Description:FIELD OF THE INVENTION

[0001] The present invention relates to the field of agricultural post-harvest management and storage systems, and more particularly, to adaptive cold storage system for farm produce by performing real-time quality assessment of produce conditions and storing the produce at required conditions, thereby improving storage efficiency, reducing spoilage, and extending their shelf life.

BACKGROUND OF THE INVENTION

[0002] The storage and preservation of farm produce is an important part of the agricultural supply chain. Once harvested, fruits and vegetables must be handled and stored properly to prevent spoilage, maintain nutritional value, and reduce wastage. Efficient storage systems help ensure that farm produce remains fresh during transit and until it reaches the market or consumer. In cold storage systems, controlling temperature, humidity, and airflow is critical to slow down spoilage and extend shelf life. In many cases, different types of farm produce require different storage conditions. Additionally, the quality of produce must be regularly checked, and action should be taken based on its condition. Managing all of these factors manually can be time-consuming, inconsistent, and lead to unnecessary losses.

[0003] Traditionally, cold storage facilities rely on fixed-temperature chambers where different types of produce are stored together under general environmental conditions. These systems usually lack real-time quality monitoring and do not provide the ability to respond dynamically to changing conditions or produce quality. Manual sorting of produce is labour-intensive and often based on visual inspection, which may not accurately identify internal or chemical signs of spoilage. Also, most systems do not include features that allow intelligent shifting of produce between chambers based on its condition or future storage needs, resulting in inefficiencies and spoilage. In conventional systems, there is limited use of sensors or automation to monitor humidity, temperature, gas emission, or internal quality of the stored produce. Often, the same cooling conditions are applied throughout the facility, even if the chambers are empty, which leads to unnecessary power consumption.

[0004] US6318111B1 discloses a belt conveyor device for transporting cold foods capable of controlling the quality and sanitation of foods, without requiring the necessity of cooling a whole processing room and without being affected by an environmental temperature, by forming cooling spaces only in the food transporting spaces of a conveyor for processing and transporting cold foods. Wherein cold air outlets and cold air suction ports are provided on the right and left sides of the transporting spaces of the belt conveyor opposedly to each other across the belt conveyor, cooling parts are provided in spaces sandwiched between the upper and lower sides of the running belt, food transporting spaces on the surfaces of the belt conveyor in a working space are formed, by a cool air flow from the cold air outlets to the cold air suction ports, into the cooled spaces having temperatures equivalent to a food refrigerating temperature of approx. 10-C. or below which is lower than the temperature in the working space, and cool air is injected against the rear surface of the belt so as to cool the rear surface of the belt.

[0005] US20180259237A1 discloses a cooling system comprising a mobile container, conveyor system, and sensor feedback system. Container includes at least a first, second, and third section. First section holds at least one pallet containing produce. Second section includes a cooling mechanism to cool the produce within the at least one pallet to an optimal temperature. Third section includes the cooling mechanism to maintain the cooled produce in the at least one pallet at the optimal temperature. Conveyor system may be used to convey the at least one pallet across the cooling system. Sensor feedback system is configured to continuously measure and track at least the weight of the at least one pallet and temperature of the produce within the at least one pallet as the at least one pallet is conveyed across the cooling system.

[0006] Conventionally, many systems have been developed in order to preserve and transport farm produce in controlled environments. However, the systems mentioned in the prior arts have limitations pertaining to relying on manual sorting, and cannot adjust storage conditions based on varying produce needs. Additionally, these systems often result in energy wastage by maintaining cooling in empty or underused chambers.

[0007] In order to overcome the aforementioned drawbacks, there exists a need in the art to develop a system that requires to be capable of real-time quality assessment, automated categorization, and dynamic storage based on produce condition. The developed system also needs to manage storage transitions using predictive modelling, optimize environmental conditions for each chamber, and reduce energy consumption by adapting operations.

OBJECTS OF THE INVENTION

[0008] The principal object of the present invention is to overcome the disadvantages of the prior art.

