WO2018184092A1

WO2018184092A1 - Bicycle performance tracking system and method

Info

Publication number: WO2018184092A1
Application number: PCT/CA2018/000066
Authority: WO
Inventors: Marc Graveline
Original assignee: Notio Technologies Inc.
Priority date: 2017-04-04
Filing date: 2018-03-29
Publication date: 2018-10-11

Abstract

A bicycle performance tracking system and method includes sensors mounted on the bicycle and onto the rider. These sensors supply data to an on-board controller that time stamps the data to thereby create a timeline of the various events recorded by the sensors and thus provide data validation, allow bad data filtering and provide context information for the various events occurring during training.

Description

TITLE

Bicycle Performance Tracking System and Method

FIELD

[0001] The present disclosure generally relates to bicycles. More specifically, the present disclosure is concerned with a bicycle performance tracking system and method.

BACKGROUND

[0002] Bicycle-related measurement systems have increased their sophistication over the years. Such systems have evolved from older, heavy mechanical speedometers to modern electronic units capable of monitoring and displaying a number of cycling performance characteristics.

[0003] These so-called bicycle computers, which, for example, track and electronically display speed, distance, and so forth, are now common in the art.

[0004] Some of the bicycle computer may output the tracked performance so that the user may review his performance during training.

BRIEF DESCRIPTION OF THE DRAWINGS [0005] In the appended drawings:

[0006] Figure 1 is a bloc diagram of a bicycle performance tracking system according to an illustrative embodiment; and [0007] Figure 2 is a flow chart of a bicycle performance tracking method according to an illustrative embodiment.

DETAILED DESCRIPTION

[0008] An object is generally to provide an improved bicycle performance tracking system including different sensors that allow a better understanding of the use of a bicycle.

[0009] According to an illustrative embodiment, there is provided a bicycle performance tracking system comprising: a plurality of sensors for gathering data related to a use of a bicycle; and a controller coupled to the plurality of sensors so as to receive the data therefrom; the controller being configured for i) time stamping the data received from the plurality of sensors, resulting in time-stamped data, and ii) creating a timeline including at least some of the time-stamped data.

[0010] According to another aspect, there is provided a bicycle performance tracking method comprising: real-time gathering, from a plurality of sensors, of data related to a use of a bicycle; time stamping the data received from the plurality of sensors, resulting in time-stamped data; and creating a timeline including at least some of the time-stamped data.

[0011] The use of the word "a" or "an" when used in conjunction with the term "comprising" in the claims and/or the specification may mean "one", but it is also consistent with the meaning of "one or more", "at least one", and "one or more than one". Similarly, the word "another" may mean at least a second or more. [0012] As used in this specification and claim(s), the words

"comprising" (and any form of comprising, such as "comprise" and "comprises"), "having" (and any form of having, such as "have" and "has"), "including" (and any form of including, such as "include" and "includes") or "containing" (and any form of containing, such as "contain" and "contains"), are inclusive or open-ended and do not exclude additional, unrecited elements or process steps.

[0013] The term "about" is used to indicate that a value includes an inherent variation of error for the device or the method being employed to determine the value.

[0014] The expressions "connected" and "coupled" are interchangeable and should be construed herein and in the appended claims broadly so as to include any cooperative or passive association between mechanical parts or components. For example, such parts may be assembled together by direct coupling or connection, or indirectly coupled or connected using further parts. The coupling and connection can also be remote, using for example a magnetic field or else.

[0015] Other objects, advantages and features of the bicycle performance tracking system will become more apparent upon reading of the following non-restrictive description of illustrative embodiments thereof, given by way of example only with reference to the accompanying drawings.

[0016] Generally stated, the illustrative embodiment of the bicycle performance tracking system includes sensors mounted on the bicycle and onto the rider. These sensors supply data to an on-board controller that time stamps the data to thereby create a timeline of the various events recorded by the sensors and thus provide data validation, allow bad data filtering and provide context information for the various events occurring during training as will be better described hereinbelow.

