimed subject matter. In order to overcome at least a few problems associated with the known solutions as provided in the previous section, an object of the present disclosure is to provide a technique for monitoring a food safety risk associated with a plurality of food products in an electronic commerce (e-commerce) environment.
[0008] It is an object of the present disclosure to provide a method and a system for monitoring a food safety risk associated with a plurality of food products in an electronic commerce (e-commerce) environment.
[0009] It is an object of the present disclosure to provide a method and a system for identifying fraudulent food items as a whole or as an ingredient in the product in real time.
[0010] It is an object of the present disclosure to ensure that the fraudulent products are not listed in the e-commerce environment, by detecting fraudulent keywords associated with the food product images and information provided as part of a background data check (product characteristics, description, consumer information, and the like.).
[0011] It is an object of the present disclosure to ensure no fraudulent items available on the e-commerce environment for the consumers and assuring regulatory compliance.
[0012] In an aspect, the present disclosure provides a method for monitoring a food safety risk associated with a plurality of food products in an electronic commerce (e-commerce) environment. The method includes receiving listing data corresponding to one or more food products. The listing data comprises at least one of textual data, and media data. Further, the method includes extracting one or more ingredients data from the received listing data. Furthermore, the method includes determining at least one food vertical in a plurality of pre-defined food verticals, corresponding to the extracted one or more ingredients data. Additionally, the method includes mapping the at least one food vertical with a plurality of pre-defined prohibited ingredient classifications. Further, the method includes identifying a food safety risk corresponding to at least one of a regulatory risk and a legal risk associated with the at least one food vertical mapped to the plurality of pre-defined prohibited ingredient classifications. Furthermore, the method includes monitoring periodically one or more food products with the identified food safety risk, and autoblocking the one or more food products at a listing level.
[0013] In an embodiment, the food safety risk is monitored for a food fraud activity in the e-commerce environment.
[0014] In another embodiment, the food fraud activity corresponds to a fraudulent activity, an adulterant activity, a prohibited activity, and a banned activity.
[0015] In another embodiment, the food fraud activity corresponds to at least one of product concealment, an unapproved enhancement of the product, an addition of unregulated ingredients in the product, an addition of prohibited ingredients in the product, a mislabeling of the product, and a false claim of the product.
[0016] In yet another embodiment, the listing data comprises at least one of product ingredients, product claims, and product labelling data.
[0017] In yet another embodiment, the listing data corresponds to existing listing data and new listing data of the one or more food products.
[0018] In yet another embodiment, the plurality of pre-defined prohibited ingredient classifications comprises at least one of: prohibited ingredient categories, prohibited ingredient sub-categories, prohibited ingredient groups, prohibited ingredient sub-groups, prohibited ingredient buckets, prohibited ingredient channels.
[0019] In another aspect, the present disclosure provides a system for monitoring a food safety risk associated with a plurality of food products in an electronic commerce (e-commerce) environment. The system receives listing data corresponding to one or more food products. The listing data comprises at least one of textual data, and media data. Further, the system extracts one or more ingredients data from the received listing data. Furthermore, the system determines at least one food vertical in a plurality of pre-defined food verticals, corresponding to the extracted one or more ingredients data. Additionally, the system maps the at least one food vertical with a plurality of pre-defined prohibited ingredient classifications. Furthermore, the system identifies a food safety risk corresponding to at least one of a regulatory risk and a legal risk associated with the at least one food vertical mapped to the plurality of pre-defined prohibited ingredient classifications. Additionally, the system monitors periodically one or more food products with the identified food safety risk, and autoblocking the one or more food products at a listing level.

BRIEF DESCRIPTION OF THE ACCOMPANYING DRAWINGS
[0020] The accompanying drawings, which are incorporated herein, and constitute a part of this invention, illustrate exemplary embodiments of the disclosed methods and systems in which like reference numerals refer to the same parts throughout the different drawings. Components in the drawings are not necessarily to scale, emphasis instead being placed upon clearly illustrating the principles of the present invention. Some drawings may indicate the components using block diagrams and may not represent the internal circuitry/sub-components of each component. It will be appreciated by those skilled in the art that the invention of such drawings includes the invention of electrical components, electronic components, or circuitry commonly used to implement such components.
[0021] FIG. 1 illustrates an exemplary block diagram representation of a network architecture implementing a proposed system for monitoring a food safety risk associated with a plurality of food products in an electronic commerce (e-commerce) environment, according to embodiments of the present disclosure.
[0022] FIG. 2 illustrates an exemplary detailed block diagram representation of the proposed system, according to embodiments of the present disclosure.
[0023] FIG. 3A illustrates an exemplary schematic diagram representation of an autogenerated mail to a seller on detection of food fraud ingredient, according to embodiments of the present disclosure.
[0024] FIG. 3B illustrates an exemplary schematic diagram representation of an autogenerated daily mail with consolidated list of autoblocking on food fraud ingredient, according to embodiments of the present disclosure.
[0025] FIG. 4 illustrates a flow chart depicting a method of monitoring a food safety risk associated with a plurality of food products in an electronic commerce (e-commerce) environment, according to embodiments of the present disclosure.
[0026] FIG. 5 illustrates a hardware platform for the implementation of the disclosed system according to embodiments of the present disclosure.
[0027] The foregoing shall be more apparent from the following more detailed description of the invention.

