WO2023126653A1

WO2023126653A1 - Data collection kit for attaching to a bicycle for acquiring mobility and environmental data, operation method thereof

Info

Publication number: WO2023126653A1
Application number: PCT/IB2021/062434
Authority: WO
Inventors: Ricardo Jorge RAMOS PESSOA; Rui João PEIXOTO JOSÉ; André VILARINHO TORRINHA; Ricardo CABRAL
Original assignee: Bosch Car Multimedia Portugal S.A; Universidade Do Minho
Priority date: 2021-12-28
Filing date: 2021-12-29
Publication date: 2023-07-06

Abstract

Data collection kit of parts, for attaching to a bicycle for acquiring mobility and environmental data, comprising at least two sensor-fixture sets, each sensor-fixture set comprising a sensor for acquiring external physical quantities and a fixture for coupling the sensor to the bicycle at a specific location; wherein the sensor comprises a transducer for acquiring an external physical quantity, an electronic data processor and a wireless communication means; wherein the fixture comprises a poka-yoke mounting for a specific bicycle location for each sensor-fixture set which is incompatible with the specific bicycle location of the other sensor-fixture set. Operation method thereof.

Description

D E S C R I P T I O N

DATA COLLECTION KIT FOR ATTACHING TO A BICYCLE FOR ACQUIRING MOBILITY AND ENVIRONMENTAL DATA, OPERATION METHOD THEREOF

Technical field

[0001] The present disclosure relates to a kit of parts for attaching to a bicycle for acquiring mobility and environmental data, in particular the disclosure relates to a sensing toolkit designed to facilitate the transformation of a common bicycle into a data collection tool for the urban environment.

Background

[0002] Document US10536638BB discloses a bicycle image capturing device that reduces annoying operations for changing an operation state. The bicycle image capturing device includes a controller. The controller includes a reception unit and an electronic control unit. The reception unit is configured to obtain information related to a component of a bicycle. The bicycle component is operable in at least a first state and a second state that differs from the first state. The electronic control unit is configured to control a first image capturing unit based on the information obtained by the reception unit.

[0003] Document US2014209400 AA discloses an electromechanical control system of an electric bike integrating a smart mobile device and cloud services therewith enables a controller of the electric bike to independently monitor and control operation of an electric motor, is integrated with an external smart mobile device with a communication interface thereof, configures cycling control parameters of the controller with the externally available cycling control parameters through an user interface provided by the smart mobile device to adapt to cyclists' physical strength. Cycling information and bike information can be displayed on the smart mobile device or make them openly available through the online function of the smart mobile device for cyclists to easily record or manage related information during bike cycling.

[0004] Document WO20182558A1 relates to a method for determining a state of an electric drive of a means of a transportation, in particular a bicycle, comprising the steps of: providing sensor data from sensors of the drive, the sensor data indicating parameters of the drive if a current operating range of the drive and/or of the means of transportation corresponds to a predefined operating range; storing such sensor data as measurement sensor signals originating from sensors predefined for the predefined operating range; detecting a defect of the drive if at least one of the measurement sensor signals deviates from a predefined standard sensor signal at least by a predefined amount; and outputting a warning about the presence of the defect to a user of the means of transportation.

[0005] These facts are disclosed in order to illustrate the technical problem addressed by the present disclosure.

General Description

[0006] The present disclosure relates to a kit of parts for attaching to a bicycle for acquiring mobility and environmental data. In particular, the toolkit is composed of multiple parts, which can be attached to different locations on the bicycle and complement each other to acquire the intended data.

[0007] Bicycles equipped with sensors, processing capabilities and communications may become a valuable source of data about the collective reality of urban cycling, as well as other dimensions of the urban environment, e.g., pollution. However, the systematic and professional collection of reliable data from multiple sensors on a bicycle is a complex process. There is a very diverse set of sensors that may offer valuable data, including, but not limited to, 3D acceleration, GPS, particles, CO2, Lidar, Radar, proximity, light, sound level or video. Theses sensors may need to be placed at specific locations and may require special calibration processes. [0008] They have to be protected from exposure to environmental elements, e.g., rain and dust, and from the challenging operational context of a moving bicycle. Currently, this type of large spectrum bicycle sensing can only be accomplished with custom solutions developed by experts for each particular case. This is inefficient and is not a viable solution for the many entities that could benefit from the capability to run large scale sensing in their own cities. However, there are currently no solutions in the market that support the seamless installation of this type of sensing solution on a bicycle. There are only single devices designed to collect data from one or two sensors at one particular location on the bicycle.

