DESC:CROSS REFERENCE TO RELATED APPLICATION
[001] This application is based on and derives the benefit of Indian Provisional Application 201741003377, the contents of which are incorporated herein by reference.

TEHCNICAL FIELD
[002] Embodiments disclosed herein relate to safety systems in vehicles and more particularly to enabling safe operation of a vehicle by monitoring air quality of the tyre of a vehicle, wherein the air quality can be an indicator of presence of at least one of gaseous and/or physical impurities in the tyre.

BACKGROUND
[003] Vehicle tyres are generally the point of contact between the vehicle and the road surface. So, it is important that the tyres have to be in optimal condition, such as being free of impurities. The impurities can be of a gaseous form or a solid form (such as a nail, nail head, metallic particles, and so on).
[004] In an example scenario, consider that the vehicle tyres are filled with compressed air from a tyre inflation machine. The quality of commonly found compressed air is never pure. Running air through a compressor typically adds trace amounts of oil and particulate, as well as water vapor, which can lead to rust, rot, and corrosion and hence compromise tyre and wheel assemblies.
OBJECTS
[005] The principal object of the embodiments disclosed herein is to provide an apparatus and methods to monitor presence of impurities inside a tyre by monitoring the quality of the air inside the tyre.
[006] Another object of the embodiments disclosed herein is to provide an apparatus and methods to monitor presence of impurities inside a tyre by monitoring the quality of air inside the tyre, wherein the impurities can be of a gaseous form.
[007] Another object of the embodiments disclosed herein is to provide an apparatus and methods to monitor presence of impurities inside a tyre by monitoring the quality of air inside the tyre, wherein the impurities can be of a solid form.
[008] Another object of the embodiments disclosed herein is to provide an apparatus and methods to monitor presence of impurities inside a tyre by monitoring the quality of air inside the tyre and providing an alert to a user on detecting at least one impurity.
[009] These and other objects of the embodiments herein will be better appreciated and understood when considered in conjunction with the following description and the accompanying drawings. It should be understood, however, that the following descriptions, while indicating embodiments and numerous specific details thereof, are given by way of illustration and not of limitation. Many changes and modifications may be made within the scope of the embodiments herein without departing from the spirit thereof, and the embodiments herein include all such modifications.

BRIEF DESCRIPTION OF FIGURES
[0010] Embodiments herein are illustrated in the accompanying drawings, through out which like reference letters indicate corresponding parts in the various figures. The embodiments herein will be better understood from the following description with reference to the drawings, in which:
[0011] FIGs. 1a, 1b and 1c depict a tyre monitor, according to embodiments as disclosed herein;
[0012] FIG. 2a depicts the tyre monitor comprising of a controller, according to embodiments as disclosed herein;
[0013] FIG. 2b depicts a tyre monitoring system, according to embodiments as disclosed herein;
[0014] FIG. 2c depicts an example air quality sensor, according to embodiments as disclosed herein; and
[0015] FIG. 3 is a flowchart depicting a process of the controller monitoring a tyre, according to embodiments as disclosed herein.