DETAILED DESCRIPTION OF INVENTION
[0028] In the following description, for the purposes of explanation, various specific details are set forth in order to provide a thorough understanding of the embodiments of the present disclosure. It will be apparent, however, that embodiments of the present disclosure may be practiced without these specific details. Several features described hereafter can each be used independently of one another or with any combination of other features. An individual feature may not address all of the problems discussed above or might address only some of the problems discussed above. Some of the problems discussed above might not be fully addressed by any of the features described herein.
[0029] The ensuing description provides exemplary embodiments only, and is not intended to limit the scope, applicability, or configuration of the disclosure. Rather, the ensuing description of the exemplary embodiments will provide those skilled in the art with an enabling description for implementing an exemplary embodiment. It should be understood that, various changes may be made in the function and arrangement of elements without departing from the spirit and scope of the invention as set forth.
[0030] Specific details are given in the following description to provide a thorough understanding of the embodiments. However, it will be understood by one of ordinary skill in the art that the embodiments may be practiced without these specific details. For example, circuits, systems, networks, processes, and other components may be shown as components in block diagram form in order not to obscure the embodiments in unnecessary detail. In other instances, well-known circuits, processes, algorithms, structures, and techniques may be shown without unnecessary detail in order to avoid obscuring the embodiments.
[0031] Also, it is noted that individual embodiments may be described as a process which is depicted as a flowchart, a flow diagram, a data flow diagram, a structure diagram, or a block diagram. Although a flowchart may describe the operations as a sequential process, many of the operations can be performed in parallel or concurrently. In addition, the order of the operations may be re-arranged. A process is terminated when its operations are completed but could have additional steps not included in a figure. A process may correspond to a method, a function, a procedure, a subroutine, a subprogram, etc. When a process corresponds to a function, its termination can correspond to a return of the function to the calling function or the main function.
[0032] The word “exemplary” and/or “demonstrative” is used herein to mean serving as an example, instance, or illustration. For the avoidance of doubt, the subject matter disclosed herein is not limited by such examples. In addition, any aspect or design described herein as “exemplary” and/or “demonstrative” is not necessarily to be construed as preferred or advantageous over other aspects or designs, nor is it meant to preclude equivalent exemplary structures and techniques known to those of ordinary skill in the art. Furthermore, to the extent that the terms “includes,” “has,” “contains,” and other similar words are used in either the detailed description or the claims, such terms are intended to be inclusive—in a manner similar to the term “comprising” as an open transition word—without precluding any additional or other elements.
[0033] As used herein, "connect", "configure", "couple" and its cognate terms, such as "connects", "connected", "configured", and "coupled" may include a physical connection (such as a wired/wireless connection), a logical connection (such as through logical gates of semiconducting device), other suitable connections, or a combination of such connections, as may be obvious to a skilled person.
[0034] As used herein, "send", "transfer", "transmit", and their cognate terms like "sending", "sent", "transferring", "transmitting", "transferred", "transmitted", etc. include sending or transporting data or information from one unit or component to another unit or component, wherein the content may or may not be modified before or after sending, transferring, transmitting.
[0035] Reference throughout this specification to “one embodiment” or “an embodiment” or “an instance” or “one instance” means that a particular feature, structure, or characteristic described in connection with the embodiment is included in at least one embodiment of the present invention. Thus, the appearances of the phrases “in one embodiment” or “in an embodiment” in various places throughout this specification are not necessarily all referring to the same embodiment. Furthermore, the particular features, structures, or characteristics may be combined in any suitable manner in one or more embodiments.
[0036] The terminology used herein is for the purpose of describing particular embodiments only and is not intended to be limiting of the invention. As used herein, the singular forms “a,” “an,” and “the” are intended to include the plural forms as well, unless the context clearly indicates otherwise. It will be further understood that the terms “comprises” and/or “comprising,” when used in this specification, specify the presence of stated features, integers, steps, operations, elements, and/or components, but do not preclude the presence or addition of one or more other features, integers, steps, operations, elements, components, and/or groups thereof. As used herein, the term “and/or” includes any and all combinations of one or more of the associated listed products.
[0037] Various embodiments of the present disclosure provide a method and a system for monitoring a food safety risk associated with a plurality of food products in an electronic commerce (e-commerce) environment. The present disclosure provides a method and a system for identifying fraudulent food items as a whole or as an ingredient in the product in real time. The present disclosure ensures that the fraudulent products are not listed in the e-commerce environment, by detecting fraudulent keywords associated with the food product images and information provided as part of a background data check (product characteristics, description, consumer information, and the like.). The present disclosure ensures no fraudulent items available on the e-commerce environment for the consumers and assuring regulatory compliance.
[0038] FIG. 1 illustrates an exemplary block diagram representation of a network architecture 100 implementing a proposed system 110 for monitoring a food safety risk associated with a plurality of food products in an electronic commerce (e-commerce) environment, according to embodiments of the present disclosure. The network architecture 100 may include an electronic device 108, the system 110, and a centralized server 118. The system 110 may be connected to the centralized server 118 via a communication network 106. The centralized server 118 may include, but is not limited to, a stand-alone server, a remote server, a cloud computing server, a dedicated server, a rack server, a server blade, a server rack, a bank of servers, a server farm, hardware supporting a part of a cloud service or system, a home server, hardware running a virtualized server, one or more processors executing code to function as a server, one or more machines performing server-side functionality as described herein, at least a portion of any of the above, some combination thereof, and the like. The centralized server 118 may be associated with an entity corresponding to an electronic commerce (e-commerce) environment. The communication network 106 may be a wired communication network or a wireless communication network. The wireless communication network may be any wireless communication network capable of transferring data between entities of that network such as, but are not limited to, a Bluetooth, a Zigbee, a Near Field Communication (NFC), a Wireless-Fidelity (Wi-Fi) network, a Light Fidelity (Li-FI) network, a carrier network including a circuit-switched network, a packet switched network, a Public Switched Telephone Network (PSTN), a Content Delivery Network (CDN) network, an Internet, intranets, Local Area Networks (LANs), Wide Area Networks (WANs), mobile communication networks including a Second Generation (2G), a Third Generation (3G), a Fourth Generation (4G), a Fifth Generation (5G), a Sixth Generation (6G), a Long-Term Evolution (LTE) network, a New Radio (NR), a Narrow-Band (NB), an Internet of Things (IoT) network, a Global System for Mobile Communications (GSM) network and a Universal Mobile Telecommunications System (UMTS) network, combinations thereof, and the like.
