The present disclosure relates, in general, to garment steamer, and
more specifically, relates to an apparatus for ironing fabrics.
BACKGROUND
[0002] A garment steamer is configured to iron different types of fabrics. In
conventional steam irons, the temperature is set by the user and is operated in
forward and backward direction over the fabric. In the forward stroke and the
backward stroke, the amount of steam that is set may be insufficient or may be more
in most cases to heat the fabric Although it does not affect the fabric, steam is
wasted that could have been used to warm up and to moisten more intensively the
fabric in order to obtain a weaker fabric at a higher temperature during the forward
stroke. A lot of unused steam is blown through the fabric into the ironing board and
to the surrounding air without the desired condensation onto and in the fabric.
[0003] The existing garment steamers suffer from limitations that include a
manual setting of the temperature of the garment streamer, cloth may get burned during ironing due to increase in temperature, it harms the person due to high temperature and causes wastage of electricity if the setting of the streamer is set at high temperature.
[0004] Therefore, there is a need in the art to provide a means that can
automatically adjust the temperate of the garment steamers by solving the aforementioned problems.
OBJECTS OF THE PRESENT DISCLOSURE
[0005] An object of the present disclosure relates, in general, to garment
steamer, and more specifically, relates to an apparatus for ironing fabrics.
[0006] Another obj ect of the present disclosure is to provide an apparatus that
provides accurate and effective steam generation for ironing the fabric.
[0007] Another obj ect of the present disclosure is to provide an apparatus that
decreases the involvement of manual effort of the user.

[0008] Another obj ect of the present disclosure is to provide an apparatus that
is safer for the person who irons the garments.
[0009] Another obj ect of the present disclosure is to provide an apparatus that
saves electricity.
[0010] Another object of the present disclosure is to provide an apparatus
prevents burning of the garments.
[0011] Yet another object of the present disclosure is to provide an apparatus
that is compact and user friendly.
SUMMARY
[0012] The present disclosure relates, in general, to garment steamer, and
more specifically, relates to an apparatus for ironing fabrics.
[0013] In an aspect, the present disclosure provides an apparatus An
apparatus for measuring texture of fabrics, the apparatus includes one or more
sensors configured in frame of the apparatus, the one or more sensors generates a
set of acoustic signals from a fabric being placed on a surface; and a processor
operatively coupled to the one or more sensors, the processor operatively coupled
to a memory, the memory storing instructions executable by the processor to
receive, from the one or more sensors, the set of acoustic signals from the fabric,
analyse the received set of acoustic signals to extract a set of attributes from the set
of acoustic signals, the set of attributes pertaining to texture attributes of fabrics;
and extract, from the extracted set of attributes, a set of values for the extracted set
of attributes, wherein, based on the comparison of the extracted set of values of the
extracted set of attributes from a reference set of values, the processor is configured
to automatically adjust temperature of the apparatus to facilitate steaming of fabric.
[0014] According to an embodiment, the one or more sensors are any or a
combination of laser generating tool, acoustic capturing device and image processing unit.
[0015] According to an embodiment, the laser generating tool directs a laser
beam towards the fabric placed on the surface and creates pressure waves that propagate through the air to generate the set of acoustic signals.

[0016] According to an embodiment, the acoustic capturing device captures
the set of acoustic signals generated from the laser generating tool to record and convey the set of acoustic signals to the processor.
[0017] According to an embodiment, the texture attributes of fabrics comprise
rough, hard, wet, bumpy, fuzzy, sticky, dusty, rough, gritty, soft, lumpy and any combination thereof.
[0018] According to an embodiment, the processor is operatively coupled to
a learning engine, the learning engine trained to detect the texture attributes of the fabric.
[0019] According to an embodiment, the learning engine is trained using a
historical data of correlation of the heat level of the extracted set of attributes pertaining to texture attributes of fabrics.
[0020] According to an embodiment, the learning engine is a machine
learning model, wherein the movement of apparatus is performed automatically
through mobile or by speaking using natural language processing (NLP), where the
image processing unit senses the boundaries of the fabrics.
[0021] According to an embodiment, the reference set of values is a pre-
defined dataset that is trained and updated using historical data of correlation of heat level of the texture attributes of the fabric.
[0022] In an aspect, the present disclosure provides a method for measuring
texture of fabrics, the method comprising generating, by one or more sensors, a set of acoustic signals from a fabric being placed on a surface, the one or more sensors configured in frame of the apparatus; receiving, at a computing device, from the one or more sensors, the set of acoustic signals from the fabric; analysing, at the computing device, the received set of acoustic signals to extract a set of attributes from the set of acoustic signals, the set of attributes pertaining to texture attributes of fabrics; and extracting, at the computing device, from the extracted set of attributes, a set of values for the extracted set of attributes, wherein, based on the comparison of the extracted set of values of the extracted set of attributes from a reference set of values, the processor is configured to automatically adjust temperature of the apparatus to facilitate steaming of fabric.

