DESC:CROSS-REFERENCE TO RELATED APPLICATIONS AND PRIORITY
The present application claims priority from an Indian Patent Application having the application number 202241003273, filed on January 20, 2022, incorporated herein by a reference.
TECHNICAL FIELD 5
The present subject matter described herein, in general, relates to the field of an agriculture produce warehouse management system. More specifically, the present subject matter discloses a system and a method for real-time monitoring health of an agricultural produce. More particularly, the present subject matter relates to a system and a method for real-time monitoring health of an agricultural 10 produce comprising a suction assembly, a gas sensor, and a control unit.
BACKGROUND
The subject matter discussed in the background section should not be assumed to be prior art merely because of its mention in the background section. Similarly, a problem mentioned in the background section or associated with the subject 15 matter of the background section should not be assumed to have been previously recognized in the prior art. The subject matter in the background section merely represents different approaches, which in and of themselves may also correspond to implementations of the claimed technology.
Conventionally, an agricultural produce, after it is harvested or after its 20 procurement form the farm, is stored in a warehouse, generally also known as cold storage. Globally, there is a significant wastage of the agricultural produce, ranging up to one third (28-30%) of the total agricultural produce stored, due to the inefficiency of the present agriculture produce warehouse management systems. The conventional warehouse does not have proper ventilation and 25 climatic conditions to store the agricultural produce for a longer span of time. However, there has been a vast development in the warehouse or warehouse management technologies and systems to improve the warehouse serviceability such that the agricultural produce can be stored for a reasonably long time.
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The significant development in sensor technology has also accelerated the technical advancement in a warehouse management system. Especially, typical gas sensors (like carbon dioxide sensor, ammonia sensor, etc.) are used to detect various gas emitted by the agricultural produce to assess the freshness of that agricultural produce. While it is easy to use such gas sensors, the cost of these gas 5 sensor systems is very high, making them unaffordable for small and medium scale warehouse systems. The effectiveness of these gas sensor systems also reduces quite drastically within a short span of its use in a warehouse containing large quantities of the agricultural produce. Moreover, it is not commercially feasible for the large warehouse systems also due to considerably huge 10 requirement of these gas sensor systems and their frequent maintenance issues.
Further, due to the use of a gas sensor for each gas emitted by the agricultural produce, the number of gas sensor for each agricultural produce also increases. As a result of this, the complexity of the gas sensor system increases which hampers the optimum functioning of the warehouse management system. Also, the use of 15 advanced technologies like internet of things (IoT) or other embedded systems become difficult and inefficient. The power consumption of these gas sensor systems is very high, ultimately making them economically impractical to use.
As known in the art, there have been many IoT-based systems for onion warehouse management present in the market. These IoT-based devices/systems 20 comprise a sensing unit and a microcontroller for detecting onset of the rotting of onion. These systems also comprise an analysis model, a forecasting model and a communication model. Further, the IoT device/system comprises various sensors like gas sensors which can sense carbon dioxide and ammonia separately and respectively. All the sensors are embedded in the hardware, wherein the sensors 25 capture environmental data which is further transmitted to the analysis model. The analysis model carries out the analysis of the environmental data and determine the onset of rotting of onions, detection and status of rotting of onions, as well as overall condition of onion stack. and the location of rotting of onions are sent to the farmer. Further, these systems also comprise a forecasting model, wherein the 30
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forecasting model forecasts the emissions of carbon dioxide and ammonia, which may forecast rotting of onions. The systems further comprise a communication model configured to alert the farmer regarding the onset of rotting of onions, detection and status of rotting of onions, and overall condition of onion stack. However, these IoT-based systems for onion warehouse management are unable 5 to efficiently compute an amount of the gases emitted by the agricultural produce, onion. Further, like every other available gas sensing module, each gas sensor sysyem in these IoT-based systems senses only one gas, carbon dioxide or ammonia. This makes it more complex and difficult for the control unit to analyse the data and correctly predict the freshness of the onion. This results in inefficient 10 functioning of such IoT-based systems. Furthermore, for achieving a reasonably appropriate efficiency of such gas sensing module, there are multiple gas sensors used for each gas emitted by onion (agricultural produce). Thus, the production cost as well as maintenance cost of such gas sensing modules becomes very high, again making them exorbitantly unaffordable for small, medium and even large 15 scale warehouse systems.