[0039] The system 110 may be implemented by way of a single device or a combination of multiple devices that may be operatively connected or networked together. For example, the system 110 may be implemented by way of a standalone device such as the centralized server 118, and the like, and may be communicatively coupled to the electronic device 108. In another example, the system 110 may be implemented in/ associated with the electronic device 108. In yet another example, the system 110 may be implemented in/ associated with respective computing device 104-1, 104-2, …..., 104-N (individually referred to as the computing device 104, and collectively referred to as the computing devices 104), associated with one or more user 102-1, 102-2, …..., 102-N (individually referred to as the user 102, and collectively referred to as the users 102). In such a scenario, the system 110 may be replicated in each of the computing devices 104. The users 102 may be a user of, but are not limited to, an electronic commerce (e-commerce) platform, a merchant platform, a hyperlocal platform, a super-mart platform, a media platform, a service providing platform, a social networking platform, a services booking platform, a messaging platform, a bot processing platform, a virtual assistance platform, an Artificial Intelligence (AI) based platform, a blockchain platform, a blockchain marketplace, and the like. In some instances, the user 102 may correspond to an entity/administrator of platforms/services.
[0040] The electronic device 108 may be at least one of, an electrical, an electronic, an electromechanical, and a computing device. The electronic device 108 may include, but is not limited to, a mobile device, a smart-phone, a Personal Digital Assistant (PDA), a tablet computer, a phablet computer, a wearable computing device, a Virtual Reality / Augmented Reality (VR/AR) device, a laptop, a desktop, a server, and the like. The system 110 may be implemented in hardware or a suitable combination of hardware and software. The system 110 or the centralized server 118 may be associated with entities (not shown). The entities may include, but are not limited to, an e-commerce company, a merchant organization, an airline company, a hotel booking company, a company, an outlet, a manufacturing unit, an enterprise, a facility, an organization, an educational institution, a secured facility, a warehouse facility, a supply chain facility, and the like.
[0041] Further, the system 110 may include a processor 112, an Input/Output (I/O) interface 114, and a memory 116. The Input/Output (I/O) interface 114 of the system 110 may be used to receive user inputs, from the computing devices 104 associated with the users 102. Further, system 110 may also include other units such as a display unit, an input unit, an output unit, and the like, however the same are not shown in FIG. 1, for the purpose of clarity. Also, in FIG. 1 only a few units are shown, however, the system 110 or the network architecture 100 may include multiple such units or the system 110/ network architecture 100 may include any such numbers of the units, obvious to a person skilled in the art or as required to implement the features of the present disclosure. The system 110 may be a hardware device including the processor 112 executing machine-readable program instructions to monitor a food safety risk associated with a plurality of food products in an electronic commerce (e-commerce) environment.
[0042] Execution of the machine-readable program instructions by the processor 112 may enable the proposed system 110 to monitor a food safety risk associated with a plurality of food products in an electronic commerce (e-commerce) environment. The “hardware” may comprise a combination of discrete components, an integrated circuit, an application-specific integrated circuit, a field-programmable gate array, a digital signal processor, or other suitable hardware. The “software” may comprise one or more objects, agents, threads, lines of code, subroutines, separate software applications, two or more lines of code, or other suitable software structures operating in one or more software applications or on one or more processors. The processor 112 may include, for example, but is not limited to, microprocessors, microcomputers, microcontrollers, digital signal processors, central processing units, state machines, logic circuits, and any devices that manipulate data or signals based on operational instructions, and the like. Among other capabilities, the processor 112 may fetch and execute computer-readable instructions in the memory 116 operationally coupled with the system 110 for performing tasks such as data processing, input/output processing, feature extraction, and/or any other functions. Any reference to a task in the present disclosure may refer to an operation being or that may be performed on data.
[0043] In the example that follows, assume that a user 102 of the system 110 desires to improve/add additional features to monitor a food safety risk associated with a plurality of food products in an electronic commerce (e-commerce) environment. In this instance, the user 102 may include an administrator of a website, an administrator of an e-commerce site, an administrator of a social media site, an administrator of an e-commerce application/ social media application/other applications, an administrator of media content (e.g., television content, video-on-demand content, online video content, graphical content, image content, augmented/virtual reality content, metaverse content), an administrator of supply chain platform, an administrator of blockchain marketplace, an administrator of a travel/services booking platform, an administrator of merchant platform, among other examples, and the like. The system 110 when associated with the electronic device 108 or the centralized server 118 may include, but is not limited to, a touch panel, a soft keypad, a hard keypad (including buttons), and the like.
[0044] In an embodiment, the system 110 may receive listing data corresponding to one or more food products. In an embodiment, the listing data includes, but are not limited to, textual data, media data, and the like. In an embodiment, the listing data includes, but are not limited to, product ingredients, product claims, product labelling data, and the like. In an embodiment, the listing data corresponds to existing listing data and new listing data of the one or more food products.
[0045] In an embodiment, the system 110 may extract one or more ingredients data from the received listing data.