[0009] An object of the present invention is to develop a system that is capable of automatically sorting farm produce based on quality and directing it to suitable storage environments without manual intervention, thereby reducing post-harvest losses.

[0010] Another object of the present invention is to develop a system that is capable of maintaining different storage conditions for various categories of farm produce, ensuring extended freshness and shelf life.

[0011] Another object of the present invention is to develop a system that is capable of identifying inedible or spoiled produce in view of preventing its entry into the storage cycle to improve food safety and efficiency.

[0012] Yet another object of the present invention is to develop a system that is capable of adjusting storage operations dynamically based on real-time sensor data and predicted changes in the condition of the farm produce.

[0013] The foregoing and other objects, features, and advantages of the present invention will become readily apparent upon further review of the following detailed description of the preferred embodiment as illustrated in the accompanying drawings.

SUMMARY OF THE INVENTION

[0014] The present invention relates to an adaptive cold storage system for farm produce that is capable of effectively sorting and storing farm produce at specific required conditions and ensure relocation of farm goods according to their real-time condition to maintain quality and extend shelf life in changing environmental or produce conditions.

[0015] According to an embodiment of the present invention, an adaptive cold storage system for farm produce is disclosed, comprising a hopper configured to receive multiple farm produce units, the hopper being equipped with a motorized flap and a vibrating motor to dispense one produce item at a time, a conveyor arrangement is installed beneath the hopper to move the produce at a pre-defined speed, a quality assessment module disposed adjacent to the conveyor includes a sensor suite comprising near-infrared spectroscopy (NIR) sensor, hyperspectral imaging, and odor sensor to determine the quality and categorize the produce accordingly, a set of cold storage chambers maintained at varying ambient conditions is positioned alongside the conveyor, each chamber equipped with a motorized door and a suction mechanism to intake the categorized produce, a processor interlinked with the motorized doors, suction mechanism, and the quality assessment module regulates produce allocation.

[0016] According to another embodiment of the present invention, the present invention further comprises a sensing module in each chamber with comprising red-green-blue (RGB) camera, near-infrared spectroscopy (NIR) sensor, hyperspectral imaging, gas sensor, and weight sensor, all connected to a Markov Chain Principle-based prediction module which anticipates future produce state and commands the processor to dynamically shift produce between chambers, the chambers include robotic arms with grippers for transferring produce, a level sensor in each chamber aids energy efficiency by disabling HVAC units when chambers are empty, the system further includes a computing unit for wireless monitoring, and the conveyor arrangement is embodied as an omnidirectional belt for versatile operation.

[0017] While the invention has been described and shown with particular reference to the preferred embodiment, it will be apparent that variations might be possible that would fall within the scope of the present invention.

BRIEF DESCRIPTION OF THE DRAWINGS

[0018] These and other features, aspects, and advantages of the present invention will become better understood with regard to the following description, appended claims, and accompanying drawings where:
Figure 1 illustrates an isometric view of an adaptive cold storage system for farm produce.

DETAILED DESCRIPTION OF THE INVENTION

[0019] The following description includes the preferred best mode of one embodiment of the present invention. It will be clear from this description of the invention that the invention is not limited to these illustrated embodiments but that the invention also includes a variety of modifications and embodiments thereto. Therefore, the present description should be seen as illustrative and not limiting. While the invention is susceptible to various modifications and alternative constructions, it should be understood, that there is no intention to limit the invention to the specific form disclosed, but, on the contrary, the invention is to cover all modifications, alternative constructions, and equivalents falling within the spirit and scope of the invention as defined in the claims.

[0020] In any embodiment described herein, the open-ended terms "comprising," "comprises,” and the like (which are synonymous with "including," "having” and "characterized by") may be replaced by the respective partially closed phrases "consisting essentially of," consists essentially of," and the like or the respective closed phrases "consisting of," "consists of, the like.

[0021] As used herein, the singular forms “a,” “an,” and “the” designate both the singular and the plural, unless expressly stated to designate the singular only.