Thus, to address and discard the aforementioned and other related flaws, there is a long-felt need for a well-designed, technically advanced but with simplicity, and well-built system for real-time monitoring health of an agricultural produce that can provide an efficient real-time monitoring of health of the agricultural produce 20 in terms of its freshness or rottenness and reduction in wastage of the agricultural produce.
SUMMARY
This summary is provided to introduce concepts related to a system and a method for real-time monitoring health of an agricultural produce, and the concepts are 25 further described below in the detailed description. This summary is not intended to identify essential features of the claimed subject matter nor is it intended for use in determining or limiting the scope of the claimed subject matter.
In an embodiment, a system for real-time monitoring health of an agricultural produce comprises a suction assembly, a gas sensor, and a control unit. The 30
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suction assembly may be configured to suck one or more gases emitted by the agricultural produce such that the gas sensor is able to sense the one or more gases emitted by the agricultural produce. Further, the control unit may be configured to: pre-calibrated the gas sensor with respect to the atmospheric carbon dioxide (CO2) value to obtain a pre-calibrated gas sensor value in presence of ambient air; 5 determine an amount of the one or more gases emitted by the agricultural produce based upon a real-time atmospheric carbon dioxide (CO2) value, the pre-calibrated gas sensor value and a real-time gas sensor value in presence of the agriculture produce; and generate an alert indicating the health of the agricultural produce based upon the amount of the one or more gases emitted by the agricultural 10 produce.
In another embodiment, a method for real-time monitoring health of an agricultural produce comprises the steps of: pre-calibrating a gas sensor with respect to the atmospheric carbon dioxide (CO2) value to obtain a pre-calibrated gas sensor value in presence of ambient air; sensing one or more gases emitted by 15 the agricultural produce, by the gas sensor; receiving, a real-time atmospheric carbon dioxide (CO2) value, by a control unit; determining, an amount of the one or more gases emitted by the agricultural produce based upon the received real-time atmospheric carbon dioxide (CO2) value, the pre-calibrated gas sensor value and a real-time gas sensor value in presence of the agriculture produce, by the 20 control unit; and generating, an alert indicating the health of the agricultural produce based upon the amount of the one or more gases emitted by the agricultural produce, by the control unit.
BRIEF DESCRIPTION OF DRAWINGS
The detailed description is described with reference to the accompanying Figures. 25 The same reference numerals are used throughout the drawings to refer like features and components.
Figure 1 illustrates a schematic representation of a system 100 for real-time monitoring health of an agricultural produce in an isometric view, in accordance with an embodiment of the present disclosure. 30
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Figure 2 illustrates a flow chart representing a method 200 for real-time monitoring health of an agricultural produce, in accordance with an embodiment of the present disclosure.
Figure 3 illustrates a block diagram 300 of the system 100 for real-time monitoring health of the agricultural produce, in accordance with an embodiment 5 of the present disclosure.
DETAILED DESCRIPTION
Reference throughout the specification to “various embodiments,” “some embodiments,” “one embodiment,” or “an embodiment” means that a particular feature, structure, or characteristic described in connection with the embodiment 10 is included in at least one embodiment. Thus, appearances of the phrases “in various embodiments,” “in some embodiments,” “in one embodiment,” or “in an embodiment” in places throughout the 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 15 embodiments.
Further, the term “agricultural produce” may interchangeably be used for any agricultural produce like a “vegetable” or a “fruit” including onion, potato, apple, orange, or the like. The term “control unit” may interchangeably be used for “controller”, “microcontroller”, “processor”, “processing unit”, “microprocessor”, 20 or the like.
