FORM 2

THE PATENT ACT 1970 &

The Patents Rules, 2003
COMPLETE SPECIFICATION
(See section 10 and rule 13)
Indian Patent office. /Delhi/ Mumbai/ Chennai/ Kolkata

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Ripeness Detection of Fruit using a Sensor Array

The following specification particularly describes the invention and the manner in
which it is to be performed.

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 Complete Specification

FIELD OF THE INVENTION

[601] Our invention “Ripeness Detection of Fruit using a Sensor Array” is related fruit
ripeness detection using ML technology
BACKGROUND OF THE INVENTION
[602] Ripeness detection of fruit using a sensor array can be a useful application in the
food industry and agriculture. The use of sensor arrays can help in non-destructive and
rapid assessment of fruit ripeness, allowing for better quality control and decision-
making during harvesting, storage, and distribution.
Here's a high-level overview of how a sensor array can be used for ripeness detection of
fruit:
1. Selection of Sensors: Different types of sensors can be used in an array to
capture various parameters that change with fruit ripeness, such as color, texture,
aroma, and gas emissions (ethylene, for example). For example, color sensors
can measure the change in color as fruit ripens, while aroma sensors can detect
the increase in volatile compounds associated with ripeness.
2. Data Acquisition: The sensor array collects data from the fruit, such as color
intensity, firmness, aroma profile, and gas emissions. This data can be acquired
non-invasively by placing the sensors in close proximity to the fruit.
3. Data Analysis: The data collected from the sensor array is then analyzed using
algorithms and machine learning techniques to correlate the sensor readings with
the ripeness stage of the fruit. This analysis may involve pattern recognition and
classification to determine the level of ripeness.
4. Calibration: The sensor array needs to be calibrated using samples of fruit at
different ripeness stages to establish the relationship between sensor readings
and actual ripeness. This calibration process is crucial for accurate and reliable
ripeness detection.
5. Integration and Feedback: Once the sensor array is calibrated and validated, it
can be integrated into processing and sorting equipment to provide real-time

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 feedback on the ripeness of fruit. This information can be used to sort fruit
according to ripeness level, optimize storage conditions, and make informed
decisions about harvesting and distribution.
By using a sensor array for ripeness detection, the industry can reduce the potential for
waste due to premature harvesting or spoilage, improve overall product quality, and
enhance consumer satisfaction with consistently ripe fruit.

OBJECTIVES OF THE INVENTION

1. Non-Destructive Assessment: One of the primary objectives is to develop a non-
destructive method for assessing fruit ripeness. By using a sensor array, the goal
is to enable the ripeness evaluation of fruit without altering or damaging the
product, thereby allowing for continuous monitoring throughout the production
and distribution process.
2. Rapid and Automated Analysis: Another objective is to achieve rapid and
automated analysis of fruit ripeness. The aim is to develop a system that can
quickly evaluate the ripeness stage of a large number of fruit samples, reducing
the need for manual intervention and accelerating decision-making processes in
the supply chain.
3. Objective Ripeness Criteria: A key goal is to establish objective criteria for
determining fruit ripeness. By leveraging sensor arrays, the objective is to
identify measurable parameters (such as color, aroma, firmness, and gas
emissions) that correspond to specific stages of ripeness, creating a standardized
and reliable method for assessing fruit quality.
4. Quality Control and Sorting: The application of sensor arrays aims to facilitate
quality control and sorting based on ripeness. By integrating sensor data with
sorting equipment, the objective is to enable the automatic segregation of fruit
into different ripeness categories, allowing for optimized distribution and storage
while minimizing waste.
5. Shelf-Life Prediction: Another objective is to use sensor array data to predict
fruit shelf life. By correlating sensor readings with fruit ripeness and quality, the
goal is to provide insights into the expected shelf life of fruit, enabling more
accurate inventory management and reducing the likelihood of spoilage.

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 6. Sustainability and Waste Reduction: An overarching objective is to contribute to
sustainability by reducing food waste. By accurately assessing fruit ripeness, the
aim is to minimize over-ripeness or premature harvesting, optimizing resource
utilization and contributing to a more sustainable supply chain.
7. Consumer Satisfaction: Ultimately, the objective is to enhance consumer
satisfaction by delivering consistently ripe and high-quality fruit. By
implementing sensor array technology, the goal is to ensure that consumers
receive fruit that meets their ripeness preferences, leading to improved overall
satisfaction and market competitiveness.

SUMMARY OF THE INVENTION

[603] Ripeness detection of fruit using a sensor array involves the application of
advanced sensor technology to non-destructively assess the ripeness stage of fruit. The
concept has evolved from the need for efficient, rapid, and objective methods for
evaluating fruit quality throughout the supply chain. The technology encompasses the
use of sensor arrays to capture multiple parameters such as color, aroma, texture, and
gas emissions, which are correlated with fruit ripeness using data analysis and machine
learning techniques. Key objectives include non-destructive assessment, rapid and
automated analysis, establishment of objective ripeness criteria, quality control and
sorting, shelf-life prediction, sustainability, waste reduction, and enhancing consumer
satisfaction. By achieving these objectives, the aim is to enhance the efficiency,
sustainability, and quality of fruit production and distribution while minimizing waste
and optimizing consumer satisfaction.