[0046] In an embodiment, the system 110 may determine at least one food vertical in a plurality of pre-defined food verticals, corresponding to the extracted one or more ingredients data. The plurality of pre-defined food verticals may include, but are not limited to, food categories, food groups, food buckets, food channels, food subcategories, and the like.
[0047] In an embodiment, the system 110 may map the at least one food vertical with a plurality of pre-defined prohibited ingredient classifications. In an embodiment, the plurality of pre-defined prohibited ingredient classifications includes, but are not limited to, prohibited ingredient categories, prohibited ingredient sub-categories, prohibited ingredient groups, prohibited ingredient sub-groups, prohibited ingredient buckets, prohibited ingredient channels, and the like.
[0048] In an embodiment, the system 110 may identify a food safety risk corresponding to at least one of a regulatory risk and a legal risk associated with the at least one food vertical mapped to the plurality of pre-defined prohibited ingredient classifications.
[0049] In an embodiment, the system 110 may monitor periodically one or more food products with the identified food safety risk, and autoblocking the one or more food products at a listing level. In an embodiment, the food safety risk may be monitored for a food fraud activity in the e-commerce environment. In an embodiment, the food fraud activity corresponds to, but is not limited to, a fraudulent activity, an adulterant activity, a prohibited activity, a banned activity, and the like. In an embodiment, the food fraud activity corresponds to, but not limited to, a product concealment, an unapproved enhancement of the product, an addition of unregulated ingredients in the product, an addition of prohibited ingredients in the product, a mislabeling of the product, a false claim of the product, and the like.
[0050] FIG. 2 illustrates an exemplary detailed block diagram representation of the proposed system 110, according to embodiments of the present disclosure. The system 110 may include the processor 112, the Input/Output (I/O) interface 114, and the memory 116. In some implementations, the system 110 may include data 202, and modules 204. As an example, the data 202 may be stored in the memory 116 configured in the system 110 as shown in FIG. 2.
[0051] In an embodiment, the data 202 may include listing data 206, food product data 208, ingredients data 210, food vertical data 212, prohibited ingredients classifications data 214, food safety risk data 216, autoblocking data 218, and other data 220. In an embodiment, the data 202 may be stored in the memory 116 in the form of various data structures. Additionally, the data 202 can be organized using data models, such as relational or hierarchical data models. The other data 218 may store data, including temporary data and temporary files, generated by the modules 204 for performing the various functions of the system 110.
[0052] In an embodiment, the modules 204, may include a receiving module 222, an extracting module 224, a determining module 226, a mapping module 228, an identifying module 230, a monitoring module 232, an autoblocking module 234, and other modules 236.
[0053] In an embodiment, the data 202 stored in the memory 116 may be processed by the modules 204 of the system 110. The modules 204 may be stored within the memory 116. In an example, the modules 204 communicatively coupled to the processor 112 configured in the system 110, may also be present outside the memory 116, as shown in FIG. 2, and implemented as hardware. As used herein, the term modules refer to an Application-Specific Integrated Circuit (ASIC), an electronic circuit, a processor (shared, dedicated, or group) and memory that execute one or more software or firmware programs, a combinational logic circuit, and/or other suitable components that provide the described functionality.
[0054] In an embodiment, the receiving module 222 may receive listing data corresponding to one or more food products. In an embodiment, the listing data includes, but are not limited to, textual data, media data, and the like. In an embodiment, the listing data includes, but are not limited to, product ingredients, product claims, product labelling data, and the like. In an embodiment, the listing data corresponds to existing listing data and new listing data of the one or more food products. The received listing data corresponding to one or more food products may be stored as the listing data 206. The one or more food products may be stored as the food product data 208.
[0055] In an embodiment, the extracting module 224 may extract one or more ingredients data from the received listing data. The extracted one or more ingredients data may be stored as the ingredients data 210. For example, the extraction of the one or more ingredients data from the received listing data may be performed using at least one of a string match technique, an optical character recognition (OCR), and the like.
[0056] In an embodiment, the determining module 226 may determine at least one food vertical in a plurality of pre-defined food verticals, corresponding to the extracted one or more ingredients data. The plurality of pre-defined food verticals may include, but are not limited to, food categories, food groups, food buckets, food channels, food subcategories, and the like. The plurality of pre-defined food verticals may be stored as the food vertical data 212.
[0057] For example, the plurality of pre-defined food verticals may include, but are not limited to, a chutney, a food color, chips, a paste/puree, a soya chunk, a fryum/papad, a cake/pastry, a syrup, a drink/juice, a ready meal, a ready mix, a stock broth, an edible seed, noodles, a water, a wafer/waffle, a popcorn, a vinegar, a vermicelli, a chyawanprash, a milk powder, a candy/mouth freshener, a pasta, a ghee, a rusk, a spice/masala, a chocolate, a pickle/murabba, a milk/drink mix, a baking ingredient, a soup, a tea, a snack/savorie, a fruit jam/spread, a coffee, a honey, a cereal/flake, a cookie/biscuit, a Fast-moving consumer goods (FMCG) combo, a milk, a digestive probiotic, a food essence, a concentrate, a sauce/ketchup, a baking decorative, a herb seasoning, a ready cook snack, an edible oil, an artificial sweetener, flour, a grain millet, a sugar, a salt, a nut dry fruit, pulses, a chewing gum, a canned food, a jaggery, a rice, a seafood, a sweet/mithai, a vitamin supplement, a protein supplement, an energy/sport drink mix, an aerated drink, an ice cube, an infant formula, a baby cereal, a baby snack puff, a fruit vegetable blend, a gripe water, a baby supplement, a bread crumb, a bakery roll, an egg, a fruit, a ready salad, a meat, a wrap base, a vegetable, a paneer/tofu, an ice cream, a butter, a dairy cream, a cheese, a butter milk, a curd/yogurt, a lassi, a bread/bun, and the like.
[0058] In an embodiment, the mapping module 228 may map the at least one food vertical with a plurality of pre-defined prohibited ingredient classifications. In an embodiment, the plurality of pre-defined prohibited ingredient classifications includes, but are not limited to, prohibited ingredient categories, prohibited ingredient sub-categories, prohibited ingredient groups, prohibited ingredient sub-groups, prohibited ingredient buckets, prohibited ingredient channels, and the like. The plurality of pre-defined prohibited ingredient classifications may be stored as the prohibited ingredients classifications data 214.
[0059] For example, the prohibited ingredient classifications may be shown in table 1 below:
Sl. No Name of
Food Banned Ingredient Notification Link
Food Banned Ingredients (FBI) 1 1 Para-Amino_Benzoic_acid
(PABA) PABA Notification

