Claims:1. An automated portable milk adulterant detection system, comprising:
a multi-spectral sensor, wherein said multi-spectral sensor [102] assembled with a milk sample holder [103];
a central microcontroller unit, wherein said central microcontroller unit [101] provisioned with necessary data pre-processing algorithm;
a wireless fidelity (Wi-Fi) module, wherein said Wi-Fi module [105] interfaced with said central microcontroller,
wherein said Wi-Fi module [105] provisioned to transmit the data, wirelessly;
a memory device, wherein said memory device [104] provisioned to store the pre-processed data;
a cloud internet server, wherein said cloud internet server [200] collects the data from the automated portable milk adulterant detection system,
wherein said cloud internet server [200] configured to maintain the historic information and deliver the data to a plurality of remote users,
wherein said remote users obtained the data on their mobile phone device [300];
a display unit, wherein said display unit [106] provisioned to display the adulterant details; and
a battery device, wherein said battery device [107] made the automated portable milk adulterant detection system as a portable instrumentation device.

2. The automated portable milk adulterant detection system as claimed in claim 1, wherein said multi-spectral sensor [102] provisioned to have 18 channel to produce a data wavelength ranges from 410 nm to 940 nm.

3. The automated portable milk adulterant detection system as claimed in claim 2, wherein said wavelength covers various bands, including ultraviolet, visible region and near infrared (NIR) and configured to have six channels for each band group to confirm an improved accuracy in the detection process.
4. The automated portable milk adulterant detection system as claimed in claim 1, wherein said central microcontroller [101] embodied with data pre-processing algorithm configured to consider the data from 18 channel fed by the multi-spectral sensor.

5. The automated portable milk adulterant detection system as claimed in claim 1, wherein said Wi-Fi module provisioned to communicate the cloud internet server, wirelessly.

6. The automated portable milk adulterant detection system as claimed in claim 5, wherein said cloud internet server provisioned to analyze the spectral data with an advent of neural network algorithm.

7. The automated portable milk adulterant detection system as claimed in claim 6, wherein said neural network algorithm provisioned to have a reduced response time as well as training time by employing peak detection algorithm and threshold unit.

8. The automated portable milk adulterant detection system as claimed in claim 1, wherein said automated portable milk adulterant detection system provisioned to detect the presence of adulterant, including sodium salicylate, ammonium sulphate, dextrose, hydrogen peroxide in milk and milk powder.

9. The automated portable milk adulterant detection system as claimed in claim 1, wherein said milk adulterant detection system observed with a response time between 1.9 seconds and 0.475 seconds.

10. The automated portable milk adulterant detection system as claimed in claim 1, wherein said automated portable milk adulterant detection system and methods of acquiring spectral data, pre-processing in the central microcontroller, transmitting and processing to the cloud internet server, said detection system and method comprising steps of:
acquiring a plurality of spectral data using a multi-spectral sensor [102];
providing a pre-processing of the acquired data using a central microcontroller [101];
transmitting the pre-processed data using a Wi-Fi module [105], wirelessly to a cloud internet server [200];
processing the data by applying an artificial intelligence algorithm constituted with neural network; and
delivering the detected adulterant information to a plurality of remote users, wirelessly.
, Description:[0030] The present invention as herein described an automated system for the detection of milk and milk powder adulterant presence with due support from artificial intelligence algorithm, in real time.
[0031] Referring to Figure 1, in an embodiment, the assembly of functional components provisioned in the automated portable milk adulterant detection system, comprises a multi-spectral sensor, wherein said multi-spectral sensor [102] assembled with a milk sample holder [103], a central microcontroller unit, wherein said central microcontroller unit [101] provisioned with necessary data pre-processing algorithm, a wireless fidelity (Wi-Fi) module, wherein said Wi-Fi module [105] interfaced with said central microcontroller [101], wherein said Wi-Fi module [105] provisioned to transmit the data, wirelessly, a memory device, wherein said memory device [104] provisioned to store the pre-processed data, a cloud internet server, wherein said cloud internet server [200] collects the data from the automated portable milk adulterant detection system [100], wherein said cloud internet server [200] configured to maintain the historic information and deliver the data to a plurality of remote users using mobile phone devices [300], a display unit, wherein said display unit [106] provisioned to display the adulterant details, and a battery device, wherein said battery device [107] made the automated portable milk adulterant detection system [100] as a portable instrumentation device.