Description of the tracking system

[0017] The on-board controller 10 is a computer that has the main tasks of acquiring data from the various sensors; transmitting the data to an external computer (not shown); time stamping the data coming from the various sensors, and selectively communicating with the cellular network.

[0018] Accordingly, the tracking system includes a cellular access 12 in bi-directional communication with the on-board controller 10. One skilled in the art will understand that this cellular access 12 may be allowed via a hardware component coupled to or part of the controller 10, allowing the controller 10 to communicate with the internet, for example, via a cellular telephone network or directly to a smart phone, tablet or any wearable device owned by the user, for example. Accordingly, the cellular access 12 can use various technologies to communicate with the world outside the tracking system. These various technologies include, amongst others, Bluetooth and Wi-Fi.

[0019] The GPS 14 is conventionally used to gather position data and supply it to the controller 10. As will be understood by one skilled in the art, the tracking system may use a conventional GPS or could use a GPS provided on a mobile phone or tablet of the user. Alternatively, the GPS from a bike computer could also be used.

[0020] The aerodynamic sensor 16 includes an air-speed sensor that determines wind speed. As will be apparent to those skilled in the art, conventionally, air-speed sensors, also known as aerosticks, include a pilot tube leading to a differential pressure sensor.

[0021] The biomechanics sensors 18 include various body position sensors positioned on the rider to monitor the position of the rider on the bicycle. These sensors 18 are positioned, for example, on the arms, helmet, torso and legs of the rider and therefore may supply the rider's position, in realtime, to the controller 10. One skilled in the art will know that these various sensors can be separately applied to the rider or could be part of the rider's clothing as wearable sensors.

[0022] The riding sensors 20 include various sensors provided on the bicycle to determine its 3d orientation via roll, yaw and pitch sensors (for the frame, for the handlebar or for both) and to determine if the bike is braking or accelerating. Furthermore, the riding sensor suite 20 includes gearing sensors that detect gearing changes and supply this data to the controller 10.

[0023] The physiologic sensors 22 are worn by the rider and supply various data such as heart rate (HR), heart rate variability (HRV) and Oxygenation level to the controller 10. Again, one skilled in the art will know that these various sensors can be separately applied to the rider or could be part of the rider's clothing as wearable sensors.

[0024] The external world sensors 24 include proximity sensors that detect other vehicles in proximity of the bicycle.

[0025] Traditional sensors 26 are also provided in the tracking system. These traditional sensors are often found on bicycle and supply power, speed and/or cadence data to the controller 10. [0026] Finally, environmental sensors 28 monitor temperature, humidity and/or atmospheric pressure in the vicinity of the bicycle.

[0027] As mentioned hereinabove, all the data supplied by the sensors 14-28 to the controller 10 is time stamped so as to allow a timeline to be created during or after the training session.

[0028] As non-limiting examples, the various elements of the tracking system such as the controller 10 and the various sensors detailed hereinabove may be embodied by the following sensors:

• On-board controller 10: Nordic NRF52832;

• Cellular access 12: sara-G3 Series from u-blox;

• GPS 14: GPS sensor model MediaTek MTK3339 made by

Ultimate GPS;

• Air-Speed sensor (Aerostick): Made by Notio Technologies

Inc. (using a differential pressure sensor from Firstsensor LMI);

• Temperature sensor: Bosch model BME280;

• Atmospheric pressure sensor: Bosch model BME280;

• Humidity sensor: Bosch model BME280;

• Roll/Yaw/Pitch Steering sensors: Bosch model BMI0055

(accelerometer/gyroscope/magnetometer);

• Roll/Yaw/Pitch Frame sensors: Bosch model BMI0055;

• Biomechanics sensors (fit): Notch

• HRV sensor: 4iiii /Polar model MTK3339;

• HR: Garmin heart rate monitor part number 010-10997-00;

• Muscle Oxygenation: Moxy model Moxy monitor;

• Power sensor: Quarq; • Cadence: Garmin model GSC10;

• Speed: Garmin model GSC10;

• Proximity: Maxbotix ultrasonic;

• Gearing: Garmin DFLY.