[0009] Crowdsourcing is often presented as the ideal solution for urban sensing in general, and particularly for collecting mobility data. It allows data to be collected from many sources and has the potential to offer a vibrant and rich representation of reality. Still, crowdsourcing is not the best answer for all forms of sensing, particularly those involving more expensive sensors or more complex sensing procedures. It does not offer a proper context for the usage of certain types of sensors and it does not provide the type of rigor that may be needed for more professional and targeted sensing processes.

[0010] Prior work has thoroughly explored multiple alternatives for adding more complex sensors to bicycles, so that they could be used as probe bicycles for urban data. Being designed specifically for that purpose, a probe bicycle is expected to support professional data collection, with rigorous, methodic and multi-dimensional sensing that can collect many more types of data, support more expensive or more complex sensors and enable more complex data sensing procedures.

[0011] When considering the broader perspective of urban cycling data collection, probe bicycles are not necessarily an alternative to crowdsourcing methods, but they offer an important complement. Crowdsourced data collection can be very effective at estimating volume or bringing up the routes that people are actually following. This type of data can easily be collected with commonly available sensors, such as GPS or accelerometers. A probe bicycle may complement crowdsourced data by producing a broader or more accurate perspective of that reality. A probe bicycle offers the unique advantage of being equipped with many more sensors and especially of being part of a process that is optimized for data collection. This process may even consider explicit data collection actions performed by a Human agent who may, for example, be instructed to stop the bicycle at specified locations to conduct a more specific data collection procedure.

[0012] The key disadvantages of probe bicycles might be the cost of the additional technology and the need to explicitly execute the data collection itself. However, as a complement to other data collection methods, probe bicycles may not be needed in large numbers to be effective. While crowdsourced data is expected to work with as many cyclists as possible, probe bicycles might be effective even with very small numbers. A regular and well-planned data collection process might offer a very strong value to a sensing system because of their strong capability to provide a major reference to other forms of data collection.

[0013] While conceptually simple, a probe bicycle represents a complex technical challenge. There are multiple data collection needs, demanding endless combinations of sensor sets. Some sensors have major deployment requirements, meaning they have to be placed at specific positions and possibly pointing at specific directions. All this technology needs to be reliably, rigorously and safely deployed on the bicycle. In the end, it must be possible to correctly interpret the data produced by the various sensors, considering in particular their operational circumstances.

[0014] While many cycling sensing systems have been proposed before, they correspond to cases where a single entity controls all the steps of the process, from sensor selection and deployment to data collection and interpretation. However, that is not a suitable strategy for a generalized solution for the problem of how to create probe bicycles.

[0015] It is disclosed a data collection kit of parts, for attaching to a bicycle for acquiring mobility and environmental data, comprising at least two sensor-fixture sets, each sensor-fixture set comprising a sensor for acquiring external physical quantities and a fixture for coupling the sensor to the bicycle at a specific location; wherein the sensor comprises a transducer for acquiring an external physical quantity, an electronic data processor and a wireless communication means; wherein the fixture comprises a poka-yoke mounting for a specific bicycle location for each sensor-fixture set which is incompatible with the specific bicycle location of the other sensor-fixture set.

[0016] In an embodiment, each sensor-fixture set comprises an inertial measurement unit comprising an accelerometer, or a magnetometer, or an accelerometer and a magnetometer, and the electronic data processor is configured to: acquire the orientation of each sensor-fixture set using the respective inertial measurement unit; compare the acquired orientation of each sensor-fixture set against a predetermined orientation; compare the acquired orientation of each sensor-fixture set against the acquired orientation of other sensor-fixture set; triggering an alarm if any of the comparisons exceeds a predetermined threshold.