In an embodiment of the present disclosure, a system for real-time monitoring health of an agricultural produce is disclosed. The system for real-time monitoring health of the agricultural produce may comprise a suction assembly, a gas sensor, and a control unit. The agricultural produce may emit one or more than one gas at 25 a time during its shelf life. The suction assembly may further comprise a suction means which may be configured to suck one or more gases emitted by the agricultural produce such that the gas sensor is able to sense the one or more gases emitted by the agricultural produce. Further, the control unit may be configured to
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pre-calibrated the gas sensor with respect to the atmospheric carbon dioxide (CO2) value to obtain a pre-calibrated gas sensor value in presence of ambient air. Further, the control unit may determine an amount of the one or more gases emitted by the agricultural produce based upon a real-time atmospheric carbon dioxide (CO2) value, the pre-calibrated gas sensor value and a real-time gas sensor 5 value in presence of the agriculture produce. The control unit may further generate an alert indicating the health of the agricultural produce based upon the amount of the one or more gases emitted by the agricultural produce. Further, the amount of the one or more gases emitted by the agricultural produce is calculated parts per million (ppm) of the amount of the one or more gases sensed by the gas sensor. 10
In another embodiment, a method for real-time monitoring health of an agricultural produce is disclosed. The method for real-time monitoring health of an agricultural produce comprises the steps of: pre-calibrating a gas sensor with respect to the atmospheric carbon dioxide (CO2) value to obtain a pre-calibrated gas sensor value in presence of ambient air; sensing one or more gases emitted by 15 the agricultural produce, by the gas sensor; receiving, a real-time atmospheric carbon dioxide (CO2) value, by a control unit; determining, an amount of the one or more gases emitted by the agricultural produce based upon the received real-time atmospheric carbon dioxide (CO2) value, the pre-calibrated gas sensor value and a real-time gas sensor value in presence of the agriculture produce, by the 20 control unit; and generating, an alert indicating the health of the agricultural produce based upon the amount of the one or more gases emitted by the agricultural produce, by the control unit. Further, the amount of the one or more gases emitted by the agricultural produce, determined according to the method, may be determined as parts per million (ppm) of the amount of the one or more 25 gases sensed by the gas sensor.
In another exemplary embodiment, the gas sensor may be pre-calibrated with respect to the atmospheric carbon dioxide (CO2) value to obtain a pre-calibrated gas sensor value in presence of ambient air, by itself. Thus, the control unit may process only the determination of the amount of the one or more gases emitted by 30
8
the agricultural produce based upon the real-time atmospheric carbon dioxide (CO2) value, the pre-calibrated gas sensor value and the real-time gas sensor value in presence of the agriculture produce, and generation of the alert indicating the health of the agricultural produce based upon the amount of the one or more gases emitted by the agricultural produce. 5
In another embodiment, the pre-calibrated gas sensor value in presence of ambient air may be a gas sensor resistor value depending upon the amount or quantity of the one or more ambient gases sensed by the gas sensor. This pre-calibrated gas sensor value in presence of ambient air may be termed as “a pre-calibrated gas sensor resistance value” and may be represented as R0. Similarly, the real-time gas 10 sensor value in presence of the agriculture produce may be a gas sensor resistor value depending upon the amount or quantity of the one or more gases emitted by the agricultural produce and sensed by the gas sensor. This real-time gas sensor value in presence of the agriculture produce may be termed as “a real-time gas sensor resistance value” and may be represented as RLoad. 15
In another exemplary embodiment, the control unit may be an internet of things (IoT) based control unit. This IoT-based control unit may be configured to receive the atmospheric carbon dioxide (CO2) value from one or more authorized external sources. This external source may be accessed through internet or may be a memory device where the atmospheric carbon dioxide data may be stored. This 20 external source may also be a part of the system for real-time monitoring health of an agricultural produce.
In an embodiment of the present disclosure, the system for real-time monitoring health of the agricultural produce may further comprise a display dashboard or an LED (light emitting diode) indication system or a sound system. The IoT-based 25 control unit may be configured to display the generated alert and/or the determined amount of the one or more gases emitted by the agricultural produce on the display dashboard. Further, the IoT-based control unit may be configured to send and/or display the generated alert and/or the determined amount of the one or more gases emitted by the agricultural produce on a user device via a wireless 30
9
communication network. The IoT-based control unit may also be configured to output the alert via the sound system as a warning sound/buzzer.
The IoT-based control unit may further be configured to display the generated alert and/or the determined amount of the one or more gases emitted by the agricultural produce on the LED indication system. The LED indication system 5 may comprise a plurality of coloured LEDs for displaying various colours indicative of freshness condition of the agricultural produce. The LED indication system may display a first colour indication for fresh state, a second colour indication for moderately-fresh state, and a third colour indication for rotten state of the agricultural produce. 10
The IoT-based control unit may display the freshness condition of the agricultural produce on the display dashboard or the user device as a test message or a colour indicative of freshness condition of the agricultural produce. The freshness condition of the agricultural produce may be any one of - fresh, moderately fresh, and rotten. Further, a user may decide on its own about the freshness condition of 15 the agricultural produce based upon the displayed amount (in ppm) of the one or more gases emitted by the agricultural produce or displayed colour indicative of freshness condition of the agricultural produce.