[0029] The CDA (Coefficient of Drag) can be determined by the controller 10, or by a computing device coupled thereto, using data from the sensors 14-28.

[0030] Generally stated, as is known to those skilled in the art, CDA may be viewed as a measure of how efficiently the rider converts the power into forward speed. In other words, the lower is the CDA, the faster the rider goes for the same level of effort. CDA is also a shorthand for CD ^* A. CD is the coefficient of drag, and A is the frontal area of the rider and the bicycle.

[0031] The CDA can be obtained by the following formula:

[0032] Power Total = Prr + Pcda + Pi + Palt

[0033] Where:

• Prr : Power to overcome the rolling resistance;

• Pcda: Power to overcome the aerodynamic resistance;

• Pi: Power to overcome inertia; and

• Palt: Power to overcome the altitude change.

[0034] With the data from the various sensors 14-28, the controller 0 can calculate Prr using the speed, mass of the rider and a rolling resistance coefficient. The controller 10 may also calculate Pi since the change of speed is required and available. Similarly, for the calculation of the Palt, the inclination and the mass of the rider are required and available.

[0035] Accordingly, the Pcda can be calculated since it is equal to

Power total - Prr - Pi - Palt.

[0036] And since:

[0037] Pcda = (Air density * ground speed ^* airspeed^{2 *} CDA)/2

[0038] It is therefore possible for the controller 10 to calculate the

CDA in real-time.

[0039] Other parameters, including for example the mass of the rider, can be entered by the rider in the controller 10.

[0040] While the above description discusses the time stamping of the data coming from the various sensors to create a timeline, the on-board controller 10 could alternatively provide a common clock to the various sensors so that their respective data may accurately be positioned on a virtual timeline. For example, the real-time clock of the GPS 14 could be used.

[0041] Turning now briefly to Figure 2 of the appended drawings, the bicycle performance tracking method 100 will be described.

[0042] The first step 102 of this performance tracking method is the gathering of data related to the use of a bicycle from a plurality of sensors and in real time. As mentioned above, these sensors are provided on the bicycle or directly on the rider. [0043] Then, the data is time-stamped in step 104.

[0044] Finally, in step 106, a timeline is created using at least some of the time-stamped data.

[0045] It is believed that one skilled in the art may configure a controller to implement the method 100.

Data validation and improvement

[0046] As mentioned hereinabove, having the data from all the above described sensors 14-28 on a single timeline allows the user to validate data coming from particular sensors with data coming from other sensors.

[0047] Indeed, sensor precision may always be improved and may yield more accurate calculations of the CDA, for example. In the above- described system, some of the sensors, alone or in combination may help improve the precision of other sensors.

[0048] As a first example, the altitude is used in the CDA calculation.

Accordingly, the precision of the basic altitude inferred from the atmospheric pressure sensor (part of the environmental sensors 28) may be improved by the GPS 14. For example, the controller 10 may send GPS data to an external server (not shown) via the cellular access 12 to receive precise altitude data. This can be done in real-time or once the data is transferred to an external computer (not shown) for analysis.

[0049] Other methods can be used to improve the precision of the altitude measurement. For example, since we know the speed and attitude of the bicycle via the sensors, it is possible to determine the altitude at the beginning of a ride and to compute the instantaneous altitude via the speed and attitude data of the bicycle.

[0050] It is therefore possible to only uses the accelerometer, gyroscope and speed measurements to compute the altitude variation. The gyroscopes are used to propagate the roll and pitch angles of the bike in order to project the longitudinal speed into its vertical component. This vertical speed is used to compute the altitude variation. This algorithm is interesting since it is not affected by the external environment (e.g. temperature and pressure variations) but it requires a precise alignment of the sensor and bike frames.