[0022] The present invention relates to an adaptive cold storage system for farm produce that is capable of handling the classification, and storage of agricultural goods in a controlled manner to preserve their condition, reduce waste, and improve operational efficiency through automated adaptive and predictive control strategies.

[0023] Referring to Figure 1, an isometric view of an adaptive cold storage system for farm produce is illustrated, comprises of a hopper 101 with a motorized flap 102, a conveyor arrangement 103 positioned beneath the hopper 101, a quality assessment module 104 disposed adjacent to the conveyor comprises of a waste container 104a, a pusher 104b, and a hyperspectral imaging 104c, cold storage chambers 105 arranged in series alongside the conveyor arrangement 103, each chamber 105 equipped with a motorized door 106 and suction mechanism 107, and robotic arms 108 with grippers 109 mounted inside each chamber 105.

[0024] The present invention discloses a system to automatically classify, handle, and preserve farm produce based on real-time quality and environmental data. “Farm produce” term herein refers to the products harvested from agricultural activities, especially crops cultivated for food consumption, processing, or sale. These typically include a wide range of perishable items such as fruits, vegetables, leafy greens, roots and tubers, legumes and pods and other perishables items like herbs, mushrooms, or sprouts.

[0025] The system is connected to a computing unit operated by the user to control the operations of the system. The user accesses a user interface which is installed in a computing unit linked with an inbuilt microcontroller wirelessly. The microcontroller, mentioned herein, is preferably an Arduino microcontroller. The Arduino microcontroller used herein controls the overall functionality of the components linked to it. The Arduino microcontroller is an open-source programming platform. The microcontroller receives the data from various electronic units and generates a command signal for further processing.

[0026] The computing unit and the microcontroller are linked by means of a communication module. The communication module includes, but not limited to Wi-Fi (Wireless Fidelity) module, Bluetooth module, GSM (Global System for Mobile Communication) module. The Wi-Fi module contains transmitters and receivers that use radio frequency signals to transmit data wirelessly to the microcontroller. The wireless module typically includes components such as antennas, amplifiers, and processors to facilitate communication and further connected to networks such as Wi-Fi, Bluetooth, or cellular networks, allowing systems to exchange information over short or long distances for communication of wireless commands to facilitate operations of the system.

[0027] The system comprises a hopper 101 designed to receive multiple farm produce items, manually fed by a user. The hopper 101 is fitted with a motorized flap 102 and a vibrating motor to dispense one produce item at a time for the storage. The motorized flap 102 is typically driven by a servo motor or stepper motor, which is controlled by a microcontroller. When the system receives a signal to dispense a produce item, the motor rotates the flap 102 to an open position, allowing a single item to fall through the outlet. Immediately after dispensing, the flap 102 returns to its closed position to prevent additional items from passing through. The timing and duration of the flap's 102 opening are precisely controlled to ensure only one item is released at a time, enabling accurate and consistent handling.

[0028] The vibrating motor is mounted on the side or base of the hopper 101 and plays a critical role in maintaining a smooth flow of produce toward the outlet. When activated by the microcontroller, the motor generates rapid, controlled vibrations that shake the hopper 101 and its contents. This motion helps to loosen any items that may be sticking together or lodged due to their shape, size, or surface texture. By reducing friction and preventing the formation of blockages at the bottom of the hopper 101, the vibration ensures that produce items continue to move toward the motorized flap 102.

[0029] The motorized flap 102 includes a spring arrangement allowing automatic return to its initial position after dispensing. When the microcontroller activates the motor, the flap 102 is rotated or lifted to open, allowing one item to pass through. As this happens, the spring attached to the flap 102 or its hinge point is either compressed or stretched, storing potential energy. Once the item is released and the motor stops or reverses, the tension in the spring forces the flap 102 back to its original closed position without requiring additional motor input.