In another embodiment, the pre-calibration of the gas sensor may be carried out in an ambient environment by switching on the gas sensor for up to 24- 48 hours. 20 The gas sensor may be any generic gas sensor not specifically designed to sense a particular gas.
In an embodiment, depending upon the type or make of the gas sensor, a pre-conditioning of the gas sensor may be performed before the pre-calibration step and a first pre-heating process of the gas sensor. In pre-conditioning step, the gas 25 sensor is kept switched ON continuously for a pre-defined pre-conditioning time based on the type or make of the gas sensor. This pre-conditioning time may vary in the range of 24 to 48 hours.
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In another exemplary embodiment, the pre-calibration of the gas sensor may be carried out after a pre-heating process of the gas sensor. The gas sensor may be pre-heated for a pre-determined time period varying for different make and/or type of the gas sensor used. The gas sensor may further be pre-heated before every use i.e., before sensing the one or more gases emitted by the agricultural produce 5 in the system for real-time monitoring health of the agricultural produce. This pre-heating period of the gas sensor, before every use and/or before the pre-calibration step, may be in the range of 15 to 25 minutes, preferably 20 minutes.
In an exemplary embodiment of the present disclosure, the system for real-time monitoring health of the agricultural produce may be configured to work in three 10 different modes, viz., without IoT and a user device, without IoT but with a user device, and with IoT and a user device.
Without IoT and a User Device:
In this mode, the control unit may be configured to display the generated alert on the LED indication system. The LED indication system may comprise a plurality 15 of coloured LEDs for displaying various colours indicative of freshness condition of the agricultural produce. The LED indication system may display a first colour indication (e.g., green colour LED) for fresh state, a second colour indication (e.g., orange colour LED) for moderately-fresh state, and a third colour indication (e.g., red colour LED)for rotten state of the agricultural produce. Further, the 20 control unit may output a waring buzzer sound via a speaker embedded in the system for real-time monitoring health of the agricultural produce.
Without IoT But With a User Device:
In this mode, the control unit may be configured to display the generated alert on a user device via a mobile application. The alert can be displayed on the user 25 device when the user device is in the vicinity of the system for real-time monitoring health of the agricultural produce. A local network may be enabled with or within the control unit for communicating with the user device. The alert may be displayed on the user device as a text or a colour representing the freshness condition of the agricultural produce or a numeric value of the amount 30
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(in ppm) of the one or more gases emitted by the agricultural produce. Further, the control unit may also output a waring buzzer sound via a speaker embedded in the user device for real-time monitoring health of the agricultural produce. The control unit may also output a visual colour indication on the user device corresponding to the colour indicated on the LED of the LED indication system. 5
With IoT and a User Device:
This mode of the system may be configured to be a combination of the above mentioned two modes. In this mode, the IoT-based control unit may be configured to display the generated alert on a user device via a mobile application. The alert can be displayed on the user device, by the IoT-based control unit, indicative of 10 freshness condition of the agricultural produce. The alert may further be generated on the user device as per a request generated by a user. A wireless data communication network (internet or local area network (LAN) or wireless area network (WAN) or cloud network or the like) may be enabled with or within the IoT-based control unit for communicating with the user device. The alert may be 15 displayed on the mobile application of the user device. Further, the user device may communicate with the IoT-based control unit using the mobile application. The alert may be displayed on the user device or a display dashboard of the system as a text or a colour representing the freshness condition of the agricultural produce or a numeric value of the amount (in ppm) of the one or more gases 20 emitted by the agricultural produce. Further, the IoT-based control unit may also output a waring buzzer sound via a speaker embedded in the user device for real-time monitoring health of the agricultural produce. Furthermore, the IoT-based control unit may also be configured to display the generated alert on the LED indication system. The LED indication system may further comprise a plurality of 25 coloured LEDs for displaying various colours indicative of freshness condition of the agricultural produce. The LED indication system may display a first colour indication (e.g., green colour LED) for fresh state, a second colour indication (e.g., orange colour LED) for moderately-fresh state, and a third colour indication (e.g., red colour LED) for rotten state of the agricultural produce. Further, the IoT-30
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based control unit may also output a waring buzzer sound via a speaker embedded in the system for real-time monitoring health of the agricultural produce.