[0051] As another example, the aerodynamic data supplied by the aerostick can be improved via the yaw sensor of the handlebar. Indeed, since the aerostick is generally mounted to the frame so as to face forward, the value sensed may be improved by the controller 10 when the handlebar is turned so that the bicycle can change direction. Since the controller knows the angle of the handlebar, it can compensate for the direction change of the bicycle.

[0052] As mentioned hereinabove, the rolling resistance of the tires on the ground is used in the calculation of the CDA. The basic measure of the rolling resistance can be improved by knowing the 3d orientation of the bicycle since the rolling resistance varies depending on which portion of the tires touches the ground. Accordingly, the data supplied by the pitch, yaw and roll sensors of the riding sensors suite 20 are used to improve the value of the rolling resistance and therefore the value of the CDA.

[0053] As another example, as mentioned hereinabove, in the determination of Palt the inclination of the road can be used. To ensure that the controller 10 has the best estimate of this road inclination, the data coming from the pitch sensor of the riding sensor suite 20 can be improved by measuring the altitude difference between two points on the road (for example using the GPS data), knowing the distance between these two points. Alternatively or complementarily, the controller 10 may be configured as to use the atmospheric pressure difference between these two points.

[0054] As another example, the air density, which is used to accurately determine wind speed, is determined by the environment sensors 28 and thereby allows the improvement of the data from the aerostick sensor.

[0055] As another example, when a rider is training in a loop setting, the controller 10 may verify that the altitude measured via the atmospheric pressure sensor is the correct altitude by comparing the current measured altitude with the previous altitude measured when the rider previously passed the same location in the loop.

[0056] To calculate the altitude, the atmospheric pressure sensor uses the sea level atmospheric pressure. Instead of estimating this pressure, the controller 10 may use the cellular access 12 to retrieve this information from the Internet, to thereby improve the altitude determination.

[0057] If many riders ride in a swarm and are equipped with the present tracking system, the data from these riders may be pooled to improve the data from the environmental and aerodynamic sensors for all the riders present. Furthermore, this data pooling may help in finding faulty sensors should a particular rider supply data vastly different from the others.

[0058] The GPS 14 and the atmospheric pressure data may be used to determine the inclination of the bike. This data may be improved by comparing the data with the data coming from the inclinometer of the riding sensors.

[0059] As mentioned hereinabove, the calculation of the CDA uses the rolling resistance as a variable. The rolling resistance is generally constant for a particular training since the bicycle features and the weight of the user does not significantly changes during this time. However, scrubbing, steering and vibrations measured at the handlebar level may change the value of the rolling resistance. Accordingly, when the controller 10 detects such scrubbing, steering and handlebar vibrations, it may calculate recalculate the rolling resistance value for this portion of the training session in view of calculating a more accurate CDA.

[0060] It is possible to validate some of the CDA changes with the

Yaw sensor of the riding sensors suite 20. Indeed, a change in the direction of the bicycle causes a change in the direction of the wind hitting the rider and the bicycle, which impacts the CDA value.

[0061] As mentioned hereinabove, the rolling resistance is generally considered a constant within a particular training. However, should the rider enter a curve at high speed, the change in the orientation of the G force on the bike and the rider changes the value of the rolling resistance. Since the riding sensor suite 20 may detect the roll of the bike and the traditional sensor suite 26 may supply the instantaneous speed, the controller 10 may be configured to correct the rolling resistance value in those cases.

[0062] In some cases, when the rider is taking a pronounced curve at high speed and is angled with respect to the vertical, the speed of the rider is not equal to the speed of the wheels since the radius travelled by the rider is less than the radius travelled by the wheels. Accordingly, to improve the calculation of the CDA, which uses the speed of the rider as a data, the controller may determine the speed of the rider from the speed of the wheels and the inclination of the bicycle.

Data filtering

[0063] All the data supplied by the sensors is not necessary good data and further data coming from other sensors may help discriminate between good and bad data.