DETAILED DESCRIPTION
[0016] The embodiments herein and the various features and advantageous details thereof are explained more fully with reference to the non-limiting embodiments that are illustrated in the accompanying drawings and detailed in the following description. Descriptions of well-known components and processing techniques are omitted so as to not unnecessarily obscure the embodiments herein. The examples used herein are intended merely to facilitate an understanding of ways in which the embodiments herein may be practiced and to further enable those of skill in the art to practice the embodiments herein. Accordingly, the examples should not be construed as limiting the scope of the embodiments herein.
[0017] The embodiments herein disclose an apparatus and methods to monitor presence of impurities inside a tyre by monitoring the quality of the air inside the tyre. Referring now to the drawings, and more particularly to FIGS. 1 through 3, where similar reference characters denote corresponding features consistently throughout the figures, there are shown preferred embodiments.
[0018] The vehicle as referred to herein can be any vehicle comprising of at least one tyre. Examples of the vehicle as referred to herein can be but not limited to cars, vans, trucks, buses, tractors, scooters, motorcycles, bicycles, and so on.
[0019] The impurities can be of at least one of a gaseous form or a solid/liquid form (such as a nail, oil particles/particulates, nail head, metallic particles, and so on), which can be stuck within the tyre or at least a portion has penetrated the interior of the tyre. In an example, consider that a tyre has been filled with air; the moisture content inside the tyre (if present) can be considered as an impurity. In an example, consider that a tyre has been filled with nitrogen; then oxygen or any other gas present in the tyre can be considered as an impurity.
[0020] FIGs. 1a, 1b and 1c depict a tyre monitor. A tyre monitor 101 can be present at one or more tyres of the vehicle 103, such that each tyre monitor 101 can monitor the quality of the air inside the tyre. In an embodiment, the tyre monitor 101 can be a miniaturized micro-electro-mechanical systems (MEMS) device.
[0021] In an embodiment, a controller 102 can be integrated with the tyre monitor 101 (as depicted in FIG. 1a). The controller 102 can be an independent module. In an embodiment herein, the controller 102 can be present in the vehicle 103 (as depicted in FIG. 1b). The tyre monitor 101 can communicate with the controller 102 using at least one of a wired means (such as a bus, CAN bus, and so on) or a wireless means (such as Bluetooth, Wi-Fi Direct, Wi-Fi, cellular communication networks, radio frequency communication means, and so on). In an embodiment, the controller 102 can be integrated with an ECU (Engine Control Unit) present in the vehicle 103. In an embodiment herein, the controller 102 can be present external to the vehicle 103 (as depicted in FIG. 1c). In an example, the controller 102 can be present in a device belonging to a user of the vehicle 103 (such as a mobile phone, smart phone, tablet, computer, wearable computing device, a security system of the vehicle 103, and so on). In an example, the controller 102 can be a dedicated module present external to the vehicle 103.
[0022] The controller 102 can communicate with other entities such as vehicle systems (such as the infotainment systems, dashboard systems, ECU, and so on), user devices, data servers, application servers, the cloud, or any other device as configured by the user or any other authorized person.