Further, for conforming the system and the method disclosed for real-time monitoring health of the agricultural produce, the disclosed system capable of performing the disclosed method was used for onion as a non-limiting example of 5 the agricultural produce. An experiment was conducted for onion as a sample agriculture produce for sixty days. The amount of the one or more gases emitted by onion was determined on the basis of the disclosed method according to the present invention. This amount of the one or more gases emitted by onion was calculated with respect to the atmospheric carbon dioxide (CO2) in parts per 10 million (ppm) of CO2. The below table 1 shows the amount of the one or more gases emitted by onion in ppm corresponding to the various time intervals and the freshness of onion relative to the amount of the one or more gases emitted by onion.
Referring to the below table 1 and the disclosed method for real-time monitoring 15 health of the agricultural produce, here, onion, it was confirmed by the experimental findings and the freshness results of onion that the disclosed method is efficient and cost-effective in determining the health of agricultural produce - onion.
TABLE 1.
Day
Gases Sensed
(ppm)
Onion Health
Day
Gases Sensed
(ppm)
Onion Health
Day
Gases Sensed
(ppm)
Onion Health
1
468
Fresh
10
543
Fresh
45
584
Fresh
2
472
Fresh
15
557
Fresh
50
589
Fresh
3
470
Fresh
20
565
Fresh
55
647
Moderate Fresh
4
469
Fresh
25
564
Fresh
60
689
Moderate Fresh
5
470
Fresh
30
571
Fresh
65
765
Moderate Fresh
6
483
Fresh
35
580
Fresh
70
809
Rotten
7
486
Fresh
40
578
Fresh
75
825
Rotten
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Following observations can be made from the above experiment and table 1:
? When the amount of the one or more gases emitted by onion was in a range of 0-600 ppm, the onion were found to be fresh.
? When the amount of the one or more gases emitted by onion was in a range of 601-800 ppm, the onion were found to be moderately fresh. 5
? When the amount of the one or more gases emitted by onion was above 800 ppm, the onion were found to be rotten.
Now, the system and the method for real-time monitoring health of an agricultural produce may further be described according to the present disclosure with respect to the disclosed drawings: 10
Firstly, referring to Figure 1, a system 100 for real-time monitoring health of an agricultural produce is illustrated. The system 100 for real-time monitoring health of the agricultural produce may comprise a suction means 105, a gas sensor 103, and a control unit 102. The suction means 105 is configured to be a suction fan 105 which sucks one or more gases emitted by the agricultural produce such that 15 the gas sensor 103 is able to sense the one or more gases emitted by the agricultural produce. The gas sensor 103 is a generic gas sensor 103 configured to sense one or more gases in its surrounding atmosphere.
Further, the control unit 102 is configured to pre-calibrated the gas sensor 102 with respect to the atmospheric carbon dioxide (CO2) value for obtaining a pre-20 calibrated gas sensor value in presence of ambient air. The control unit 102 also determines an amount of the one or more gases emitted by the agricultural produce based upon a real-time atmospheric carbon dioxide (CO2) value, the pre-calibrated gas sensor value and a real-time gas sensor value in presence of the agriculture produce. The control unit 102 further generates an alert indicating the 25 health of the agricultural produce based upon the amount of the one or more gases emitted by the agricultural produce. The control unit 102 calculates the amount of the one or more gases emitted by the agricultural produce in parts per million (ppm) of the amount of the one or more gases sensed by the gas sensor.
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The system 100 further comprises a conduit 106, wherein the conduit 106 is any duct or a pipe or the like. The conduit 106 is inserted deep into a container filled with the agricultural produce till the bottom of the container. Further, the conduit 106 comprises openings or holes 107 for allowing proper suction of the one or more gases emitted by the agricultural produce so as to be effectively sensed by 5 the gas sensor 103. The is a mesh cover 101 at the top of the system 100 providing exit to the sucked one or more gases, emitted by the agricultural produce, into the atmosphere.