[0030] A conveyor arrangement 103 is positioned beneath the hopper 101 to convey each dispensed item at a defined speed toward the classification zone to ensure consistent handling and routing flexibility. The conveyor arrangement 103 used herein is an omnidirectional conveyor belt. The omnidirectional conveyor belt works by using a series of small, independently rotating rollers embedded on the surface of the belt. The belt allows movement in multiple directions such as forward, backward, sideways, or diagonally, without repositioning the object or changing the belt’s orientation. The belt includes motorized actuators that are activated by the microcontroller, upon sending a signal to a motor linked with the actuators that control the rotation and direction of each roller. By coordinating the speed and direction of individual rollers, the system precisely manoeuvres farm produce to different locations, reorient them, or sort them dynamically while they remain on the belt.

[0031] Adjacent to the conveyor, the quality assessment module 104 is mounted within the system that conducts real-time evaluation of each item’s quality. The quality assessment module 104 utilizes a sensor suite comprising near-infrared spectroscopy (NIR) sensors, hyperspectral imaging 104c, and an odor sensor.

[0032] Upon activation by the microcontroller, the near-infrared spectroscopy (NIR) sensor begins its analysis by directing near-infrared light onto the surface of the produce item. Different chemical compounds within the item absorb and reflect this light in unique ways. By measuring the reflected wavelengths, the sensor assesses internal qualities such as sugar content, moisture level, and overall ripeness. This non-destructive method provides valuable insight into the internal composition of the fruit without cutting or damaging it.

[0033] The hyperspectral imaging sensor 104c also activates under the microcontroller’s command, capturing high-resolution spectral data across a wide range of wavelengths for each pixel of the produce surface. The hyperspectral imaging 104c collects information from both visible and non-visible spectrums, allowing the system to detect subtle differences in color, texture, and composition.

[0034] Simultaneously, the odor sensor, often designed as an electronic nose (e-nose), detects volatile organic compounds (VOCs) emitted by the produce. As fruits ripen or begin to spoil, they release specific gases that the sensor identifies and quantify. By analysing the type and concentration of these VOCs, the sensor helps determine the freshness of the item, detect early signs of spoilage, or even identify contamination.

[0035] If the farm produce is found to be inedible, as identified through this assessment module, the farm produce is removed into a waste container 104a. A pusher 104b is integrated with the system to push the inedible produce into the container 104a. The assessment module sends the signal regarding the inedible produce to the microcontroller, which in turn activates a motor linked with the pusher 104b to discard the farm produce. The motor drives the pusher 104b forward, physically pushing the item off the conveyor and into a dedicated waste container 104a. After the item is discarded, the pusher 104b retracts to its original position, ready for the next activation. This automated rejection ensures that only acceptable produce continues through the system, while defective or spoiled items are efficiently removed without manual intervention.

[0036] Following quality assessment, graded produce is directed toward one of a series of cold storage chambers 105 installed in a series adjacent to the conveyor arrangement 103. Each chamber 105 is maintained under different ambient conditions by an individual HVAC (Heating, Ventilation, and Air Conditioning) unit. This unit regulates the temperature, humidity, and air quality within a specific environment, such as the cold storage chambers 105 used for farm produce. In this context, each HVAC unit controls the ambient conditions inside its assigned chamber 105 to create an optimal environment tailored to the type and ripeness of the stored produce. The unit works by circulating cooled or heated air through the chamber, adjusting humidity levels to prevent moisture loss or excess condensation, and filtering the air to reduce contaminants and maintain freshness.

[0037] There are four chambers 105 in the system to store different farm produce as per specific requirement. Chamber A, known as the Deep Freeze chamber maintains temperatures between -5°C to 0°C and is ideal for over-ripe or highly perishable items that require immediate slowing of spoilage processes. Chamber B, the Cooler chamber, operates between 1°C to 5°C and is suitable for ripe fruits that are ready for consumption but still need preservation to extend their shelf life. Chamber C, or the Moderate chamber, ranges from 6°C to 10°C and is best for semi-ripe fruits that continue to mature slowly under controlled conditions. Finally, Chamber D, the Ambient chamber, maintains temperatures between 10°C to 20°C, accommodating fewer sensitive fruits that tolerate warmer conditions without significant quality loss. This temperature-based chamber system ensures that different fruit types are stored in optimal conditions based on their ripeness and sensitivity.