[0017] In an embodiment, the electronic data processor is configured to make said orientation comparisons in one axis, in two axes or in three axes.

[0018] In an embodiment, one of the sensor-fixture sets comprises a geolocation sensor.

[0019] In an embodiment, a transducer of said sensor-fixture sets is an inertial measurement sensor comprising an accelerometer, a magnetometer, and a gyroscope for acquiring movement data of the bicycle.

[0020] In an embodiment, a transducer of said sensor-fixture sets is a LIDAR or RADAR sensor for acquiring ranging distances, a gas concentration sensor, an air particle sensor, a light intensity sensor, a humidity sensor, an atmospheric pressure sensor, or a temperature sensor.

[0021] In an embodiment, the electronic data processor comprises a non-volatile memory for recording data and the electronic data processor is further configured for recording the acquired external physical quantities in said non-volatile memory. [0022] In an embodiment, each sensor-fixture set comprises a rechargeable power source.

[0023] In an embodiment, the wireless communication means is a Bluetooth or Wi-Fi wireless communication means.

[0024] In an embodiment, the bicycle specific location is a top of a head tube, at a front handlebar, at a seat post, a top tube of a bicycle frame, a seat tube of a bicycle frame, a down tube of a bicycle frame, a chainstay tube, or a pole-based attachment to the bicycle.

[0025] In an embodiment, the electronic data processor is further configured to use wireless communication for self-identifying and capability self-inventory to other sensor-fixture sets.

[0026] In an embodiment, the fixture and the sensor are detachable.

[0027] An embodiment comprises a plurality of charging stations arranged to receive and charge the fixture-sensor sets.

[0028] It is also disclosed a method of operation of the data collection kit according to any of the described embodiments, comprising the steps of: acquiring the orientation of each sensor-fixture set using the respective inertial measurement unit; comparing the acquired orientation of each sensor-fixture set against a predetermined orientation; comparing the acquired orientation of each sensor-fixture set against the acquired orientation of other sensor-fixture set; triggering an alarm if any of the comparisons exceeds a predetermined threshold.

Brief Description of the Drawings

[0029] The following figures provide preferred embodiments for illustrating the description and should not be seen as limiting the scope of disclosure. [0030] Figure 1 is a schematic representation of an embodiment of the system stack.

[0031] Figure 2 is a schematic representation of an embodiment of the profile view of the bicycle and hardware.

[0032] Figure 3 is a schematic representation of an embodiment of the architecture of a possible instance of a sensor-fixture set.

[0033] Figure 4 is a schematic representation of an embodiment of bicycle with multiple sensor-fixture sets.

Detailed Description

[0034] In the present disclosed was developed a Probe Bicycle Toolkit, which allows any common bicycle to be easily instrumented to operate as a probe bicycle for multipurpose professional data collection. A toolkit is not a special bicycle with sensors. It is a collection of modular sensing devices that can be easily attached to any common bicycle. Those modules can be used autonomously or in combination to extend the sensing capabilities of a probe bicycle.

[0035] When multiple modules are used, they will typically be selected and placed at predefined positions in the bicycle in ways that increase their complementarity and the efficiency of the overall sensing solution. The multiple modular devices are able to automatically coordinate with each other to optimize the whole data collection process and they can be operated as a whole from a companion interface, possibly a mobile application connected via wireless connection.

[0036] Each module is an autonomous sensing device, with its own controller and its own specific array of sensors. The modules are designed so that their deployment on the bicycle can be made correctly at predefined positions on the bicycle, even by people that are not experts on the sensing process. Each sensing device contains its own unique combination of sensors, but the deployment of multiple modular devices allows a very broad range of sensors to be used. Most of those sensors may be related with cycling activity, but many other may be addressing other types of urban sensing needs, such as pollution or noise levels. A companion interface, possibly on a mobile application may be used to configure and operate the toolkit devices.