[0064] The filtering of untrustworthy CDA readings will be shown as an example of data filtering. As mentioned above, the CDA is an interesting factor to consider since a high proportion of the power generated by the rider is used to fight the CDA. However, in some instances the data from the aerostick, used in the determination of the CDA is not trustworthy. For example, when the proximity sensor determines that a vehicle passes the rider, it creates an air disturbance that causes the CDA to show a spike that should not be considered when averaging of the data is done. Accordingly, the controller 10 is so configured as to reject the aerostick data when the proximity sensor detects a vehicle passing the rider.

[0065] Another example is when the rider has to brake in order to avoid an obstacle, the changes it produces in the CDA should not be taken into account in the CDA averaging.

[0066] Speed changes and instantaneous speed are used in the calculation of the CDA. To validate the speed supplied by the speed meter of the traditional sensors suite 26, the controller may use the acceleration data supplied by the accelerometer of the riding sensors suite 20 and/or the braking data from the brake sensor thereof. Position data coming from the GPS 14 could also be used to validate the instantaneous speed of the rider.

[0067] As will be apparent to one skilled in the art, speed data may be determined by the GPS 14 and by the speed sensor, usually provided on one wheel of the bike. When speed data abruptly changes, the controller 10 may correlate the speed data with the acceleration data from the acceleration sensor and/or with the brake sensor to determine if the speed data is correct and to reject it should no acceleration or braking be detected.

Context information

[0068] After the training session, the system allows the rider to review his or her performance by analyzing the timeline created with the time stamped data from the various sensors 14-28. The controller 10 or the external computer (not shown) may use the data to highlight performances changes during the training session or by comparing the present training session with previous sessions.

[0069] Indeed, since all the data is time stamped and can be viewed as a timeline, some variations of the performances or behavior can be explained by data from other sensors.

[0070] As a first example, an elevation of the heart rate of the user may be explained for example by temperature, humidity or altitude variations or by the rider position, which are all data available from the sensors 14-28. [0071] As a second example, an increase in the CDA may be explained by the rider position. Indeed, since the rider position affects the frontal area is affects the CDA, position changes may explain changes in the CDA calculated value. The rider may thus appreciate how is position affects the speed and the power required to go at the desired speed.

[0072] Accordingly, the user may, for example, view the effects that small body position variations may have on power or HR.

[0073] For example, the rolling resistance is used in the computation of the CDA. The value of the rolling resistance is not a constant for a particular rider and/or bicycle, but varies with the attitude of the bicycle. Accordingly, the data from the riding sensors, including the roll sensor, may be used by the controller 10 to adjust the value of the rolling resistance.

[0074] Similarly, the movements of the handlebars of the bicycle also affect the value of the rolling resistance. Since the riding sensor suite 20 includes sensors, it is possible to detect yaw changes in the handlebars and to correct the rolling resistance value.

[0075] When the current training session is compared to previous training sessions, the data from the various sensors 14-28 may be used to determine the reasons behind performance variations. For example, should the HR of a particular rider developing a known power is different than usual, the controller may look at the position of the rider, from the biomechanics sensor suite 8, the fatigue of the rider, from the HRV or Oxygen sensors of the physiologic sensors suite to explain the differences in performance.

[0076] One skilled in the art will understand that not all the sensor suites described hereinabove are required. Accordingly, one could design a bicycle performance tracking system having only the sensors required for a particular type of performance analysis and tracking.

[0077] The controller 10 may have multiple other functions that consider the data from the various sensors. As a non-limiting example, if the controller 10 determines that there has been an accident involving the rider (using various sensors such as pitch, yaw, roll, HR, body position) the controller 10 may send a call for help using the cellular access 12 and supply GPS data.

[0078] While the above description refers to an external computer

(not shown) used to review data and to potentially refine portion of the data, this could be done directly onto the on-board controller 10 and the results supplied to an integrated (not shown) or external (also not shown) display screen.