FBI 1 2 Raspberry_ketone Implementation of health supplements

FBI 1 3 Silica Implementation of health supplements

FBI 1 4 Angelica_sinensis Implementation of health supplements

FBI 1 5 Paullinia_cupana Implementation of health supplements

FBI 1 6 Saw_palmetto Implementation of health supplements

FBI 1 7 Notoginseng Implementation of health supplements

FBI 1 8 Chlorella_growth_factor or Chlorella Implementation of health supplements

FBI 1 9 Pinus_radiate Implementation of health supplements

FBI 1 10 Pinus_pinaster Implementation of health supplements

FBI 1 11 Chaga_extract/Inonotus_obliquus Implementation of health supplements

FBI 1 12 Oxalobacter_formigenes Implementation of health supplements

FBI 1 13 tea_tree_oil Implementation of health supplements

FBI 1 14 Succinic_acid Implementation of health supplements

FBI 1 15 Inosine Implementation of health supplements

FBI 1 16 Vanadium Implementation of health supplements

FBI 1 17 Prenolit Implementation of health supplements

FBI 1 18 Selenium_dioxide Implementation of health supplements

FBI 1 19 D-ribose Implementation of health supplements

FBI 1 20 Ipriflavone Implementation of health supplements

FBI 1 21 Polypodium_leucotomos Implementation of health supplements

FBI 1 22 Artichoke Implementation of health supplements

FBI 1 23 Kale_Powder Implementation of health supplements

FBI 1 24 Salvia_hispanica Implementation of health supplements

FBI 1 25 Cashew_fruit Implementation of health supplements

FBI 1 26 Passion_fruit Implementation of health supplements

FBI 1 27 Kiwi_fruit_extract Implementation of health supplements

FBI 1 28 Broccoli Implementation of health supplements

FBI 1 29 Pectinase Implementation of health supplements

FBI 1 30 Xylanase Implementation of health supplements

FBI 2 31 Potassium_bromate Prohibition of Potassium Bromate

FBI 2 32 Tobacco Compendium - Food Safety and Standards (Prohibition and Restriction of Sales) Regulation

FBI 2 33 nicotine Compendium - Food Safety and Standards (Prohibition and Restriction of Sales) Regulation

FBI 2 34 Kesari_gram/Lathyrus_sativus Compendium - Food Safety and Standards (Prohibition and Restriction of Sales) Regulation

FBI 2 35 Kesari_Dal/Lathyrus_sativus Compendium - Food Safety and Standards (Prohibition and Restriction of Sales) Regulation

FBI 2 36 Kesari_Dal_flour/Lathyrus_sativus Compendium - Food Safety and Standards (Prohibition and Restriction of Sales) Regulation

FBI 2 37 Coumarin Compendium - Food Safety and Standards (Food Products Standards and Food Additives) Regulation

FBI 2 38 Dihydrocoumarin Compendium - Food Safety and Standards (Food Products Standards and Food Additives) Regulation

FBI 2 39 Tonkabean/Dipteryl_adorat Compendium - Food Safety and Standards (Food Products Standards and Food Additives) Regulation

FBI 2 40 β-asarone Compendium - Food Safety and Standards (Food Products Standards and Food Additives) Regulation

FBI 2 41 cinamyl_anthracilate Compendium - Food Safety and Standards (Food Products Standards and Food Additives) Regulation

FBI 2 42 Estragole Compendium - Food Safety and Standards (Food Products Standards and Food Additives) Regulation

FBI 2 43 Ethyl_methyl_ketone Compendium - Food Safety and Standards (Food Products Standards and Food Additives) Regulation

FBI 2 44 Ethyl-3-phenylglycidate Compendium - Food Safety and Standards (Food Products Standards and Food Additives) Regulation

FBI 2 45 Eugenyl_methyl_ether Compendium - Food Safety and Standards (Food Products Standards and Food Additives) Regulation

FBI 2 46 Methyl_β-napthyl_ketone Compendium - Food Safety and Standards (Food Products Standards and Food Additives) Regulation

FBI 2 47 p-Propylanisole Compendium - Food Safety and Standards (Food Products Standards and Food Additives) Regulation

FBI 2 48 Saffrole Compendium - Food Safety and Standards (Food Products Standards and Food Additives) Regulation

FBI 2 49 Isosaffrole Compendium - Food Safety and Standards (Food Products Standards and Food Additives) Regulation

FBI 2 50 Thujone Compendium - Food Safety and Standards (Food Products Standards and Food Additives) Regulation

FBI 2 51 α-isothujone Compendium - Food Safety and Standards (Food Products Standards and Food Additives) Regulation

FBI 2 52 β-thujone Compendium - Food Safety and Standards (Food Products Standards and Food Additives) Regulation

FBI 2 53 4,5 epoxydec-2(trans)-enal] Compendium - Food Safety and Standards (Food Products Standards and Food Additives) Regulation

FBI 2 54 Shilajit Compendium - Food Safety and Standards (Food Products Standards and Food Additives) Regulation

FBI 3 55 Carbide_gas/Acetylene_gas Compendium - Food Safety and Standards (Prohibition and Restriction of Sales) Regulation

Food Banned Ingredient 4 56 Diethyleneglycol Compendium - Food Safety and Standards (Food Products Standards and Food Additives) Regulation

Food Banned Ingredient 4 57 Monoethyl _ether Compendium - Food Safety and Standards (Food Products Standards and Food Additives) Regulation