[0023] Various objects, features, aspects, and advantages of the inventive
subject matter will become more apparent from the following detailed description of preferred embodiments, along with the accompanying drawing figures in which like numerals represent like components.
BRIEF DESCRIPTION OF THE DRAWINGS
[0024] The following drawings form part of the present specification and are
included to further illustrate aspects of the present disclosure. The disclosure may
be better understood by reference to the drawings in combination with the detailed
description of the specific embodiments presented herein.
[0025] FIG. 1A illustrate an exemplary representation of garment steamer, in
accordance with an embodiment of the present disclosure.
[0026] FIG. IB illustrate an exemplary functional components of garment
steamer, in accordance with an embodiment of the present disclosure.
[0027] FIG. 1C illustrate an exemplary working model of garment steamer,
in accordance with an embodiment of the present disclosure.
[0028] FIG. 2 illustrate an exemplary method for measuring texture of fabric,
in accordance with an embodiment of the present disclosure.
DETAILED DESCRIPTION
[0029] The following is a detailed description of embodiments of the
disclosure depicted in the accompanying drawings. The embodiments are in such detail as to clearly communicate the disclosure. If the specification states a component or feature "may", "can", "could", or "might" be included or have a characteristic, that particular component or feature is not required to be included or have the characteristic.
[0030] As used in the description herein and throughout the claims that
follow, the meaning of "a," "an," and "the" includes plural reference unless the context clearly dictates otherwise. Also, as used in the description herein, the meaning of "in" includes "in" and "on" unless the context clearly dictates otherwise.

[0031] The present disclosure relates, in general, to garment steamer, and
more specifically, relates to an apparatus for ironing fabrics. The garment steamer
includes a laser generating tool, an acoustic capturing device, and a data processing
unit. The laser generating tool directs a laser towards a cloth placed on a surface to
the garment steamer and creates pressure waves that propagate through the air and
produce an acoustic signal. The acoustic capturing device records and forwards the
signal to the data processing unit. The data processing unit further comprises a
digital signal processing module that processes the received acoustic signal. A
statistical processing module further filters the acoustic signal from the data
processing unit and generates a machine learning model for different texture
attributes of the fabrics. The machine learning model is correlated with the heat
level of the surface of the garment steamer and it can set the temperature of the
garment steamer automatically according to the texture of the fabric. The present
disclosure can be described in enabling detail in the following examples, which may
represent more than one embodiment of the present disclosure.
[0032] FIG. 1A illustrate an exemplary representation of garment steamer, in
accordance with an embodiment of the present disclosure.
[0033] Referring to FIG. 1A, photoacoustic non-destructive measurement
garment steamer 100 (also referred to as an apparatus 100, herein) can be configured to automatically adjust the temperature of steam passing to fabrics. The apparatus 100 can include a soleplate 102, which can be heated by an electrical heating element. One or more sensors 104 can be configured in apparatus 100 and configured to change the desired temperature of the soleplate 102 according to the texture of the fabric. The apparatus 100 can set the temperature automatically according to the texture of the fabrics.
[0034] In an exemplary embodiment, one or more sensors 104 can be any or
a combination of a laser generating tool 116, an acoustic capturing device 118 and an image processing unit 120. FIG. IB illustrate an exemplary functional components of garment steamer, in accordance with an embodiment of the present disclosure. The sensor 104 can be coupled to the data processing unit 106 (also referred to as processor 106, herein). In an embodiment, the laser generating tool

