Abstract: An intelligent fabric sensing iron comprises: image capturing means adapted to capture an image of an object to be ironed; image analysing means adapted to analyse each captured image in relation to pre-defined parameters of analysis in order to determine fabric type in relation to stored pre-defined parameters and further adapted to output an operating temperature range in correlation with said determined fabric type; and operating mechanism adapted to receive said operating temperature range in order to enable working of said iron to work within said operating range.
FORM 2
THE PATENTS ACT, 1970
(39 of l970)
As amended by the Patents (Amendment) Act, 2005
AND
The Patents Rules, 2003
As amended by the Patents (Amendment) Rules, 2005
COMPLETE SPECIFICATION
(See section 10 and rule 13)
TITLE OF THE INVENTION
An intelligent fabric sensing iron.
APPLICANTS (S)
Crompton Greaves Limited, CG House, Dr Annie Besant Road, Worli, Mumbai 400 030, Maharashtra, India, an Indian Company
INVENTOR (S)
Gawali Nilesh Pundalik and Mahajan Trupti Yashwant of Crompton Greaves Limited, Electronic Development Centre, CG Global R&D, Kanjur Marg (E), Mumbai - 400042, Maharashtra, India; both Indian Nationals.
PREAMBLE TO THE DESCRIPTION:
The following specification particularly describes the nature of this invention and the manner in which it is to be performed:
FIELD OF THE INVENTION:
This invention relates to the field of electrical and electronic appliances.
Particularly, this invention relates to a clothes' iron.
More particularly, this invention relates to an intelligent fabric sensing iron.
BACKGROUND OF THE INVENTION:
A clothes' iron is a home appliance used to remove wrinkles from a fabric or a cloth. It is a heated appliance which works on electric power. Ironing works by loosening the ties between the long chains of molecules that exist in polymer fibre materials.
When the iron is turned on, the consumer moves it over an item of clothing on an ironing board. The combination of heat and pressure removes wrinkles. The evolution of irons began from the use of a flat plate of metal with coal as the heating medium. The electric iron was invented in the 1880s when electricity became widely available in home. The electric iron was invented in 1882 by Henry W. Seeley, a New York inventor Seeley patented his "electric flatiron" on June 6, 1882 (US patent no. 259,054). His iron weighed almost 15 pounds and took a long time to warm up. Other electric irons had also been invented, including one from France (1882), but it used a carbon arc to heat the iron, a method which was dangerous.
In 1903, irons with electric cords directly attached to the iron were being sold.
In the 1920s, the iron was improved by adding an automatic heat control made of
pure silver. Thermostats soon became a standard feature.
Contemporary irons have nonstick coating on the sole plate, an innovation that was introduced in 1995. Most featured bodies are made of plastic and have more holes on the sole plate to allow steam to come through.
Electric irons developed over the years. Some advancements included automated thermostat regulation in accordance with a pre-defined fabric setting, steam disposal off the base ironing plate for some fabrics, and the like.
Understanding the nature of the fabric to be ironed is an important aspect of ironing. A fabric is defined by the following characteristics:
1) nature of the thread used, which may be technically evaluated with respect to the diameter of the thread; and
2) distance between adjacent threads in a fabric.
Heat applied to the fabric depends on these above two characteristics along with evaluation of the fact that whether the fabric has been ironed or not.
All these are visual parameters which are judged manually, according to the prior art, before the ironing process in order to select an operating range from the currently available irons. This operating range sets a temperature range for the iron thermostat. With an experience of ironing, it is relatively easy for an experienced person to select the range or function. But many a times, a user cannot decide the
temperature range required for ironing due to lack of awareness of the type of fabric. Wrong judgement may lead to burning the fabric or leaving wrinkled which are not easy to set.
Hence, there is a need for an intelligent iron which senses fabric without human intervention or judgement.
OBJECTS OF THE INVENTION:
An object of the invention is to provide a safer iron.
Another object of the invention is to provide a smart or an intelligent iron which can sense the fabric that is to be ironed.
Another object of the invention is to provide a smart or an intelligent iron which can sense working condition of the iron once it is being used.
SUMMARY OF THE INVENTION:
According to this invention, there is provided an intelligent fabric sensing iron comprising:
a. image capturing means adapted to capture an image of an object to be
ironed;
b. image analysing means adapted to analyse each captured image in relation to
pre-defined parameters of analysis in order to determine fabric type in
relation to stored pre-defined parameters and further adapted to output an
operating temperature range in correlation with said determined fabric type; and c. operating mechanism adapted to receive said operating temperature range in order to enable working of said iron to work within said operating range.
Typically, said image capturing means is an image sensor.
Typically, said image capturing means is camera enabled to take out images at a close range.
Preferably, said image capturing means is a CCD sensor.
Alternatively, said image capturing means is a CMOS sensor.
Typically, said image analysing means includes at least a first comparator means adapted to compare thickness of threads from each of said captured images with a first stored value from a pre-defined database in order to provide a first output.