[0079] It is to be understood that the bicycle performance tracking system is not limited in its application to the details of construction and parts illustrated in the accompanying drawings and described hereinabove. The bicycle performance tracking system is capable of other embodiments and of being practiced in various ways. It is also to be understood that the phraseology or terminology used herein is for the purpose of description and not limitation. Hence, although the bicycle performance tracking system has been described hereinabove by way of illustrative embodiments thereof, it can be modified, without departing from the spirit, scope and nature thereof.

[0080] The following numbered clauses are offered as further description: [0081] 1. A bicycle performance tracking system comprising:

[0082] a plurality of sensors for gathering data related to a use of a bicycle; and

[0083] a controller coupled to the plurality of sensors so as to receive the data therefrom; the controller being configured for i) time stamping the data received from the plurality of sensors, resulting in time-stamped data, and ii) creating a timeline including at least some of the time-stamped data.

[0084] 2. The bicycle performance tracking system from clause 1 , wherein the timeline is created in real-time by the controller during the use of the bicycle.

[0085] 3. The bicycle performance tracking system from clause 1 , wherein the timeline is created by the controller after the use of the bicycle.

[0086] 4. The bicycle performance tracking system as recited in any of the preceding clauses, wherein the controller is further configured for using at least some of the time-stamped data in determining further data related to the use of the bicycle.

[0087] 5. The bicycle performance tracking system as recited in any of the preceding clauses, wherein the controller includes a clock that is used in time stamping the data received from the plurality of sensors.

[0088] 6. The bicycle performance tracking system as recited in any of the preceding clauses, wherein the controller is further configured for validating or improving time-stamped data from a first sensor from the plurality of sensors using time-stamped data from at least another sensor from the plurality of sensors. [0089] 7. The bicycle performance tracking system from clause 6, further comprising a cellular access coupled to the controller; the first sensor being an atmospheric pressure sensor and said at least another sensor being a GPS tracker; wherein the controller being further configured to send time- stamped data related to the GPS via the cellular access and to receive first altitude data related thereto; the first altitude data being used by the controller to improve second altitude data inferred by the controller from the atmospheric pressure data.

[0090] 8. The bicycle performance tracking system as recited in any of clauses 6 to 7, wherein the first sensor being an atmospheric pressure sensor and at least another sensor including an accelerometer, a speed sensor and a gyroscope; wherein the controller being further configured to use time- stamped data related to the accelerometer, the speed sensor and the gyroscope to determine first altitude data; the first altitude data being used by the controller to improve second altitude data inferred by the controller from the atmospheric pressure data.

[0091] 9. The bicycle performance tracking system as recited in any of clauses 6 to 8, wherein the first sensor is an aerostick and at least another sensor includes a yaw sensor; the controller being configured to improve time- stamped aerodynamic data related to the aerostick using time-stamped data associated to the yaw sensor.

[0092] 10. The bicycle performance tracking system as recited in any of clauses 6 to 9, wherein the first sensor measures data related to the rolling resistance of the tires and at least another sensor includes pitch, yaw and roll sensors; the controller being configured to improve time-stamped rolling resistance data from the first sensor using time-stamped data from the pitch, yaw and roll sensors.

[0093] 11. The bicycle performance tracking system as recited in any of clauses 6 to 10, wherein the first sensor is an aerostick sensor and at least another sensor includes an environmental sensor.

[0094] 12. The bicycle performance tracking system as recited in any of clauses 6 to 1 , wherein the controller is further coupled to another similar bicycle performance tracking system; the controller being further configured to received time-stamped data from said another similar bicycle performance tracking system and to use the time-stamped data from said another similar bicycle performance tracking system in validating time-stamped data from one of the plurality of sensors.

[0095] 13. The bicycle performance tracking system as recited in any of the preceding clauses, wherein the controller is further coupled to another similar bicycle performance tracking system; the controller being further configured to received time-stamped data from said another similar bicycle performance tracking system and to use the time-stamped data from said another similar bicycle performance tracking system in improving or discriminating the time-stamped data from one of the plurality of sensors.