116 directs a laser beam towards the fabric placed on a surface on an ironing board,
the texture of fabrics can be rough, hard, wet, bumpy, fuzzy, sticky, dusty, rough,
gritty, soft, lumpy and any combination thereof. The laser generating tool creates
pressure waves that propagate through the air and produce a set of acoustic signals.
[0035] The acoustic capturing device 118 can capture the set of acoustic
signals generated from the laser generating tool 116 to record and convey the set of
acoustic signals to the processor 106. The processor 106 can receive, from the one
or more sensors 104, the set of acoustic signals of the fabrics. The processor 106
analyse the received acoustic signals to extract a set of attributes from the acoustic
signals, the set of attributes pertaining to different texture attributes of fabrics,
where the different texture attributes include rough, hard, wet, bumpy, fuzzy, sticky,
dusty, rough, gritty, soft, lumpy and any combination thereof.
[0036] The processor 106 configured to extract, from the extracted set of
attributes, a set of values for the extracted set of attributes, where based on the comparison of the extracted set of values of the extracted set of attributes from a reference set of values, the processor 106 is configured to automatically adjust the temperature of the apparatus 100 to facilitate steaming of fabric according to the texture of the fabric. The reference set of values is a pre-defined dataset that is trained and updated using historical data of correlation of the heat level of the texture attributes of the fabric.
[0037] For example, the set of values for the rough fabrics may be different
from that of the soft fabrics, where the processor 106 is configured to automatically adjust the apparatus 100 to high temperature to facilitate steaming of rough fabrics. Similarly, processor 106 is configured to automatically adjust the apparatus 100 to low temperature to facilitate the steaming of soft fabrics.
[0038] The processor 106 can be operatively coupled to a learning engine 114
as shown in FIG. 1C, the learning engine 114 trained to detect the texture of the fabric. The learning engine 114 is trained using historical data of correlation of the heat level of the extracted set of attributes pertaining to different texture attributes of fabrics. The learning engine 114 is a combination of machine learning model. A statistical processing module further filters the acoustic signal from the processor

106 and generates the machine learning model for different texture attributes such as rough, hard, wet, bumpy, fuzzy, sticky, dusty, rough, gritty, soft, lumpy cloths. The machine learning model is correlated with the heat level of the surface of the apparatus 100 and can set the temperature of the apparatus 100 automatically according to the texture of the cloth/fabric
[0039] In another embodiment, movement of apparatus 100 can be performed
automatically through mobile or by speaking using natural language processing (NLP), where the image processing unit 120 configured in the apparatus 100 can sense the boundaries of the fabrics.
[0040] The processor 106 that can be in communication with each of a
memory 108, display 110 and input/output units or interface module 112. The interface module 112 can include analogue gain amplifier, signal conditioning and driver. The processor 106 may include a microprocessor or other devices capable of being programmed or configured to perform computations and instruction processing in accordance with the disclosure. Such other devices may include microcontrollers, digital signal processors (DSP), analogue to digital converter (ADC), complex programmable logic device (CPLD), field programmable gate arrays (FPGA), application-specific assimilated circuits (ASIC), discrete gate logic, and/or other assimilated circuits, hardware or firmware in lieu of or in addition to a microprocessor.
[0041] The memory 108 can include programmable software instructions that
are executed by the processor 106. The processor 106 may be embodied as a single processor or a number of processors. The processor 106 and a memory may each be, for example located entirely within a single computer or other computing device. The memory, which enables storage of data and programs, may include random-access memory (RAM), read-only memory (ROM), flash memory and any other form of readable and writable storage medium.
[0042] The embodiments of the present disclosure described above provide
several advantages. The one or more of the embodiments provides apparatus 100 that enables accurate and effective steam generation for ironing the fabric. The present disclosure provides the apparatus 100 that decreases the involvement of

manual effort of the user and is safer for the person who irons the garments. The present disclosure provides the apparatus 100 that saves electricity, prevents burning of the garments, compact and user friendly.
[0043] FIG. 2 illustrate an exemplary method for measuring texture of fabric,
in accordance with an embodiment of the present disclosure.
[0044] Referring to FIG. 2, the method 200 can be implemented using a
computing device, which can include one or more processors. The method 200 incudes at block 202 one or more sensors can generate a set of acoustic signals from a fabric being placed on a surface, the one or more sensors configured in frame of the apparatus. At block 204, the computing device can receive from the one or more sensors, the set of acoustic signals from the fabric.
[0045] At block 206, the computing device can analyse the received set of
acoustic signals to extract a set of attributes from the set of acoustic signals, the set of attributes pertaining to texture attributes of fabric. At block 208, the computing device extract from the extracted set of attributes, a set of values for the extracted set of attributes, wherein, based on the comparison of the extracted set of values of the extracted set of attributes from a reference set of values, the processor is configured to automatically adjust temperature of the apparatus to facilitate steaming of fabric.
[0046] It will be apparent to those skilled in the art that the apparatus 100 of
the disclosure may be provided using some or all of the mentioned features and components without departing from the scope of the present disclosure. While various embodiments of the present disclosure have been illustrated and described herein, it will be clear that the disclosure is not limited to these embodiments only. Numerous modifications, changes, variations, substitutions, and equivalents will be apparent to those skilled in the art, without departing from the scope of the disclosure, as described in the claims.
ADVANTAGES OF THE PRESENT DISCLOSURE
[0047] The present disclosure provides an apparatus that provides accurate
and effective steam generation for ironing the fabric.