Typically, said image analysing means includes at least a second comparator means adapted to compare gap between adjacent threads from each of said captured images with a second stored value from a pre-defined database in order to provide a second output.
Typically, said image analysing means includes at least a third comparator means adapted to compare folds on a fabric from each of said captured images with a third stored value from a pre-defined database in order to provide a third output.
Typically, said image analysing means includes at least a first collating means to collate each of said first outputs, second outputs, and third outputs to provide a captured output.
Typically, said image analysing means includes a primary database means including at least a first database first database adapted to store a plurality of first stored values in relation to defined thickness of threads in terms of images in correlation with first output values.
Typically, said image analysing means includes a primary database means including at least a second database adapted to store a plurality of second stored values in relation to defined gaps between adjacent threads in terms of images in correlation with second output values.
Typically, said image analysing means includes a primary database means including at least a third database adapted to store a plurality of third stored values in relation to defined folds of fabric in terms of images in correlation with third output values.
Typically, said image analysing means includes a second collating means adapted to collate each of said first stored values, said second stored values, and said third stored values, in various permutations and combinations according to user-definition, to define a fabric type which is stored in a look-up table.
Typically, said image analysing means includes a secondary database adapted to store temperature ranges for each type of defined fabric type such that each fabric
type is defined in a primary database in terms of collated first stored values, second stored values, and third stored values,
Typically, said image analysing means includes a fold determination module adapted to employ a fold determination algorithm adapted to work with said image analysing means in order to receive and analyse data in relation to folds on a fabric.
Typically, said iron includes a fabric determination means adapted to determine if a fabric is present when the iron is in switched ON position and a decision making means to enable said image analysing means if the determined value is positive, and to switch OFF the iron and said image analysing means if the determined value is negative.
BRIEF DESCRIPTION OF THE ACCOMPANYING DRAWINGS:
The invention will now be described in relation to the accompanying drawings, in which:
Figure 1 illustrates an exemplary placement of the sensing means of the sensing mechanism of the intelligent fabric sensing iron; and
Figure 2 illustrates a schematic of the sensing mechanism of the intelligent fabric sensing iron.
DETAILED DESCRIPTION OF THE ACCOMPANYING DRAWINGS:
According to this invention, there is provided an intelligent fabric sensing iron.
Figure 1 illustrates an exemplary placement of the sensing means of the sensing mechanism of the intelligent fabric sensing iron.
Figure 2 illustrates a schematic of the sensing mechanism of the intelligent fabric sensing iron.
In accordance with an embodiment of this invention, there is provided an image capturing means or an image sensor (1CM) adapted to capture an image of an object to be ironed. Typically, the object is a fabric. Typically, the image capturing means is a camera enabled to take out images at a close range. This image capturing means or image sensor (ICM) is preferably located advantageously near the sole i.e. the iron plate (IP) of the iron (100). Preferably, the image capturing means or image sensor is a CCD sensor or a CMOS sensor.
In accordance with another embodiment of this invention, there is provided an image analysing means (IAM) adapted to analyse each captured image. The image analysing means includes at least three comparator means. Typically, a first comparator (CI) means compares thickness of threads from each of captured images with a first stored value from a pre-defined database in order to provide a first output. Typically, a second comparator means (C2) compares average gap between adjacent threads from each of captured images with a second stored value from a pre-defined database in order to provide a second output. A fold
determination module which employs a fold determination algorithm is adapted to work with the image analysing means. This fold determination module receives data in relation to folds on a fabric. Typically, a third comparator (C3) means compares folds on a fabric from each of captured images with a third stored value from a pre-defined database in order to provide a third output. Each of the first output, the second output, and third output is collated by a first collating means (CLM1) of the image analysing means to provide a captured output.
In accordance with yet another embodiment of this invention, there is provided a primary database means (PD) including at least a first database (Dl), at least a second database (D2), and at least a third database (D3). The first database (Dl) is used to store a plurality of first stored values in relation to defined thickness of threads in terms of images in correlation with first output values. The second database (D2) is used to store a plurality of second stored values in relation to defined gaps between adjacent threads in terms of images in correlation with second output values. The third database (D3) is used to store a plurality of third stored values in relation to defined folds of fabric in terms of images in correlation with third output values. Each of the first stored values, the second stored values, and third stored values is collated by a second collating means (CLM2), in various permutations and combinations according to user-definition, to define a fabric type which is stored in a look-up table.
In accordance with still another embodiment of this invention, there is provided a secondary database (SD) adapted to store temperature ranges for each type of defined fabric type. Each fabric type is defined in the primary database in terms of collated first stored values, second stored values, and third stored values.
In accordance with an additional embodiment of this invention, there is provided an operating mechanism (OM) of said iron adapted to receive said temperature range of operation and to enable the iron to work within that operating range. This corresponds to a favourable range for the fabric that is detected.
In accordance with yet an additional embodiment of this invention, there is provided a fabric determination means (FDM) adaptedi to determine if a fabric is present when the iron is in switched ON position- If the determined value is positive, the image analysing means is enabled. If the determined value is negative, the image analysing means and iron is disabled.