[0096] 14. The bicycle performance tracking system as recited in any of the preceding clauses, wherein the controller is further configured for identifying in the timeline time-stamped data indicative of changes in the use of the bicycle.

[0097] 15. The bicycle performance tracking system from clause 14, wherein the time-stamped data are associated to a training session; the controller being configured to use time-stamped data from another training session when identifying in the timeline time-stamped data indicative of changes in the use of the bicycle.

[0098] 16. The bicycle performance tracking system as recited in any of the preceding clauses, wherein the controller is further configured for selectively ignoring time-stamped data corresponding to a selected sensor from the plurality of sensors when time-stamped data corresponding to at least another one of the plurality of sensors corresponds to predetermined criteria.

[0099] 17. The bicycle performance tracking system from clause 16, wherein the selected sensor is an aerostick sensor and the at least another one of the plurality of sensors includes a proximity sensor; the predetermined criteria being a detection of a vehicle by the proximity sensor.

[00100] 18. The bicycle performance tracking system as recited in any of clauses 16 to 17, wherein the selected sensor is a speed sensor and the at least another one of the plurality of sensors includes at least one of a brake sensor and an acceleration sensor; the predetermined criteria being a detection of an acceleration or braking.

[00101] 19. The bicycle performance tracking system as recited in any of the preceding clauses, wherein the plurality of sensors are selected from the group consisting of aerodynamic sensors, biomechanics sensors, riding sensors, physiologic sensors, external world sensors, traditional sensors and environmental sensors.

[00102] 20. A bicycle performance tracking method comprising:

[00103] real-time gathering, from a plurality of sensors, of data related to a use of a bicycle;

[00104] time stamping the data received from the plurality of sensors, resulting in time-stamped data; and

[00105] creating a timeline including at least some of the time- stamped data.

[00106] 21. The method of clause 20, further comprising using selected ones of the plurality of time-stamped data in determining further data related to the use of the bicycle.

[00107] 22. The method as recited in any of clauses 20 to 21 , further comprising validating time-stamped data from one of the plurality of sensors using time-stamped data from at least another one of the plurality of sensors.

[00108] 23. The method of clause 22, wherein said using time- stamped data from at least one other of the plurality of sensors includes using time-stamped data from sensors associated to different bicycles.

[00109] 24. The method as recited in any of clauses 20 to 23, further comprising identifying in the timeline time-stamped data indicative of changes in a use of the bicycle.

Claims

WHAT IS CLAIMED IS:

1. A bicycle performance tracking system comprising:

a plurality of sensors for gathering data related to a use of a bicycle; and

a controller coupled to the plurality of sensors so as to receive the data therefrom; the controller being configured for i) time stamping the data received from the plurality of sensors, resulting in time-stamped data, and ii) creating a timeline including at least some of the time-stamped data.

2. The bicycle performance tracking system from claim 1 , wherein the timeline is created in real-time by the controller during the use of the bicycle.

3. The bicycle performance tracking system from claim 1 , wherein the timeline is created by the controller after the use of the bicycle.

4. The bicycle performance tracking system from claim 1 , wherein the controller is further configured for using at least some of the time-stamped data in determining further data related to the use of the bicycle.

5. The bicycle performance tracking system from claim 1 , wherein the controller includes a clock that is used in time stamping the data received from the plurality of sensors.

6. The bicycle performance tracking system from claim 1 , wherein the controller is further configured for validating or improving time-stamped data from a first sensor from the plurality of sensors using time-stamped data from at least another sensor from the plurality of sensors.

7. The bicycle performance tracking system from claim 6, further comprising a cellular access coupled to the controller; the first sensor being an atmospheric pressure sensor and said at least another sensor being a GPS tracker; wherein the controller being further configured to send time-stamped data related to the GPS via the cellular access and to receive first altitude data related thereto; the first altitude data being used by the controller to improve second altitude data inferred by the controller from the atmospheric pressure data.