[0037] The target market is composed of third-parties that need to collect data about the cycling reality. These might be municipalities or consulting companies doing that work on behalf of municipalities or other companies that need such information.

[0038] The following pertains to technical characteristics of each module. Each toolkit module is an autonomous device composed of its own controller board, a specific set of sensors, a rechargeable power source and a specially designed casing. Each module type is designed for a specific purpose and a particular set of possible sensors. These will determine the specific system architecture, the specific target position on the bicycle and the physical design of the respective casing.

[0039] The technical characteristics of the controller board may vary, depending on the processing requirements and communication channels of the various sensors in the module. Figure 3 represents an example of a possible instance of a toolkit module composed of a STM board, multiple sensors, a Bluetooth module and a SD card.

[0040] As illustrated in Figure 3, an architecture of a possible instance of a toolkit module according to an embodiment includes an input sensors A, e.g., temperature B; Gyroscope C; light D; rain E; GPS F and lidar G; a STM32 L; SD card H; Bluetooth I and a slave system J.

[0041] Likewise, the casing will also vary with the physical needs of the sensors in the module. The casing provides protection against external elements, but it also plays an important role in guaranteeing the right operational environment for each of the sensors in the module. In particular, the device casing should be designed to promote the physical alignment between sensors and their expected position and orientation in relation to the bicycle. The casing may also consider other sensor requirements, such as the line of sight for a Lidar or the need to allow the passing of air for humidity or particle sensors.

[0042] The following pertains to companion interface. A companion interface, possibly on a mobile application, supports the configuration of the modules and allows the data produced to be shared with the target cloud services. It may also guide the rider to follow specific routes or conduct specific operations to improve the efficiency of the data collection process or address specific data collection needs. The seamless synchronization of data from all the modules with a target cloud service is done transparently by this companion interface.

[0043] The following pertains to module control. Most control operations are expected to be performed indirectly, via the companion interface, possibly a mobile application, but in addition to the base on/off, there are two features that should be supported directly by the modules. The first is pairing control, in which the module provides the features needed to complete a safe pairing process with other modules or an external interface. The second is status information that allows the user to monitor the proper operation of each sensing module, without having to resort to an external interface.

[0044] Modules are able to run by themselves a set of coordination procedures. They have the technical capability to discover each other using short-range wireless technologies and will automatically run a leader-election algorithm to determine which module will coordinate the operation of all the other modules, so that they can be operated as if they were a single piece with multiple sensors. Most common modules will be designed to operate in standalone mode and will thus be prepared to assume the master role when used as part of a sensor mesh on the same bicycle. Some modules, however, may be designed to be operated only as slaves. This might be done to offer lower-cost modules that do not need to repeat processing capabilities and default sensors expected for any master device, e.g., GPS. It may also be done to comply with more stringent restrictions that may exist in relation to modules that need to be placed at less convenient locations, such as a wheel or a pedal. A simpler design will allow those modules to be smaller and require less power, thus making it easier to comply with the restrictions of specific deployment circumstances.

[0045] The following pertains to bicycle attachment. One of the distinguishing characteristics of the present disclosure is the way it drives sensor deployment, so that every sensor is placed in the position for which it has been conceived during the design of the various modules. This "poka-yoke" or mistake-proofing strategy aims to avoid sensor deployment errors, guaranteeing that all sensing devices are placed at the right position and held in the correct orientation, so that their data can be correctly analyzed based on that assumption.

[0046] This strong coupling between sensors and their deployment position is accomplished through the combination of multiple related mechanisms. The first is a set of bicycle fixtures for specific bicycle locations. Typical examples include the top of the head tube, at the front, or the seat post at the back. A pole-based attachment can also be created to hold a module with sensors that may need a high-ground view. Other special attachment can be conceived for even more specific positions such as the pedal or the wheel.

[0047] Figure 4 represents a possible instance of a bicycle with multiple toolkit modules attached to their specific deployment positions.

[0048] Regardless of their deployment position, all these fixtures have specific and clear mounting instructions and markers to make sure they are attached in the right position. They also have specific holders that are only meant for compatible modules. Consequently, a module can only be attached to a compatible fixture, corresponding to one of its possible deployment positions.