Furthermore, the system 100 comprises a plurality of light indicators (RGB LEDs) 104 for displaying the health of the agricultural produce. The plurality of light 10 indicators 104 comprises various colour LEDs for displaying the health of the agricultural produce, for example – Green colour LED for fresh state, Orange colour LED for moderately fresh state, and Red colour LED for rotten state of the agricultural produce.
In another embodiment, the system 100 also comprises a display dashboard (not 15 shown) and a buzzer (not shown) to display or output the health of the agricultural produce in terms of fresh, moderately fresh, and rotten or amount of the one or more gases emitted by the agricultural produce in ppm, and a warning buzzer for alerting a user of the system about the health of the agricultural produce.
Now, referring figure 2, a system 200 for real-time monitoring health of an 20 agricultural produce is illustrated comprising a gas sensor 201, a microcontroller 202 and a communication (Wi-Fi) module 203 embedded in the system 200, a power supply 204 for the system 200, a cloud setup 205 for the system 200 to communicate with a user device 206 via a mobile application. The system 200 works exactly as the system 100 for determining the amount of the one or more 25 gases emitted by the agricultural produce, except in the system 200, the microcontroller 202 is an internet of things (IoT) based control unit which is configured to interact with a user via the user device 206 through the mobile application over a cloud network 205. The system 200 enables the user, via the user device 206, to command the system for various functions like pre-calibrating 30
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the gas sensor 201 and/or start the sensing of the one or more gases emitted by the agricultural produce by the gas sensor 201 and/or determine the amount of the one or more gases emitted by the agricultural produce by the microcontroller 202 and/or fetch the amount of the one or more gases emitted by the agricultural produce from the system 200 or the like. Further, the microcontroller 202 is also 5 configured to send the data related to the sensed and/or calculated amount of the one or more gases emitted by the agricultural produce to the user device 206 over the cloud network 205 using the embedded communication module 203. The microcontroller 202 also sends the generated alert corresponding to the amount of the one or more gases emitted by the agricultural produce to the user device 206 10 in form of a display text message or a warning sound or a colour symbol representing the health of the agricultural produce.
Referring figure 3, a method 300 for real-time monitoring health of an agricultural produce is illustrated as a flow-chart according to an exemplary embodiment of the present disclosure. The method 300 for real-time monitoring health of an 15 agricultural produce further comprises the steps: pre-calibrating, 310, a gas sensor 103 with respect to the atmospheric carbon dioxide (CO2) value; sensing, 320, one or more gases emitted by the agricultural produce, by the gas sensor 103; receiving, 330, a real-time atmospheric carbon dioxide (CO2) value, by a control unit 102; determining, 340, an amount of the one or more gases emitted by the 20 agricultural produce, by the control unit 102; and generating, 350, an alert indicating the health of the agricultural produce, by the control unit 102.
Further, the amount of the one or more gases emitted by the agricultural produce, determined according to the method, is determined as parts per million (ppm) of the amount of the one or more gases sensed by the gas sensor 103. 25
At step 310, the gas sensor 103 is pre-calibrated with respect to the atmospheric carbon dioxide (CO2) value to obtain a pre-calibrated gas sensor value, represented as R0. Further, the pre-calibration step 310, of the gas sensor 103 is carried out in an ambient environment by switching on the gas sensor for up to 24-48 hours. 30
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The pre-calibrated gas sensor value in presence of ambient air is a gas sensor resistor value depending upon the amount or quantity of the one or more ambient gases sensed by the gas sensor 103. This pre-calibrated gas sensor value in presence of ambient air is termed as “a pre-calibrated gas sensor resistance value” and may be represented as R0. Similarly, the real-time gas sensor value in 5 presence of the agriculture produce may be a gas sensor resistor value depending upon the amount or quantity of the one or more gases emitted by the agricultural produce and sensed by the gas sensor 103. This real-time gas sensor value in presence of the agriculture produce is termed as “a real-time gas sensor resistance value” and may be represented as RLoad. 10
As a non-limiting example, a sensor MQ135 may be used as a gas sensor 103. The gas sensor 103 may be pre-calibrated by switching it ON continuously for 24 hours before using it for calibration. Here, calibration of the sensor, technically means to get the pre-calibrated gas sensor resistance value called R0 (Rzero) for any gas in known concentration. As per the present disclosure, carbon dioxide has 15 been considered in the ambient i.e., open air. A load resistance RL of 22KO may be used. The value of RL could be between 10KO to 47KO. The higher the load resistance value, the more sensitive the gas sensor 103 would be but having the RL of 22KO gives the most accurate and efficient readings for the used sensor MQ135. (an open library from https://github.com/GeorgK/MQ135 for calculating 20 R0 value in open air may be used by taking the reading of resistance using the function getRZero() provided by the library.) Taking 10 readings and finding the mean, and finally observing this value for about 30 minutes or until it gets stabilized gives the R0 for the sensor MQ135 as the gas sensor 103.