[0038] Each chamber 105 integrates a motorized door 106 with suction mechanism 107 to intake items as directed by the microcontroller, based on the data provided by the assessment module. According to the data from the assessment module, the conveyor arrangement 103 moves to the farm produce near the appropriate chamber. Once the farm produce is positioned, the microcontroller sends a signal to a motor linked with the door 106 to allow the farm produce get stored within the chamber.

[0039] The motorized door 106 with suction integrated into each chamber 105 operates as an automated access point controlled by the microcontroller based on data from the assessment module. When the conveyor positions the farm produce near the designated chamber, the microcontroller sends a signal to activate the motor linked to the door 106. This motor drives the door 106 to open smoothly, allowing the produce to be transferred into the chamber. The suction mechanism 107helps create a gentle airflow that assists in drawing the item into the chamber 105 and minimizing air exchange between the chamber 105 and the external environment, which helps maintain the controlled temperature and humidity inside. After the produce is stored, the motor automatically closes the door 106, sealing the chamber 105 to preserve the ideal storage conditions. The microcontroller ensures correct routing of each item into the respective chamber 105 based on quality.

[0040] A sensing module is integrated wwithin each chamber, including a red-green-blue (RGB) camera, NIR (near-infrared) sensor, hyperspectral imager, gas sensor, and weight sensor, continuously monitors produce.

[0041] High-resolution RGB cameras are used to visually inspect the surface of farm produce. Through image processing and machine learning techniques, the system detects and classifies external defects such as bruises, rot, mold, discolouration, cuts or blemishes. Pattern recognition and colour analysis protocols help distinguish between acceptable variations and defects, enabling real-time decision-making. The RGB camera in each chamber 105 captures high-resolution color images of the stored produce, providing visual information about the surface appearance, including color changes, bruising, or decay. This real-time visual data helps detect external defects or ripeness variations, allowing the system to monitor the produce’s condition continuously.

[0042] NIR is employed to evaluate internal quality attributes that are not visible externally. This includes measuring sugar content (Brix level), firmness, moisture levels and detecting early signs of internal spoilage such as browning or tissue breakdown. For example: Brix level range of apple is 11-16 °Bx. This provides rapid, non-invasive insights into fruit ripeness and freshness. The NIR sensor operates by emitting near-infrared light onto the produce and measuring the reflected wavelengths. This non-destructive technique provides insights into the internal quality of the fruit, such as moisture content, sugar levels, and firmness, which are key indicators of ripeness and freshness during storage.

[0043] The hyperspectral imager captures detailed spectral data across a wide range of wavelengths for every pixel in the image. By analyzing this spectral information, it identifies subtle chemical and physical changes in the produce that are not visible to the naked eye, such as early signs of spoilage, fungal infections, or nutrient deficiencies. Hyperspectral imager combines both imaging and spectroscopy, capturing data across a wide range of wavelengths beyond the visible spectrum. This allows for comprehensive analysis of both surface and subsurface properties. It is highly effective in identifying hidden bruises, fungal infections and subtle variations in skin or internal composition that RGB cameras or NIR might miss individually.

[0044] The gas sensor detects volatile organic compounds (VOCs) and other gases emitted by the produce as it ripens or deteriorates. By continuously monitoring the concentration and composition of these gases, the sensor provides an early warning system for over ripeness, fermentation, or spoilage, enabling timely intervention to maintain quality. Gas Sensor detect volatile organic compounds (VOCs), particularly ethylene gas, which is emitted by ripening or decaying apples. Elevated ethylene levels indicate over-ripeness or spoilage even when the fruit appears normal on the surface. Gas sensors enhance the system’s ability to identify early-stage deterioration and prevent defective fruit from progressing down the line.