Food Banned Pesticide 1 Aldicarb Notification Pesticide Removal

Food Banned Pesticide 2 Aldrin Notification Pesticide Removal

Food Banned Pesticide 3 dieldrin Notification Pesticide Removal

Food Banned Pesticide 4 Chlordane Notification Pesticide Removal

Food Banned Pesticide 5 Heptachlor Notification Pesticide Removal

Food Banned Pesticide 6 Lindane Gamma-HCH) Gamma (γ) Isomer (Known as Lindane) Notification Pesticide Removal

Food Banned Pesticide 7 Endosulfan Notification Pesticide Removal

Food Banned Pesticide 8 Carbofuran 50 per cent. SP Notification Pesticide Removal

Food Banned Pesticide 9 Methomyl 12.5 per cent. L andMethomyl 24 per cent. formulation Notification Pesticide Removal

Food Banned Pesticide 10 Phosphamidon 85 per cent. SL Notification Pesticide Removal

Food Banned Pesticide 11 Captafol 80 per cent. Powder Notification Pesticide Removal

Food Banned Pesticide 12 Ferbam Notification Pesticide Removal

Food Banned Pesticide 13 Formothion Notification Pesticide Removal

Food Banned Pesticide 14 Simazine Notification Pesticide Removal

Food Banned Pesticide 15 Diazinon (Food Banned for use in agriculture except for household use) Notification Pesticide Removal

Food Banned Pesticide 16 D.D.T (Withdrawn for use in agriculture) Notification Pesticide Removal

Food Banned Pesticide 17 Fenitrothion (Food Banned for use in agriculture except for locust control in scheduled dessert area and public
health) Notification Pesticide Removal

Food Banned Pesticide 18 Fenthion (Food Banned in agriculture except for locust control, house hold and public health) Notification Pesticide Removal

Food Banned Pesticide 19 Methyl Parathion 50 per cent. EC and 2 per cent. DP formulations (Food Banned for use in fruits and
vegetables) Notification Pesticide Removal

Food Banned Pesticide 20 Ethyl Parathion Notification Pesticide Removal

Food Banned Pesticide 21 Monocrotophos (Food Banned for use on vegetable) Notification Pesticide Removal