[0049] Modules can be designed for only a specific holder type, and consequently for a single position, or they can be designed with more than one of such holders, possibly on different sides of the casing, in which case they may be used at more than one position. Modules designed for more than one position should have some other internal mechanism to automatically detected their current usage position. If they have different holders on different sides, they will be mounted on different positions with a different 3D orientation, which can easily be detected through internal module sensors, e.g., accelerometers. This possibility adds an extra layer of flexibility without jeopardizing positional constraints. On top of that, certain modules may also have the capability to run diagnostic or calibration procedures when instructed, either by itself or in coordination with actions performed by the Human operator, under the instruction of the companion interface. [0050] The bicycle fixtures should be strongly attached to the bicycle on a long-term basis, but the modules should be easy to remove from those bicycle fixtures, allowing them to be safely stored, to be charged at a more convenient location than the bicycle itself, or to be changed to a different bicycle, possible under a different module configuration.

[0051] The following pertains to power. Each module toolkit is equipped with its own rechargeable power source and does not rely on any assumptions about the availability of electric power on the bicycle. This can be recharged through any common means, such as connecting a USB-C cable to an available USB-C socket in the module casing. This can be done when the device is in operation or not. It can be done with the device attached to the bicycle or when it is temporarily removed for charging or safe storage. The data collection algorithms may optimize power usage by implementing common power saving procedures, such as reducing or stopping GPS data collection, when the accelerometers signal that the bicycle is not moving, or stopping some sensors on a module when the same data is already being collected by similar sensors in another module.

[0052] The following pertains to connectivity. The connection between the multiple modular devices and also between the master module and the external device running the companion interface can be supported by multiple short-range wireless technologies, with those more commonly available on current smartphones, e.g., Bluetooth, being the primary option.

[0053] The following pertains to data qualification. The data produced by the toolkit modules is tagged with meta-data describing the sensing conditions, such as the position or orientation of the sensor, or any other information that may be deemed relevant for the correct interpretation of the data produced by any of the sensors. This is made possible because of the tight control over the installation of the modules, which allows those assumptions to be protected. The toolkit defines a set of reference sensing contexts, corresponding to the main bicycle location for sensor deployment. When sensor data is shared with cloud services, it is tagged with these references and the references for the respective type of sensor, so that it can be properly analyzed, even by entities without any other knowledge about the data collection process.

[0054] The following pertains to reference sensors and sensing profiles. Given the wide range of sensor possibilities and their various applications domains, the specific sensors to be included in each modular device is wide open. Framing this process under specific sensing profiles may help to align sensor selection with particular application domains. This profile structure explores the fact the various sensor possibilities are not independent between each other. Similar sensors will typically be used for similar purposes and, most of the time, they will just be alternative solutions to the same problem. By treating them as a whole, we significantly reduce the complexity of the analysis, while still maintaining the capability to make meaningful connections between sensors and their value propositions. By providing a perspective of the mapping between sensing system and key data-centric services these profiles should help companies creating probe bicycle toolkits to find the most meaningful combinations of sensors to be packaged as a single module.

[0055] The most basic sensing profile involves GPS and IMU (Inertial Measurement Unit) sensors, such as 3-axis accelerometers, 3-axis gyros and 3-axis magnetometers. These basic sensors are likely to be present across multiple modules and will often be used redundantly.

[0056] Lidar, Radar, distance, radar or other similar sensors might correspond to a slightly more advanced profile aiming at the characterization of the surrounding space of the bicycle as an indicator for traffic intensity and, very importantly, of the safety risks associated with the distance to other vehicles or potential obstacles. Given their stringent positional requirements, these sensors are likely to have their own modules.

[0057] Environmental sensors can measure a wide range of environmental characteristics, such as gas concentrations, particles in the air, light intensity, humidity level, atmospheric pressure or temperature. Some of these sensors can be particularly expensive and require specific installation settings or sensing procedures, suggesting that this may constitute a module in itself. [0058] Video and sound, coupled with image processing algorithms, can be used to automatically produce data about events of interest, with processing being done directly on the bicycle or at some edge infrastructure. Video can also be collected as ground truth data for training machine learning algorithms. Video cameras and microphone may be easily integrated with other profiles, particularly those related with the characterization of the surrounding space, with which they should share similar positional requirements.