[0032] Referring to Figure 2, in an aspect, the functional description in the form of block diagram representation of said automated portable milk adulterant detection system illustrated, accordingly spectrum of data captured using multi-spectral sensor [102] which considered as a beginning of operation involved. The variation of distance, ambient light condition and acquisition angle affect the accuracy of detection of milk adulterant which is addressed in the present invention by design of an adaptive threshold unit and employing 18 different channel data for reliability. Wherein said 18 channel data mostly has redundant information which is unnecessarily increasing the training time and response time which is addressed by means of novel adaptive threshold unit which select best 6 channel alone to reduce the response and training time. The present invention considered to reduce the response time from 1.9 sec to 0.475 seconds. Eventually, the training time has been reduced from 40 minutes to 7 minutes. Wherein said multi-spectral sensor [102] consists of 18 channels which equipped to produce data from 410 nm to 940 nm wavelength. Wherein said 18 channel data used to make reliable adulterant detection applying to neural network algorithm. The present invention has made the improvement in reducing the response time and training time and the reduction in training time is achieved by employing peak detection algorithm and threshold unit. The threshold unit designed to compare the peak value with the threshold value and select appropriate best channel for training the neural network.
[0033] An adaptive threshold unit is designed which considering the neural network classifier output as an input to adapt the threshold value such that the classifier classification accuracy is maximized. This novel adaptive threshold unit taking care of variation in the input data due to ambient light condition variation, variation in the distance of acquiring the data and variation in the angle of data acquisition.

Application example:
[0034] Milk producer and co-operative societies and in the dairy industries for the adulterant identification present in the milk. It provides real time, portable analysis. Industrial Food products produced from the milk can be able to avoid the hazardous adulteration.
Benefits:
[0035] It also helps the end consumer in buying adulterant free milk products. Since every day the consumers cannot be able to analyze the milk for adulteration on the laboratory. Since it is low cost, rapid analysis kit, portable and delivers better accuracy in real-time.

TECHNICAL ADVANCEMENTS:

[0036] The present invention is portable one which support for on- field adulteration detection.
[0037] Said invention provisioned with a product case which is designed in such a way to operate with single key option with simplicity.
[0038] Said invention is portable, non- destructive and capable of providing real time results.
[0039] Said invention configured to capture data from three different bands called UV, Visible and NIR with six channels for each group in a total of 18 channels to improve detection accuracy.
[0040] Said invention found to be with an improved efficiency of 100 % with the help of artificial algorithm.
[0041] Said invention configured as an Internet of Things (IoT) device to update the detected adulterant in the web server to enable accessing the result from anywhere.
[0042] The variation of distance, ambient light condition and acquisition angle affect the accuracy of detection of milk adulterant which is addressed in the present invention by introducing an adaptive threshold unit and employing 18 different channel data for reliability.
[0043] Said 18 channel data mostly has redundant information which is unnecessarily increasing the training time and response time which is addressed by means of novel adaptive threshold unit which select best 6 channel alone to reduce the response and training time.
[0044] The present invention observed to be having a response time between 1.9 sec and 0.475 seconds.
[0045] The training time associated with neural network has been reduced from 40 minutes to 7 minutes in the present invention.

[0046] The embodiments herein and the various features and advantageous details thereof are explained with reference to the non-limiting embodiments in the following description. Descriptions of well-known components and processing techniques are omitted to not unnecessarily obscure the embodiments herein. The examples used herein are intended merely to facilitate an understanding of ways in which the embodiments herein may be practiced and to further enable those of skill in the art to practice the embodiments herein. Accordingly, the examples should not be construed as limiting the scope of the embodiments herein.
[0047] Throughout this specification the word “comprise”, or variations such as “comprises” or “comprising”, will be understood to imply the inclusion of a stated element, integer or step, or group of elements, integers or steps, but not the exclusion of any other element, integer or step, or group of elements, integers or steps.
[0048] The use of the expression “at least” or “at least one” suggests the use of one or more elements or ingredients or quantities, as the use may be in the embodiment of the disclosure to achieve one or more of the desired objects or results.
[0049] Any discussion of documents, acts, materials, devices, articles or the like that has been included in this specification is solely for the purpose of providing a context for the disclosure. It is not to be taken as an admission that any or all these matters form a part of the prior art base or were common general knowledge in the field relevant to the disclosure as it existed anywhere before the priority date of this application.
[0050] The numerical values mentioned for the various physical parameters, dimensions or quantities are only approximations and it is envisaged that the values higher/lower than the numerical values assigned to the parameters, dimensions or quantities fall within the scope of the disclosure, unless there is a statement in the specification specific to the contrary.
[0051] While considerable emphasis has been placed herein on the components and component parts of 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 disclosure. These and other changes in the preferred embodiment as well as other embodiments of the disclosure 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 interpreted merely as illustrative of the disclosure and not as a limitation.
[0052] The foregoing description comprises illustrative embodiments of the present invention. Having thus described exemplary embodiments of the present invention, it should be noted by those skilled in the art that the within disclosures are exemplary only, and that various other alternatives, adaptations, and modifications may be made within the scope of the present invention. Many modifications and other embodiments of the invention will come to mind to one skilled in the art to which this invention pertains having the benefit of the teachings presented in the foregoing descriptions. Although specific terms may be employed herein, they are used only in generic and descriptive sense and not for purposes of limitation. Accordingly, the present invention is not limited to the specific embodiments illustrated herein.