Table 1
[0060] In an example, from the above table 1, 78 banned ingredient categories are categorized in a 5 different category for 87 food verticals. Further, the mapping of the at least one food vertical with the plurality of pre-defined prohibited ingredient classifications may be shown in table 2 below:
Food Vertical List
FBI 1 FBI 2 FBI 3 FBI 4 Food Banned Pesticide
protein_supplement festive_gift_box festive_gift_box food_essence festive_gift_box
vitamin_supplement Rusk fruit food _colour Rusk
digestive_probiotic honey fmcg_combo honey
baby_supplement paneer_tofu paneer_tofu
nutrition_supplement milk milk
festive_gift_box chocolate chocolate
fmcg_combo jaggery jaggery
infant_formulla protein_supplement protein_supplement
salt salt
edible_seed edible_seed
cake_pastry cake_pastry
baking_ingredient baking_ingredient
chyawanprash chyawanprash
vitamin_supplement vitamin_supplement
chutney chutney
ready_cook_snack ready_cook_snack
drinks_juice drinks_juice
ready_mix ready_mix
pulses pulses
herb_seasoning herb_seasoning
seafood seafood
digestive_probiotic digestive_probiotic
baby_supplement baby_supplement
cereal_flake cereal_flake
ice_cream ice_cream
jam_spread jam_spread
egg egg
noodle noodle
butter butter
artificial_sweetener artificial_sweetener
vegetable vegetable
fryum_papad fryum_papad
canned_food canned_food
grain_millet grain_millet
wafer_waffle wafer_waffle
pasta pasta
nutrition_supplement nutrition_supplement
lassi lassi
concentrate concentrate
butter_milk butter_milk
edible_oil edible_oil
baking_decorative baking_decorative
ice_cube ice_cube
sugar sugar
tea tea
soup soup
energy_sport_drink_mix energy_sport_drink_mix
chips chips
dairy_cream dairy_cream
sweet_mithai sweet_mithai
water water
snack_savourie snack_savourie
ready_meal ready_meal
ready_salad ready_salad
chewing_gum chewing_gum
nut_dry_fruit nut_dry_fruit
coffee coffee
rice rice
pickle_murabba pickle_murabba
soya_chunk soya_chunk
cheese cheese
syrup syrup
candy_mouth_freshener candy_mouth_freshener
stock_broth stock_broth
popcorn popcorn
vermicelli vermicelli
vinegar vinegar
food_color food_color
fmcg_combo fmcg_combo
aerated_drink aerated_drink
flour flour
food_essence food_essence
paste_puree paste_puree
spice_masala spice_masala
curd_yogurt curd_yogurt
bakery_roll bakery_roll
sauce_ketchup sauce_ketchup
ghee ghee
fruit fruit
wrap_base wrap_base
meat meat
cookie_biscuit cookie_biscuit
milk_drink_mix milk_drink_mix
milk_powder milk_powder
bread_bun bread_bun
Baby Cereal Baby Cereal
Baby Snack puff Baby Snack puff
Infant Formula Infant Formula
Table 2
[0061] In an embodiment, the identifying module 230 may identify a food safety risk corresponding to at least one of a regulatory risk and a legal risk associated with the at least one food vertical mapped to the plurality of pre-defined prohibited ingredient classifications. The identified food safety risk corresponding to at least one of the regulatory risks and the legal risk may be stored as the food safety risk data 216.
[0062] In an embodiment, the monitoring module 232 may monitor periodically one or more food products with the identified food safety risk. In an embodiment, the autoblocking module 234 may autoblock the one or more food products at a listing level. In an embodiment, the food safety risk may be monitored for a food fraud activity in the e-commerce environment. In an embodiment, the food fraud activity corresponds to, but is not limited to, a fraudulent activity, an adulterant activity, a prohibited activity, a banned activity, and the like. In an embodiment, the food fraud activity corresponds to, but not limited to, a product concealment, an unapproved enhancement of the product, an addition of unregulated ingredients in the product, an addition of prohibited ingredients in the product, a mislabeling of the product, a false claim of the product, and the like. The autoblocked one or more food products at the listing level may be stored as the autoblocking data 218.
Further, the monitoring report may be sent to the entity based on the table 3 below:
Request
Id Request
Type Seller
Id fsn time vertical auto_
status attributes_
abusing Attribute
_value restricted_
words_
found
REQ CREATE a4099 VSLG 29-10-2022 23:21 vitamin_
supplement FAILED image_
6||
composition herbal
license artichoke
REQ2 CREATE a4099 VSLG 29-10-2022 23:21 vitamin_
supplement FAILED image_6||
composition||
image_0 herbal
license artichoke
Table 3
For example, FIG. 3A illustrates an exemplary schematic diagram of an autogenerated mail to a seller on detection of food fraud ingredient. Further, FIG. 3B illustrates an exemplary schematic diagram of an autogenerated daily mail with consolidated list of autoblocking on food fraud ingredient.
[0063] FIG. 4 illustrates a flow chart depicting a method 400 of monitoring a food safety risk associated with a plurality of food products in an electronic commerce (e-commerce) environment, according to embodiments of the present disclosure.
[0064] At block 402, the method 400 includes receiving, by the processor 112 associated with a system 110, listing data corresponding to one or more food products. The listing data comprises at least one of textual data, and media data.
[0065] At block 404, the method 400 includes extracting, by the processor 112, one or more ingredients data from the received listing data.
[0066] At block 406, the method 400 includes determining, by the processor 112, at least one food vertical in a plurality of pre-defined food verticals, corresponding to the extracted one or more ingredients data.
[0067] At block 408, the method 400 includes mapping, by the processor 112, the at least one food vertical with a plurality of pre-defined prohibited ingredient classifications.
[0068] At block 410, the method 400 includes identifying, by the processor 112, a food safety risk corresponding to at least one of a regulatory risk and a legal risk associated with the at least one food vertical mapped to the plurality of pre-defined prohibited ingredient classifications.
[0069] At block 412, the method 400 includes monitoring periodically, by the processor 112, one or more food products with the identified food safety risk, and autoblocking the one or more food products at a listing level.
[0070] The order in which the method 400 is described is not intended to be construed as a limitation, and any number of the described method blocks may be combined or otherwise performed in any order to implement the method 400 or an alternate method. Additionally, individual blocks may be deleted from the method 400 without departing from the spirit and scope of the present disclosure described herein. Furthermore, the method 400 may be implemented in any suitable hardware, software, firmware, or a combination thereof, that exists in the related art or that is later developed. The method 400 describes, without limitation, the implementation of the system 110. A person of skill in the art will understand that method 400 may be modified appropriately for implementation in various manners without departing from the scope and spirit of the disclosure.
[0071] FIG. 5 illustrates a hardware platform 500 for implementation of the disclosed system 110, according to an example embodiment of the present disclosure. For the sake of brevity, the construction, and operational features of the system 110 which are explained in detail above are not explained in detail herein. Particularly, computing machines such as but not limited to internal/external server clusters, quantum computers, desktops, laptops, smartphones, tablets, and wearables which may be used to execute the system 110 or may include the structure of the hardware platform 500. As illustrated, the hardware platform 500 may include additional components not shown, and that some of the components described may be removed and/or modified. For example, a computer system with multiple GPUs may be located on external-cloud platforms including Amazon® Web Services, or internal corporate cloud computing clusters, or organizational computing resources, and the like.
[0072] The hardware platform 500 may be a computer system such as the system 110 that may be used with the embodiments described herein. The computer system may represent a computational platform that includes components that may be in a server or another computer system. The computer system may execute, by the processor 505 (e.g., a single or multiple processors) or other hardware processing circuit, the methods, functions, and other processes described herein. These methods, functions, and other processes may be embodied as machine-readable instructions stored on a computer-readable medium, which may be non-transitory, such as hardware storage devices (e.g., RAM (random access memory), ROM (read-only memory), EPROM (erasable, programmable ROM), EEPROM (electrically erasable, programmable ROM), hard drives, and flash memory). The computer system may include the processor 505 that executes software instructions or code stored on a non-transitory computer-readable storage medium 510 to perform methods of the present disclosure. The software code includes, for example, instructions to gather data and documents and analyze documents. In an example, the modules 204, may be software codes or components performing these steps. For example, the modules 204, may include a receiving module 222, an extracting module 224, a determining module 226, a mapping module 228, an identifying module 230, a monitoring module 232, an autoblocking module 234, and other modules 236.
[0073] The instructions on the computer-readable storage medium 510 are read and stored the instructions in storage 515 or in random access memory (RAM). The storage 515 may provide a space for keeping static data where at least some instructions could be stored for later execution. The stored instructions may be further compiled to generate other representations of the instructions and dynamically stored in the RAM such as RAM 520. The processor 505 may read instructions from the RAM 520 and perform actions as instructed.
[0074] The computer system may further include the output device 525 to provide at least some of the results of the execution as output including, but not limited to, visual information to users, such as external agents. The output device 525 may include a display on computing devices and virtual reality glasses. For example, the display may be a mobile phone screen or a laptop screen. GUIs and/or text may be presented as an output on the display screen. The computer system may further include an input device 530 to provide a user or another device with mechanisms for entering data and/or otherwise interacting with the computer system. The input device 530 may include, for example, a keyboard, a keypad, a mouse, or a touchscreen. Each of these output devices 525 and input device 530 may be joined by one or more additional peripherals. For example, the output device 525 may be used to display the results such as bot responses by the executable chatbot.
[0075] A network communicator 535 may be provided to connect the computer system to a network and in turn to other devices connected to the network including other clients, servers, data stores, and interfaces, for instance. A network communicator 535 may include, for example, a network adapter such as a LAN adapter or a wireless adapter. The computer system may include a data sources interface 540 to access the data source 545. The data source 545 may be an information resource. As an example, a database of exceptions and rules may be provided as the data source 545. Moreover, knowledge repositories and curated data may be other examples of the data source 545.
[0076] While considerable emphasis has been placed herein on the preferred embodiments, it will be appreciated that many embodiments can be made and that many changes can be made in the preferred embodiments without departing from the principles of the invention. These and other changes in the preferred embodiments of the invention will be apparent to those skilled in the art from the disclosure herein, whereby it is to be distinctly understood that the foregoing descriptive matter is to be implemented merely as illustrative of the invention and not as a limitation.