At step 320, sensing of the one or more gases emitted by the agricultural produce 25 by the gas sensor 103 is performed to get the “real-time gas sensor resistance value” (RLoad) in presence of the agricultural produce.
At step 330, receiving of a real-time atmospheric carbon dioxide (CO2) value by the control unit 102 is performed. This real-time atmospheric carbon dioxide
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(CO2) value may be stored in the memory of the control unit 102 or may be fetched by the control unit 102 in real-time.
At step 340, determining an amount of the one or more gases emitted by the agricultural produce by the control unit 102 is performed. The control unit 102 determines the amount of the one or more gases emitted by the agricultural 5 produce based upon the received real-time atmospheric carbon dioxide (CO2) value, the pre-calibrated gas sensor value (R0) and a real-time gas sensor value in presence of the agriculture produce (RLoad).
Further, the amount of the one or more gases emitted by the agricultural produce, determined according to the method, may be determined as parts per million 10 (ppm) of the amount of the one or more gases sensed by the gas sensor.
In another non-limiting example, after receiving the R0 value during the pre-calibration step, receiving real-time (current) ambient air CO2 value in ppm from an authorized source (e.g., trusted website sources like co2.earth, etc.) is performed. Now, considering the pre-calibrated R0, RL as 22 KO, as per the 15 aforementioned example, and the real-time atmospheric CO2 value and using the function getPPM() from the open library, as discussed in pre-calibration step 310, receiving the real-time amount of the one or more gases emitted by the agricultural produce in ppm with respect to the atmospheric CO2 value.
At step 350, generating an alert indicating the health of the agricultural produce 20 by the control unit 102 is performed. The control unit 102 generates the alert based upon the amount of the one or more gases emitted by the agricultural produce. The generated alert may be a text or a colour display or a sound indicative of the health or freshness state of the agriculture produce. Further, the generated alert may be displayed on a display dashboard of the disclosed system 25 100 or 20, or may be sent and displayed on a user device 206 via a mobile application over a wireless communication network 205.
Below are the advantages of the system for real-time monitoring health of the agricultural produce disclosed in the present disclosure:
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— Only one generic gas sensor used.
— Very low cost of production.
— Cheapest solution with higher efficiency in sensing the freshness of the agricultural produce.
— Low maintenance cost due to generic components used. 5
— Simplistic constructional details.
— Easy calibration of the gas sensor and/or the system.
Various modifications to the aforementioned embodiment or embodiments will be readily apparent to those skilled in the art and the generic principles herein may be applied to other embodiments. However, one of ordinary skill in the art will 10 readily recognize that the present disclosure is not intended to be limited to the embodiments illustrated but is to be accorded the widest scope consistent with the principles and features described herein.
The foregoing description shall be interpreted as illustrative and not in any limiting sense. A person of ordinary skill in the art would understand that certain 15 modifications could come within the scope of this disclosure.
The embodiments, examples, and alternatives of the preceding paragraphs or the description and drawings, including any of their various aspects or respective individual feature(s), may be taken independently or in any combination. Features described in connection with one embodiment are applicable to all embodiments 20 unless such features are incompatible.