[0023] FIG. 2a depicts the tyre monitor comprising of a controller. The tyre monitor 101 comprises of the controller 102 (as depicted in FIG. 1a). The controller 102, as depicted, comprises of an air quality sensor 201, a memory 202, an impurity detection unit 203, and a communication interface 204. The memory 202 can be at least one of a volatile memory or a non-volatile memory. The memory 202 can be present internally to the controller 102. The memory 202 can be present in another system present in the vehicle 103, such as the ECU, and the controller 102 can store and access data from the memory 202. The memory 202 can comprise of data such as pre-configured thresholds for the impurity presence in the tyres, user configurations (which can include the type of impurities to be detected, the threshold levels, actions to be taken on detecting impurities, and so on), and so on. For example, if the user is filling the tyre with nitrogen, then the user can configure the tyre monitor 101 to consider presence of oxygen within the tyre as an impurity. In another example, if the user is filling the tyre with normal air, then the user can configure the tyre monitor 101 to consider the presence of moisture content greater than a pre-defined threshold as an impurity. The memory 202 can comprise of information measured by the tyre monitor 101. The memory 202 can comprise of results of operations performed by the air quality sensor 201. The memory 202 can comprise of time stamps of the received information.
[0024] The communication interface 203 can enable the controller 102 to communicate with at least one external entity. Examples of the external entity can be but not limited to the vehicle systems (such as the infotainment systems, dashboard systems, ECU, and so on), user device(s), data servers, application servers, the cloud, or any other device as configured by the user or any other authorized person.
[0025] The air quality sensor 201 can comprise of one or more sensors that can be configured to measure the constituents of the air present inside the tyre. The impurity detection unit 203 can receive the measurements from the air quality sensor 201. The impurity detection unit 203 can check for any impurities in the measurements by comparing to baseline entries and corresponding values of the expected constituents of the air that should be present in the tyre.
[0026] In an embodiment herein, the impurity detection unit 203 can estimate a Coefficient of correlation (R). R is a relative measure of the association between the observed and predicted values. It can vary from 0 (which indicates no correlation to +1 (which indicates perfect correlation). A value of R close to 1.0 implies good agreement between the observed and predicted values i.e. good model performance.
R = ((Co-C_o)(Cp-C_p))/sCpsCo
[0027] The impurity detection unit 203 can determine a Coefficient of Determination (R2). R2 is the square of coefficient of correlation, determines the proportion of variance that can be explained by the model.
[0028] The impurity detection unit 203 can determine a Root Mean Square Error (RMSE). RMSE is a measure of the differences between values predicted by a model and the observed values and is expressed as follows:
RMSE= ((Co-Cp)2 )/(vRMSE=(Co-Cp)2¯)
[0029] The impurity detection unit 203 can determine a Normalized Mean Square Error (NMSE). NMSE is a measure of performance, emphasizes the scatter in the entire data set and is defined as follows:
NMSE=((Co-Cp)2)/(C_o.Cp)
[0030] The impurity detection unit 203 can perform normalization by
C_o.C_pC_o.C_p
[0031] Normalization ensures that NMSE will not be biased towards models that over predict or under predict. Ideal value for NMSE is zero. Smaller values of NMSE denote better model performance.
[0032] The impurity detection unit 203 can estimate Fractional Bias (FB). FB is a performance measure known as the normalized or fractional bias of the mean concentrations of the detected impurities:

FB=(C__o-C__P)0.5(C__o+C__P)FB=(C__o-C__P)0.5(C__o+C__P)
[0033] Where:
Cp: model predictions,
Co: observations,
Overbar
(C¯¯)(C¯): Average over the dataset, and
sCsC: standard deviation over the data set.

[0034] On detecting presence of at least one impurity and the level of the impurities in the air is higher than a pre-defined threshold, the impurity detection unit 203 can perform at least one pre-configured action, such as providing an alert to the user (using at least one of a user device, an infotainment system present in the vehicle 103, the dashboard system, warning light(s), an audio alert, and so on), storing the alert and related data (such as the nature/type of impurity, detected levels, time stamps, operating point characteristics, and so on) in a pre-configured location (such as at least one of the memory 202, the application server, the data server, the cloud, at least one user device, and so on) and so on.
[0035] For example, consider that a nail has penetrated the tyre and at least a portion of the nail is protruding into the inner space of the tyre. The metal particles from the nail can be present within the air present in the tyre.
[0036] In an embodiment herein, the tyre monitor 101 can comprise of at least one additional sensor for monitoring additional factors related to the tyre such as pressure, movement, temperature, and so on.
[0037] FIG. 2b depicts a tyre monitoring system. The tyre monitoring system comprises of the tyre monitor 101 and the controller 102 (as depicted in FIGs. 1b and 1c). The tyre monitor 101 comprises of at least one air quality sensor 201 and the communication interface 205. The air quality sensor 201 can measure the constituents of the air present inside the tyre. The measured data can be communicated to the controller 102 using the communication interface 205 in real time. The communication interface 205 can use at least one of a wired means (such as a bus, CAN bus, and so on) or a wireless means (such as Bluetooth, Wi-Fi Direct, Wi-Fi, cellular communication networks, radio frequency communication means, and so on) for communicating the data to the controller 102.
[0038] In an embodiment herein, the tyre monitor 101 can comprise of at least one additional sensor for monitoring additional factors related to the tyre such as pressure, movement, temperature, and so on.
[0039] Further, the tyre management system comprises the controller 102 that acquires the measured data from the tyre monitor 101 and is configured to process the sensed data for further analysis. The impurity detection unit 203 can check for any impurities in the measurements by comparing to a baseline entries and corresponding values of the expected constituents of the air that should be present in the tyre.
[0040] In an embodiment herein, the impurity detection unit 203 can estimate a Coefficient of correlation (R). R is a relative measure of the association between the observed and predicted values. It can vary from 0 (which indicates no correlation to +1 (which indicates perfect correlation). A value of R close to 1.0 implies good agreement between the observed and predicted values i.e. good model performance.
R = ((Co-C_o)(Cp-C_p))/sCpsCo
[0041] The impurity detection unit 203 can determine a Coefficient Of Determination (R2). R2 is the square of coefficient of correlation, determines the proportion of variance that can be explained by the model.
[0042] The impurity detection unit 203 can determine a Root Mean Square Error (RMSE). RMSE is a measure of the differences between values predicted by a model and the observed values and is expressed as follows:
RMSE= ((Co-Cp)2 )/(vRMSE=(Co-Cp)2¯)
[0043] The impurity detection unit 203 can determine a Normalized Mean Square Error (NMSE). NMSE is a measure of performance, emphasizes the scatter in the data set and is defined as follows:
NMSE=((Co-Cp)2)/(C_o.Cp)
[0044] The impurity detection unit 203 can perform normalization by
C_o.C_pC_o.C_p
Normalization ensures that NMSE will not be biased towards models that over predict or under predict. Ideal value for NMSE is zero. Smaller values of NMSE denote better model performance.
The impurity detection unit 203 can estimate Fractional Bias (FB). FB is a performance measure known as the normalized or fractional bias of the mean concentrations:
FB=(C__o-C__P)0.5(C__o+C__P)FB=(C__o-C__P)0.5(C__o+C__P)
[0047] Where:
Cp: model predictions,
Co: observations,
Overbar
(C¯¯)(C¯): Average over the dataset, and
sCsC: standard deviation over the data set.
[0048] On detecting presence of at least one impurity and the level of the impurities in the air is higher than a pre-defined threshold, the impurity detection unit 203 can perform at least one pre-configured action, such as providing an alert to the user (using at least one of a user device, an infotainment system present in the vehicle 103, the dashboard system, warning light(s), an audio alert, and so on), storing the alert and related data (such as the nature/type of impurity, detected levels, time stamps, operating point characteristics, and so on) in a pre-configured location (such as at least one of the memory 202, the application server, the data server, the cloud, at least one user device, and so on) and so on.