[0048] The present disclosure provides an apparatus that decreases the
involvement of manual effort of the user.
[0049] The present disclosure provides an apparatus that is safer for the
person who irons the garments.
[0050] The present disclosure provides an apparatus that saves electricity.
[0051] The present disclosure provides an apparatus that prevents burning of
the garments.
[0052] The present disclosure provides an apparatus that is compact and user
friendly.

An apparatus (100) for measuring texture of fabrics, the apparatus
comprising:
one or more sensors (104) configured in frame of the apparatus
(100), the one or more sensors (104) generates a set of acoustic signals from
a fabric being placed on a surface; and
a processor (106) operatively coupled to the one or more sensors
(104), the processor operatively coupled to a memory (108), the memory
storing instructions executable by the processor to:
receive, from the one or more sensors (104), the set of acoustic signals from the fabric;
analyse the received set of acoustic signals to extract a set of attributes from the set of acoustic signals, the set of attributes pertaining to texture attributes of fabrics; and
extract, from the extracted set of attributes, a set of values for the extracted set of attributes, wherein, based on the comparison of the extracted set of values of the extracted set of attributes from a reference set of values, the processor is configured to automatically adjust temperature of the apparatus to facilitate steaming of fabric.
The apparatus as claimed in claim 1, wherein the one or more sensors (104) are any or a combination of a laser generating tool (116), acoustic capturing device (118) and an image processing unit (120).
The apparatus as claimed in claim 2, wherein the laser generating tool (116) directs a laser beam towards the fabric placed on the surface and creates pressure waves that propagate through the air to generate the set of acoustic signals.

4. The apparatus as claimed in claim 2, wherein the acoustic capturing device (118) captures the set of acoustic signals generated from the laser generating tool to record and convey the set of acoustic signals to the processor (106).
5. The apparatus as claimed in claim 1, wherein the texture attributes of fabrics comprise rough, hard, wet, bumpy, fuzzy, sticky, dusty, rough, gritty, soft, lumpy and any combination thereof.
6. The apparatus as claimed in claim 1, wherein the processor (106) is operatively coupled to a learning engine (114), the learning engine trained to detect the texture attributes of the fabric.
7. The apparatus as claimed in claim 6, wherein the learning engine (114) is trained using historical data of correlation of heat level of the extracted set of attributes pertaining to texture attributes of fabrics.
8. The apparatus as claimed in claim 7, wherein the learning engine (114) is a machine learning model, wherein the movement of apparatus (100) is performed automatically through mobile or by speaking using natural language processing (NLP), the image processing unit (120) configured in the apparatus (100) senses the boundaries of the fabrics.
9. The apparatus as claimed in claim 1, wherein the reference set of values is a pre-defined dataset that is trained and updated using the historical data of correlation of the heat level of the texture attributes of the fabric.
10. A method (200) for measuring texture of fabrics, the method comprising:
generating (202), by one or more sensors, a set of acoustic signals from a fabric being placed on a surface, the one or more sensors configured in frame of the apparatus;

receiving (204), at a computing device, from the one or more sensors, the set of acoustic signals from the fabric;
analysing (206), at the computing device, the received set of acoustic signals to extract a set of attributes from the set of acoustic signals, the set of attributes pertaining to texture attributes of fabrics; and
extracting (208), at the computing device, from the extracted set of attributes, a set of values for the extracted set of attributes, wherein, based on the comparison of the extracted set of values of the extracted set of attributes from a reference set of values, the processor is configured to automatically adjust temperature of the apparatus to facilitate steaming of fabric.