DESCRIPTION OF SYMBOLS
100 : System for Real-time Monitoring Health of an Agricultural Produce
101 : Cover
102 : Control Unit 25
103 : Gas Sensor
104 : Indicators / LEDs
105 : Suction Means
19
106 : Conduit
107 : Conduit Openings
200 : Block Diagram of System 100
201 : Gas Sensor
202 : Control Unit (Microcontroller) 5
203 : Communication Module (Wi-Fi Module)
204 : Power Supply
205 : Network Server/Cloud Setup
206 : User Device (Mobile Application) ,CLAIMS:WE CLAIM:
1. A system (100) for real-time monitoring health of an agricultural produce, comprising:
a suction assembly (105) configured to suck one or more gases emitted by the agricultural produce; 5
a gas sensor (103) configured for sensing the one or more gases emitted by the agricultural produce; and
a control unit (102);
characterized in that,
the gas sensor (103) is configured to be pre-calibrated with 10 respect to the atmospheric carbon dioxide (CO2) value to obtain a pre-calibrated gas sensor value in presence of ambient air; and
the control unit (102) is configured to
determine an amount of the one or more gases emitted by the agricultural produce based upon a real-time 15 atmospheric carbon dioxide (CO2) value, the pre-calibrated gas sensor value and a real-time gas sensor value in presence of the agriculture produce, and
generate an alert indicating the health of the agricultural produce based upon the amount of the one or 20 more gases emitted by the agricultural produce.
2. The system (100) as claimed in claim 1, wherein the pre-calibrated gas sensor value in presence of ambient air is a pre-calibrated gas sensor resistance value (R0) and the real-time gas sensor value in presence of the 25 agriculture produce is a real-time gas sensor resistance value (RLoad).
3. The system (100) as claimed in claim 1, wherein the control unit (102) is an internet of things (IoT) based control unit configured to receive the atmospheric carbon dioxide (CO2) value from authorized external 30
21
sources, wherein the alert is displayed on a system dashboard (104) and/or a user display device (206) by the IoT based control unit.
4. The system (100) as claimed in claim 3, wherein the alert generated by the control unit (102) is displayed as a text and/or colour indicative of 5 freshness condition of the said agriculture produce, and wherein the freshness condition is one of fresh, moderately fresh, and rotten.
5. The system (100) as claimed in claim 4, wherein the agricultural produce is an onion, and wherein the onion is detected to be fresh, moderately 10 fresh, or rotten when the amount of the one or more gases emitted by the agricultural produce is in the range of 0-600 ppm, 601-800 ppm and above 800 ppm respectively.
6. The system (100) as claimed in claim 1, wherein the agricultural produce 15 is a vegetable or a fruit.
7. A method (300) for real-time monitoring health of an agricultural produce, the method comprising:
pre-calibrating (310), a gas sensor (103) with respect to the 20 atmospheric carbon dioxide (CO2) value to obtain a pre-calibrated gas sensor value in presence of ambient air;
sensing (320), by the gas sensor (103), one or more gases emitted by the agricultural produce;
receiving (330), by a control unit (102), a real-time atmospheric 25 carbon dioxide (CO2) value;
determining (340), by the control unit (102), an amount of the one or more gases emitted by the agricultural produce based upon the received real-time atmospheric carbon dioxide (CO2) value, the pre-calibrated gas sensor value and a real-time gas sensor value in 30 presence of the agriculture produce; and
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generating (350), by the control unit (102), an alert indicating the health of the agricultural produce based upon the amount of the one or more gases emitted by the agricultural produce.
8. The method (300) as claimed in claim 7, wherein the pre-calibrated gas 5 sensor value in presence of ambient air is a pre-calibrated gas sensor resistance value (R0) and the real-time gas sensor value in presence of the agriculture produce is a real-time gas sensor resistance value (RLoad).
9. The method (300) as claimed in claim 7, wherein the step of pre-10 calibrating (310) the gas sensor is carried out in an ambient environment by switching on the gas sensor (103) for up to 24- 48 hours.
10. The method (300) as claimed in claim 7, generating (350) the alert comprises displaying a text and/or colour indicative of freshness 15 condition of the said agriculture produce, and wherein the freshness condition is one of fresh, moderately fresh, and rotten.
11. The method (300) as claimed in claim 10, wherein the agricultural produce is an onion, and wherein the onion is detected to be fresh, 20 moderately fresh, or rotten when the amount of the one or more gases emitted by the agricultural produce is in the range of 0-600 ppm, 601-800 ppm and above 800 ppm respectively.
12. An IoT environment (200) comprising: a pre-calibrated gas sensor (201), 25 a suction assembly, a control unit (202) and a user display device (206) configured to implement the method as claimed in claims 7-11.