[0049] In an example depicted in FIG. 2c, the air quality sensor 201 comprises of a VOC (Volatile Organic Compound) sensor 206 and a NOx sensor 207. VOCs are carbon based (organic) chemicals (compounds) found in man-made and naturally occurring solids and liquids. They evaporate easily at room temperature. The VOC sensor 206 can use MEMS and metal oxide semiconductors, as they have a high level of sensitivity hereby increasing their capability of detecting VOCs. The VOC sensor 206 can detect VOCs in the tyre in real-time. The VOC sensor 206 can detect differences in the level of VOCs over a broad detection range. The VOC sensor 206 can also track other factors that impact air quality such as temperature and humidity. The user can customize the VOC sensor 206, so that the VOC sensor 206 can easily select the preferred factors/impurities/threshold to be determined.
[0050] The NOx sensor 207 is a high-temperature device, which can detect nitrogen oxides (NOx) present in the tyre. The NOx sensor 207 can detect NOx in the presence of oxygen. The NOx sensor 207 can be a continuous sensor-based nitrogen oxide analyzer used to detect pollutant nitrogen oxide gas in the air present in the tyre. In an embodiment herein, the NOx sensor 207 can incorporate gas sensitive semiconductor (GSS) sensing technology.
[0051] FIG. 3 is a flowchart depicting a process of the controller monitoring a tyre. The tyre monitor 101 measures (301) the constituents of the air present inside the tyre. The controller 102 compares (302) the measured data to the baseline entries and corresponding values of the expected constituents of the air that should be present in the tyre. The controller 102 checks (303) if any impurities are present by comparing the measured data to the baseline entries and corresponding values of the expected constituents of the air that should be present in the tyre If the controller 102 determines (303) that there is at least one impurity, the controller 102 checks (304) if the measured level of impurities is greater than the pre-defined threshold. If the measured level of impurities is greater than the pre-defined threshold, the controller 102 performs (305) at least one pre-configured action, such as providing an alert to the user, and storing the alert and related data in a pre-configured location, and so on. The various actions in method 300 may be performed in the order presented, in a different order or simultaneously. Further, in some embodiments, some actions listed in FIG. 3 may be omitted.
[0052] The embodiments disclosed herein can be implemented through at least one software program running on at least one hardware device and performing network management functions to control the network elements. The network elements shown in Figs. 1, and 2 include blocks, which can be at least one of a hardware device, or a combination of hardware device and software module.
[0053] The embodiment disclosed herein methods and systems for monitoring and communicating abnormalities detected in the wheels/tyres of a vehicle 103. Therefore, it is understood that the scope of the protection is extended to such a program and in addition to a computer readable means having a message therein, such computer readable storage means contain program code means for implementation of one or more steps of the method, when the program runs on a server or mobile device or any suitable programmable device. The method is implemented in a preferred embodiment through or together with a software program written in e.g. Very high speed integrated circuit Hardware Description Language (VHDL) another programming language, or implemented by one or more VHDL or several software modules being executed on at least one hardware device. The hardware device can be any kind of portable device that can be programmed. The device may also include means which could be e.g. hardware means like e.g. an ASIC, or a combination of hardware and software means, e.g. an ASIC and an FPGA, or at least one microprocessor and at least one memory with software modules located therein. The method embodiments described herein could be implemented partly in hardware and partly in software. Alternatively, the invention may be implemented on different hardware devices, e.g. using a plurality of CPUs.
[0054] The foregoing description of the specific embodiments will so fully reveal the general nature of the embodiments herein that others can, by applying current knowledge, readily modify and/or adapt for various applications such specific embodiments without departing from the generic concept, and, therefore, such adaptations and modifications should and are intended to be comprehended within the meaning and range of equivalents of the disclosed embodiments. It is to be understood that the phraseology or terminology employed herein is for the purpose of description and not of limitation. Therefore, while the embodiments herein have been described in terms of preferred embodiments, those skilled in the art will recognize that the embodiments herein can be practiced with modification within the spirit and scope of the embodiments as described herein.
,CLAIMS:STATEMENT OF CLAIMS
We Claim:
1. A method for detecting impurities inside a tyre, the method comprising
measuring constituents of air present in the tyre by an air quality sensor (201) in a tyre monitor (101);
determining if at least one impurity is present in the measured constituents by a controller (102);
checking if level of the at least one determined impurity is greater than a pre-defined threshold by the controller (102); and
performing at least one action by the controller (102), if the level of the at least one determined impurity is greater than a pre-defined threshold.