While this detailed description has disclosed certain specific enbodiment of the present invention for illustrative purposes, various modifications will be apparent to those skilled in the art which do not constitute departures from the spirit and scope of the invention as defined in the following claims, and it is to be distinctly understood that the foregoing descriptive matter is to be interpreted merely as illustrative of the invention and not as a limitation.
We claim,
1. An intelligent fabric sensing iron comprising:
a. image capturing means adapted to capture an image of an object to be
ironed;
b. image analysing means adapted to analyse each captured image in relation to
pre-defmed parameters of analysis in order to determine fabric type in
relation to stored pre-defined parameters and further adapted to output an
operating temperature range in correlation with said determined fabric type;
and
c. operating mechanism adapted to receive said operating temperature range in
order to enable working of said iron to work within said operating range.
2. An iron as claimed in claim 1 wherein, said image capturing means is an image sensor.
3. An iron as claimed in claim 1 wherein, said image capturing means is camera enabled to take out images at a close range.
4. An iron as claimed in claim 1 wherein, said image capturing means is a CCD sensor.
5. An iron as claimed in claim 1 wherein, said image capturing means is a CMOS sensor.
6. An iron as claimed in claim 1 wherein, said image analysing means includes at least a first comparator means adapted to compare thickness of threads from each of said captured images with a first stored value from a predefined database in order to provide a first output.
7. An iron as claimed in claim 1 wherein, said image analysing means includes at least a second comparator means adapted to compare gap between adjacent threads from each of said captured images with a second stored value from a pre-defined database in order to provide a second output.
8. An iron as claimed in claim 1 wherein, said image analysing means includes at least a third comparator means adapted to compare folds on a fabric from each of said captured images with a third stored value from a pre-defined database in order to provide a third output.
9. An iron as claimed in claim 1 wherein, said image analysing means includes at least a first collating means to collate each of said first outputs, second outputs, and third outputs to provide a captured output.
10. An iron as claimed in claim 1 wherein, said image analysing means includes a primary database means including at least a first database first database adapted to store a plurality of first stored values in relation to defined thickness of threads in terms of images in correlation with first output values.
1 l.An iron as claimed in claim 1 wherein, said image analysing means includes a primary database means including at least a second database adapted to store a plurality of second stored values in relation to defined gaps between adjacent threads in terms of images in correlation with second output values.
12.An iron as claimed in claim 1 wherein, said image analysing means includes a primary database means including at least a third database adapted to store a plurality of third stored values in relation to defined folds of fabric in terms of images in correlation with third output values.
13.An iron as claimed in claim 1 wherein, said image analysing means includes a second collating means adapted to collate each of said First stored values, said second stored values, and said third stored values, in various permutations and combinations according to user-definition, to define a fabric type which is stored in a look-up table.
14. An iron as claimed in claim 1 wherein, said image analysing means includes a secondary database adapted to store temperature ranges for each type of defined fabric type such that each fabric type is defined in a primary database in terms of collated first stored values, second stored values, and third stored values.
15.An iron as claimed in claim 1 wherein, said image analysing means includes a fold determination module adapted to employ a fold determination algorithm adapted to work with said image analysing means in order to receive and analyse data in relation to folds on a fabric.
16.An iron as claimed in claim 1 wherein, said iron includes a fabric determination means adapted to determine if a fabric is present when the iron is in switched ON position and a decision making means to enable said image analysing means if the determined value is positive, and to switch OFF the iron and said image analysing means if the determined value is negative.
| # | Name | Date |
|---|---|---|
| 1 | 3589-MUM-2011DESCRIPTION(COMPLETE).pdf | 2018-08-10 |
| 2 | 3589-MUM-2011-FORM 3.pdf | 2018-08-10 |
| 3 | 3589-MUM-2011-FORM 26(2-4-2012).pdf | 2018-08-10 |
| 4 | 3589-MUM-2011-FORM 2.pdf | 2018-08-10 |
| 5 | 3589-MUM-2011-FORM 2(TITLE PAGE).pdf | 2018-08-10 |
| 6 | 3589-MUM-2011-FORM 1.pdf | 2018-08-10 |
| 7 | 3589-MUM-2011-FORM 1(13-1-2012).pdf | 2018-08-10 |
| 8 | 3589-MUM-2011-DRAWING.pdf | 2018-08-10 |
| 9 | 3589-MUM-2011-CORRESPONDENCE.pdf | 2018-08-10 |
| 10 | 3589-MUM-2011-CORRESPONDENCE(2-4-2012).pdf | 2018-08-10 |
| 11 | 3589-MUM-2011-CORRESPONDENCE(13-1-2012).pdf | 2018-08-10 |
| 12 | 3589-MUM-2011-CLAIMS.pdf | 2018-08-10 |
| 13 | 3589-MUM-2011-ABSTRACT.pdf | 2018-08-10 |