[0045] The weight sensor measures the mass of the produce in the chamber, which helps track moisture loss or degradation over time. The weight sensor used herein is precision load cells which are highly accurate to measure the weight or force applied to them with great sensitivity. They work by converting a physical force, such as the weight of produce resting on them, into an electrical signal. Inside the load cell, strain gauges are bonded to a metal structure that deforms slightly under load. This deformation changes the electrical resistance of the strain gauges, producing a measurable electrical signal proportional to the applied weight.

[0046] This data from the sensing module is fed into a Markov Chain Principle–based prediction module, which forecasts future produce condition and may instruct the processor to dynamically shift items between chambers 105. The Markov Chain Principle treats the condition of each produce item as a series of possible states (for example, fresh, ripening, nearly spoiled, or spoiled) and models the probability of transitioning from one state to another based solely on its current state. In other words, the future condition of the produce depends only on its present quality, not on the entire past history. By applying this statistical model to the real-time sensor data, the prediction module estimates how the quality of each item is likely to change over time. This foresight allows the system’s processor to make intelligent, dynamic decisions about how to best preserve the produce.

[0047] For instance, if the model predicts that an item is about to ripen rapidly, the processor can instruct the automated system to move it to a colder chamber 105 to slow down the ripening process. Conversely, items that are stable might be moved to chambers 105 with less stringent conditions to save energy. This dynamic, data-driven management ensures optimal storage conditions tailored to each item’s predicted needs, reducing spoilage, extending shelf life, and improving overall efficiency.

[0048] For example, an apple is detected exhibiting medium levels of ethylene and a noticeable color shift, both of which are indicators of the ripening process. Based on these observations, the system predicts that the apple will reach full ripeness within two days. To manage this progression and extend its shelf life, the apple is automatically relocated to Chamber B. This chamber maintains a cooler temperature range of 1°C to 5°C, which is optimal for slowing down the maturation process and preserving the fruit’s quality for a longer period.

[0049] The chambers 105 comprise of a robotic arm 108 with gripper 109 as an end effector, to shift the farm produce to different chamber. The gripper 109 effectively grip the farm produce from the chamber 105 and place on the conveyor arrangement 103 for shifting the farm produce to different chamber. The robotic arm 108 comprises, motor controllers, arm, end effector and sensors. All these parts are configured with the microcontroller. The elbow is at the middle section of the arm 108 that allows the upper part of the arm 108 to move the lower section independently. Lastly, the wrist is at the tip of the upper arm and attached to the end effector thereby the end effector works as a hand to grip the farm produce from the chamber 105 and place on the conveyor arrangement 103.

[0050] The microcontroller continuously acquire data regarding operational parameters of the chambers 105 and current state of the farm produce and sends the notification to the user via computing unit.

[0051] A level sensor integrated within each chamber 105 to detect emptiness in any of the chamber 105 after shifting of the farm produce. The level sensor used herein is an ultrasonic level sensor emits sound waves that reflect off the surface of the produce; if no reflections are detected or the distance measured exceeds a certain threshold, the sensor determines that the chamber 105 is empty. Based on the detected condition, the sensors send a signal to the microcontroller that sends a signal to the specific HVAC unit associated with the empty chamber 105 to shut off, thus saving energy.

[0052] A battery (not shown in figure) is associated with the system to supply power to electrically powered components which are employed herein. The battery is comprised of a pair of electrodes named as a cathode and an anode. The battery uses a chemical reaction of oxidation/reduction to do work on charge and produce a voltage between their anode and cathode and thus produces electrical energy that is used to do work in the system.