2. The method, as claimed in claim 1, wherein the detected impurities is at least one of a solid impurity; and a gaseous impurity.

3. The method, as claimed in claim 1, wherein the air quality sensor (201) comprises at least one of a Volatile Organic Compound (VOC) sensor (206); and a nitrogen oxides (NOx) sensor (207).

4. The method, as claimed in claim 3, wherein the VOC sensor (206) comprises Micro-Electro-Mechanical Systems (MEMS) and metal oxide semiconductors.

5. The method, as claimed in claim 3, wherein the NOx sensor (207) comprises gas sensitive semiconductor (GSS) sensing technology.

6. The method, as claimed in claim 1, wherein determining if at least one impurity is present in the measured constituents further comprises
estimating a coefficient of correlation as a relative measure of association between observed and predicted values by the controller (102);
determining a coefficient of determination as square of the coefficient of correlation by the controller (102);
determining a Root Mean Square Error (RMSE) by the controller (102);
determining a Normalized Mean Square Error (NMSE) by the controller (102);
normalizing the NMSE by the controller (102);
estimating fractional bias by the controller (102); and
determining the levels of the impurities by the controller (102).

7. The method, as claimed in claim 1, wherein the at least one action comprises at least one of
providing an alert to the user by the controller (102); and
storing the alert and related data in a pre-configured location by the controller (102).

8. A system for detecting impurities inside a tyre, the system comprising
at least one tyre monitor (101) configured for
measuring constituents of air present in the tyre by an air quality sensor (201) in the tyre monitor (101);
communicating the measured constituents to a controller (102); and
the controller (102) configured for
determining if at least one impurity is present in the measured constituents;
checking if level of the at least one determined impurity is greater than a pre-defined threshold; and
performing at least one action, if the level of the at least one determined impurity is greater than a pre-defined threshold.

9. The system, as claimed in claim 8, wherein the detected impurities is at least one of a solid impurity; and a gaseous impurity.

10. The system, as claimed in claim 8, wherein the air quality sensor (201) comprises at least one of a Volatile Organic Compound (VOC) sensor (206); and a nitrogen oxides (NOx) sensor (207).

11. The system, as claimed in claim 10, wherein the VOC sensor (206) comprises Micro-Electro-Mechanical Systems (MEMS) and metal oxide semiconductors.

12. The system, as claimed in claim 10, wherein the NOx sensor (207) comprises gas sensitive semiconductor (GSS) sensing technology.

13. The system, as claimed in claim 8, wherein the controller (102) is configured for determining if at least one impurity is present in the measured constituents by
estimating a coefficient of correlation as a relative measure of association between observed and predicted values;
determining a coefficient of determination as square of the coefficient of correlation;
determining a Root Mean Square Error (RMSE);
determining a Normalized Mean Square Error (NMSE);
normalizing the NMSE;
estimating fractional bias; and
determining the levels of the impurities.

14. The system, as claimed in claim 8, wherein the at least one action comprises at least one of
providing an alert to the user by the controller (102); and
storing the alert and related data in a pre-configured location by the controller (102).

15. A tyre monitor (101) for detecting impurities inside a tyre, the tyre monitor (101) comprising
an air quality sensor (201) configured for
measuring constituents of air present in the tyre; and
a controller (102) configured for
determining if at least one impurity is present in the measured constituents;
checking if level of the at least one determined impurity is greater than a pre-defined threshold; and
performing at least one action, if the level of the at least one determined impurity is greater than a pre-defined threshold.

16. The tyre monitor, as claimed in claim 15, wherein the detected impurities is at least one of a solid impurity; and a gaseous impurity.

17. The tyre monitor, as claimed in claim 15, wherein the air quality sensor (201) comprises at least one of a Volatile Organic Compound (VOC) sensor (206); and a nitrogen oxides (NOx) sensor (207).

18. The tyre monitor, as claimed in claim 17, wherein the VOC sensor (206) comprises Micro-Electro-Mechanical Systems (MEMS) and metal oxide semiconductors.

19. The tyre monitor, as claimed in claim 17, wherein the NOx sensor (207) comprises gas sensitive semiconductor (GSS) sensing technology.

20. The tyre monitor, as claimed in claim 15, wherein the controller (102) is configured for determining if at least one impurity is present in the measured constituents by
estimating a coefficient of correlation as a relative measure of association between observed and predicted values;
determining a coefficient of determination as square of the coefficient of correlation;
determining a Root Mean Square Error (RMSE);
determining a Normalized Mean Square Error (NMSE);
normalizing the NMSE;
estimating fractional bias; and
determining the levels of the impurities.

21. The tyre monitor, as claimed in claim 15, wherein the at least one action comprises at least one of
providing an alert to the user; and
storing the alert and related data in a pre-configured location.