ADVANTAGES OF THE PRESENT DISCLOSURE
[0077] The present disclosure provides a method and a system for monitoring a food safety risk associated with a plurality of food products in an electronic commerce (e-commerce) environment.
[0078] The present disclosure provides a method and a system for identifying fraudulent food items as a whole or as an ingredient in the product in real time.
[0079] The present disclosure ensures that the fraudulent products are not listed in the e-commerce environment, by detecting fraudulent keywords associated with the food product images and information provided as part of a background data check (product characteristics, description, consumer information, and the like.).
[0080] The present disclosure ensures no fraudulent items available on the e-commerce environment for the consumers and assuring regulatory compliance.
 
, Claims:1. A method for monitoring a food safety risk associated with a plurality of food products in an electronic commerce (e-commerce) environment, the method comprising:
receiving, by a processor (112) associated with a system (110), listing data corresponding to one or more food products, wherein the listing data comprises at least one of textual data, and media data;
extracting, by the processor (112), one or more ingredients data from the received listing data;
determining, by the processor (112), at least one food vertical in a plurality of pre-defined food verticals, corresponding to the extracted one or more ingredients data;
mapping, by the processor (112), the at least one food vertical with a plurality of pre-defined prohibited ingredient classifications;
identifying, by the processor (112), a food safety risk corresponding to at least one of a regulatory risk and a legal risk associated with the at least one food vertical mapped to the plurality of pre-defined prohibited ingredient classifications; and
monitoring periodically, by the processor (112), one or more food products with the identified food safety risk, and autoblocking the one or more food products at a listing level.
2. The method as claimed in claim 1, wherein the food safety risk is monitored for a food fraud activity in the e-commerce environment.
3. The method as claimed in claim 2, wherein the food fraud activity corresponds to a fraudulent activity, an adulterant activity, a prohibited activity, and a banned activity.
4. The method as claimed in claim 2, wherein the food fraud activity corresponds to at least one of a product concealment, an unapproved enhancement of the product, an addition of unregulated ingredients in the product, an addition of prohibited ingredients in the product, a mislabeling of the product, and a false claim of the product.
5. The method as claimed in claim 1, wherein the listing data comprises at least one of product ingredients, product claims, and product labelling data.
6. The method as claimed in claim 1, wherein the listing data corresponds to existing listing data and new listing data of the one or more food products.
7. The method as claimed in claim 1, wherein the plurality of pre-defined prohibited ingredient classifications comprises at least one of: prohibited ingredient categories, prohibited ingredient sub-categories, prohibited ingredient groups, prohibited ingredient sub-groups, prohibited ingredient buckets, and prohibited ingredient channels.
8. A system (110) for monitoring a food safety risk associated with a plurality of food products in an electronic commerce (e-commerce) environment, the system (110) comprising:
a processor (112);
a memory (116) coupled to the processor (112), wherein the memory (116) comprises processor (112) executable instruction, which on execution, cause the processor (112) to:
receive listing data corresponding to one or more food products, wherein the listing data comprises at least one of textual data, and media data;
extract one or more ingredients data from the received listing data;
determine at least one food vertical in a plurality of pre-defined food verticals, corresponding to the extracted one or more ingredients data;
map the at least one food vertical with a plurality of pre-defined prohibited ingredient classifications;
identify a food safety risk corresponding to at least one of a regulatory risk and a legal risk associated with the at least one food vertical mapped to the plurality of pre-defined prohibited ingredient classifications; and
monitor periodically one or more food products with the identified food safety risk, and autoblocking the one or more food products at a listing level.
9. The system (110) as claimed in claim 8, wherein the food safety risk is monitored for a food fraud activity in the e-commerce environment.
10. The system (110) as claimed in claim 9, wherein the food fraud activity corresponds to a fraudulent activity, an adulterant activity, a prohibited activity, and a banned activity.
11. The system (110) as claimed in claim 9, wherein the food fraud activity corresponds to at least one of a product concealment, an unapproved enhancement of the product, an addition of unregulated ingredients in the product, an addition of prohibited ingredients in the product, a mislabeling of the product, and a false claim of the product.
12. The system (110) as claimed in claim 8, wherein the listing data comprises at least one of product ingredients, product claims, and product labelling data.
13. The system (110) as claimed in claim 8, wherein the listing data corresponds to existing listing data and new listing data of the one or more food products.
14. The system (110) as claimed in claim 8, wherein the plurality of pre-defined prohibited ingredient classifications comprises at least one of: prohibited ingredient categories, prohibited ingredient sub-categories, prohibited ingredient groups, prohibited ingredient sub-groups, prohibited ingredient buckets, and prohibited ingredient channels.