BRIEF DESCRIPTION OF THE DIAGRAM

Figure 1: Flow Control of Proposed System
Figure 2: Block diagram of the system
Figure 3: Experimental Setup for Sensor Array
Figure 4: Circuit arrangement of developed system
Figure 5: Schematic of developed system

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DESCRIPTION OF THE INVENTION
[604] Ripeness detection of fruit using a sensor array involves the utilization of multiple
sensors to capture various characteristics associated with fruit ripeness, such as color,
aroma, texture, and gas emissions. The process typically starts with the selection of
suitable sensors based on the parameters to be measured.

Once the sensors are chosen, they are placed in close proximity to the fruit to collect
data without causing any damage. The data collected from the sensors is then analyzed
using algorithms and machine learning techniques to establish correlations between
sensor readings and different stages of ripeness. This analysis enables the calibration of
the sensor array, which is crucial for accurate and reliable ripeness detection.

The calibrated sensor array can be integrated into processing and sorting equipment for
real-time assessment of fruit ripeness. This integration allows for the automatic
segregation of fruit based on their ripeness stage, facilitating efficient sorting and
distribution.

Overall, the use of a sensor array for ripeness detection provides a non-destructive,
rapid, and automated method to assess the quality and ripeness of fruit. This approach
aims to enhance the efficiency, sustainability, and overall quality of fruit production and
distribution processes, while also contributing to reducing waste and optimizing
consumer satisfaction.

Fruit Chamber
The fruit chamber has constructed and designed in such a way that one small fruit can
easily fit into it. The chamber is made up of acrylic sheet. All sensors have mounted
within the chamber to measure the emitted gases. On both sides of chambers holes are
created in order to maintain the proper ventilation.
System hardware

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The system is made up of MQ3, MQ4 and MQ 135 sensor, DHT 22 temperature and
humidity sensor, ADC155, ESP32, SD Card, Power Supply and Laptop Latitude E7440.
The sensors readings are connected to ADC155. The sensor analog input is converted
into digital using 16-bit ADC1555. Output of ADC155 is connected to ESP 32. The
advantage of using ESP32 is having built-in Wi-Fi connectivity. The system designed
measures the readings in two ways. The system is connected to Wi-Fi and provided a
SD Card to store the measured data. The facility is also provided to monitor the readings
serially by connecting the system to Laptop/Desktop through USB. Researcher used
“Hercules” Open-Source Software to monitor the readings and record them. system.
Sensor Calibration
Ethylene is included under the gases that falls under Liquified Petroleum Gases (LPG)
The datasheet of MQ3 sensor uses LPG sensitivity characteristics curve to detect
ethylene gas. Hence to detect the ethylene gas released from banana MQ3 sensor is
used. MQ3 is preheated before using in the system. For sensor calibration resistance in
clean air(R0) is detected first and then resistance at various concentration of gases (Rs)
is detected. The ratio of Rs/R0 is calculated. The DHT 22 sensor is used as its
temperature ranges from – 400C to + 1250C.

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I/ WE CLAIM

1. The use of sensor arrays enables more precise and consistent evaluation of fruit
ripeness, leading to improved quality control throughout the supply chain.
2. By analyzing data from the sensor array, it becomes possible to predict the shelf
life of fruit more accurately, reducing wastage and optimizing inventory
management.
3. Sensor arrays allow for non-destructive assessment of fruit ripeness, which can
lead to less handling and potential damage to the fruit.
4. Implementing sensor arrays for ripeness detection can lead to more efficient
sorting and grading processes, reducing labor and enhancing overall operational
efficiency.
5. The use of sensor arrays helps establish objective criteria for determining fruit
ripeness, reducing subjective interpretation and potential errors associated with
visual inspection.
6. By minimizing waste through more accurate ripeness detection and reducing
premature harvesting, sensor arrays contribute to more sustainable food
production practices.

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 ABSTRACT
“Ripeness Detection of Fruit using a Sensor Array”
[600] Our invention “Ripeness Detection of Fruit using a Sensor Array ” is basically
working with machine learning technology in that Fruits play very important role in our
day-to-day life because of their nutrition parameters. In recent years organic cultivation
is more popular as there is more demand for organic fruits. Ripeness detection of fruit is
most important parameter in order to decide the maturity level of the fruit. Traditional
methods of ripeness assessment rely on subjective human judgment leading to
inconsistencies and inaccuracies. Ethylene is termed as fruit natural hormone. Ethylene
plays as important roles in ripening process of fruit. As fruit ripens Ethylene contents
increases. A sensor array is designed to detect the contents of Ethylene during the
ripening process of fruit. This can be useful to decide the quality of the fruit. In order to
record the Ethylene gas emitted by fruit the MQ series commercially available metal
oxide semiconductor gas sensors have been used by the researcher. Ethylene is included
under the gases that falls under Liquefied Petroleum Gases (LPG). The datasheet of MQ
3 sensor uses LPG sensitivity characteristics curve to detect ethylene gas. Hence to
detect the ethylene gas released from fruit a MQ 3 sensor was used. MQ 3 is preheated
before using in the system. MQ135 and MQ 4 sensors are used to record the Odor.
DHT22 sensor has been used to check out the effect of Temperature and Humidity
during ripening of fruit. Daily two readings have been recorded for the Ethylene gas
emitted from fruit and for the Odor. The data was stored in the SD card by the designed
system. SD card generates an Excel file. The user has flexibility to choose how many
readings have been recorded in a day.