[0053] The present invention works best in the following manner, where the present invention includes where the harvested produce is loaded into the hopper 101, where the motorized flap 102 and vibrating motor dispense one item at a time onto the conveyor arrangement 103 operating at a pre-defined speed. The quality assessment module 104, situated alongside the conveyor, evaluates the produce using the sensor suite and classifies it accordingly. If deemed inedible, the produce is discarded into a waste container 104a via the actuated pusher 104b. Based on the quality assessment, the processor regulates the operation of the motorized door 106 and suction mechanism 107 for directing the produce into one of several cold storage chambers 105 maintained under different environmental conditions by separate HVAC units. Each chamber 105 includes sensors to monitor produce status, and the level sensor ensures that energy is conserved by turning off the HVAC when the chamber 105 is empty. The sensing module within each chamber 105 collects real-time data, which is analysed using the Markov Chain Principle–based prediction module to forecast future produce condition. If required, the processor initiates a transfer of the produce between chambers 105 using the robotic arm 108 with the gripper 109 to optimize storage. The system also includes the computing unit wirelessly linked to the processor for monitoring operational parameters and chamber 105 conditions, ensuring adaptive, data-driven, and resource-efficient produce management.

[0054] Although the field of the invention has been described herein with limited reference to specific embodiments, this description is not meant to be construed in a limiting sense. Various modifications of the disclosed embodiments, as well as alternate embodiments of the invention, will become apparent to persons skilled in the art upon reference to the description of the invention. , Claims:1) An adaptive cold storage system for farm produce, comprising:

i) a hopper 101, configured to receive a plurality of farm produce, the hopper 101 installed with a motorized flap 102 and a vibrating motor to operatively dispense a farm produce at a time;
ii) a conveyor arrangement 103 installed beneath the hopper 101 to receive and move the farm produce at a pre-defined speed;
iii) a quality assessment module 104 disposed adjacent to the conveyor arrangement 103 to determine the quality of farm produce and categorize the farm produce corresponding to the quality;
iv) a set of cold storage chambers 105 installed in a series adjacent to the conveyor arrangement 103 and maintained at different ambient conditions, each storage chamber 105 includes a motorized door 106 with a suction mechanism 107 to intake the farm produce;
v) a processor interlinked with the motorized door 106, suction mechanism 107 and quality assessment module 104 to regulate conveying of farm produce in the chamber 105 corresponding to the detected quality; and
vi) a sensing module configured within each of the chambers 105 and connected with a Markov Chain Principle based prediction module that predicts the future state and accordingly triggers the processor to dynamically shift the farm produce in between different chambers 105 based on the prediction.

2) The system as claimed in claim 1, wherein each of the chamber 105 is connected with a separate HVAC (heating ventilation and air conditioning unit) to maintain a different temperature and humidity condition in each of the chambers 105.

3) The system as claimed in claim 2, wherein the chambers 105 are installed with a level sensor operatively coupled with the processor to automatically shut off corresponding HVAC in case the chamber 105 is detected to be empty in order to ensure energy efficiency.

4) The system as claimed in claim 1, wherein the quality assessment module 104 comprises of a waste container 104a, a pusher 104b, a sensor suite including near-infrared spectroscopy (NIR) sensor, hyperspectral imaging 104c and odor sensor.

5) The system as claimed in claim 4, wherein the pusher 104b is actuated to push and discard the farm produce in the waste container 104a in case the sensor suite classifies the farm produce as inedible.

6) The system as claimed in claim 1, wherein the sensing module includes a group of sensors including red-green-blue (RGB) camera, near-infrared spectroscopy (NIR) sensor, hyperspectral imager, gas sensor, weight sensor.

7) The system as claimed in claim 1, wherein the chambers 105 comprises of a robotic arm 108 with gripper 109 as an end effector, to effectively grip the farm produce from the chamber 105 and place on the conveyor arrangement 103 for shifting the farm produce to different chamber.

8) The system as claimed in claim 1, wherein the motorized flap 102 is embodied with a spring arrangement to reposition the flap 102 at an initial position.

9) The system as claimed in claim 1, further comprises of a computing unit wirelessly linked with the processor to acquire data regarding operational parameters of the chambers 105 and current state of the farm produce.

10) The system as claimed in claim 1, wherein the conveyor arrangement 103 is an omnidirectional conveyor belt.