8. The bicycle performance tracking system from claim 6, wherein the first sensor being an atmospheric pressure sensor and at least another sensor including an accelerometer, a speed sensor and a gyroscope; wherein the controller being further configured to use time-stamped data related to the accelerometer, the speed sensor and the gyroscope to determine first altitude data; the first altitude data being used by the controller to improve second altitude data inferred by the controller from the atmospheric pressure data.

9. The bicycle performance tracking system from claim 6, wherein the first sensor is an aerostick and at least another sensor includes a yaw sensor; the controller being configured to improve time-stamped aerodynamic data related to the aerostick using time-stamped data associated to the yaw sensor.

10. The bicycle performance tracking system from claim 6, wherein the first sensor measures data related to the rolling resistance of the tires and at least another sensor includes pitch, yaw and roll sensors; the controller being configured to improve time-stamped rolling resistance data from the first sensor using time-stamped data from the pitch, yaw and roll sensors.

11. The bicycle performance tracking system from claim 6, wherein the first sensor is an aerostick sensor and at least another sensor includes an environmental sensor.

12. The bicycle performance tracking system from claim 6, wherein the controller is further coupled to another similar bicycle performance tracking system; the controller being further configured to received time-stamped data from said another similar bicycle performance tracking system and to use the time-stamped data from said another similar bicycle performance tracking system in validating time-stamped data from one of the plurality of sensors.

13. The bicycle performance tracking system from claim 1 , wherein the controller is further coupled to another similar bicycle performance tracking system; the controller being further configured to received time-stamped data from said another similar bicycle performance tracking system and to use the time-stamped data from said another similar bicycle performance tracking system in improving or discriminating the time-stamped data from one of the plurality of sensors.

14. The bicycle performance tracking system from claim 1 , wherein the controller is further configured for identifying in the timeline time-stamped data indicative of changes in the use of the bicycle.

15. The bicycle performance tracking system from claim 14, wherein the time-stamped data are associated to a training session; the controller being configured to use time-stamped data from another training session when identifying in the timeline time-stamped data indicative of changes in the use of the bicycle.

16. The bicycle performance tracking system from claim 1 , wherein the controller is further configured for selectively ignoring time-stamped data corresponding to a selected sensor from the plurality of sensors when time- stamped data corresponding to at least another one of the plurality of sensors corresponds to predetermined criteria.

17. The bicycle performance tracking system from claim 16, wherein the selected sensor is an aerostick sensor and the at least another one of the plurality of sensors includes a proximity sensor; the predetermined criteria being a detection of a vehicle by the proximity sensor.

18. The bicycle performance tracking system from claim 16, wherein the selected sensor is a speed sensor and the at least another one of the plurality of sensors includes at least one of a brake sensor and an acceleration sensor; the predetermined criteria being a detection of an acceleration or braking.

19. The bicycle performance tracking system from claim 1 , wherein the plurality of sensors are selected from the group consisting of aerodynamic sensors, biomechanics sensors, riding sensors, physiologic sensors, external world sensors, traditional sensors and environmental sensors.

20. A bicycle performance tracking method comprising:

real-time gathering, from a plurality of sensors, of data related to a use of a bicycle;

time stamping the data received from the plurality of sensors, resulting in time-stamped data; and

creating a timeline including at least some of the time-stamped data.

21. The method of claim 20, further comprising using selected ones of the plurality of time-stamped data in determining further data related to the use of the bicycle.

22. The method of claim 20, further comprising validating time- stamped data from one of the plurality of sensors using time-stamped data from at least another one of the plurality of sensors.

23. The method of claim 22, wherein said using time-stamped data from at least one other of the plurality of sensors includes using time-stamped data from sensors associated to different bicycles.

24. The method of claim 20, further comprising identifying in the timeline time-stamped data indicative of changes in a use of the bicycle.