[0059] The following pertains to evolution. The range of modules and even their specific characteristics and set of sensors can easily be extended. This should provide a natural path for the progressive alignment of the sensing modules portfolio with the real market demand and the new needs that may emerge from new market segments. The wider availability of new sensors types or their lower-cost may also create new opportunities to consider new modules and new application domains.

[0060] From a broader perspective, this type of probe bicycle is also likely to evolve towards a closer integration with data processing activities. This may be accomplished along two complementary paths. The first is the local execution of machine learning methods that can extract high-level knowledge from the sensed data. This will significantly broaden the scope and possibly the value of the data collection process. The other possible path is to optimize data collection itself by automatically generating data collection plans, possibly for multiple probe bicycles, that take into consideration dynamic information needs to define specific collection areas or particular data collection procedures.

[0061] The present disclosure offers a simple and reliable solution for any non-expert to install a broad set of sensors on a bicycle in a way that produces quality data about the urban environment in general and the cycling context in particular.

[0062] In particular, this disclosure involves the autonomous or combined used of multiple sensing pieces, designed to consider the positional requirements of various types of sensors and prepared to optimize their complementarity.

[0063] The disclosure can be used as a sensing toolkit designed to facilitate the transformation of a common bicycle (of any type) into a professional data collection tool for the urban environment. The toolkit is composed of multiple parts, which can be attached to different locations on the bicycle and complement each other to provide the intended data. The present disclosure can involve the following set of features: (1) Each piece can operate autonomously and can thus be used just by itself on a bicycle. (2) When two or more pieces are used together as part of a single bicycle, they can be linked together through a simple initialization process and they begin to act as one, in which case all the data collected by any of them will be made available as single data collection point, with the data from the various pieces properly synchronized. (3) Each piece will normally be designed to accommodate the needs of one sensor with more stringent positional requirements, for example, a Lidar piece will be designed in such a way that the Lidar itself will have access to the proper viewing angle to capture the intended scene. (4) Other sensors without relevant positional requirements will be placed opportunistically inside pieces designed for the most demanding sensors. (5) Each piece is designed to automate or facilitate any calibration needs associated with their sensors. This may involve guaranteeing particular positions or orientations of the sensors within the box and specific positional attachments of the piece to the bicycle. (6) In a typical multi-piece setting, each piece is focused on a specialized sensor and may include a combination of other common sensors. In situations in which this leads to multiple instances of the same type of sensor, the system may decide to optimise power by using only one of the sensors involved or use that redundancy to improve the quality of the respective data. (7) Toolkit usage is supported by a service that can collect the data from the devices and support the installation process. The information produced during this setup phase will then be used to help the service with the correct interpretation of the data generated by the toolkit devices.

[0064] With these features, it should become easy for any non-expert to install a set of sensors on a bicycle that is able to produce reliable data about the urban environment in general and the cycling context in particular.

[0065] A possible instantiation of the present disclosure may be composed of a microcontroller in a special designed case attached to the bike frame, as shown in Figure 2. Each case is designed around the positional needs of a sensor (or possibly multiple sensors with compatible requirements). Each case will also be equipped with a set of sensors that may be fitted in the case. Since these sensors do not need to be placed in specific positions to produce valuable data, they can be arranged in any convenient way.

[0066] As illustrated in Figure 2, this system according to an embodiment includes a rain sensor 1; a lidar sensor (2,9); an accelerometer and gyroscope 4 and a general position sensor 3, e.g., temperature.

[0067] In a possible instantiation represented in Figure 1, the system may have four different layers. A hardware layer contains every physical hardware device, such as the STM32 microcontroller and the set of sensors used. A FreeRTOS layer with device drivers for the sensors allows the system to work in real time, with parallel tasks, and maximizing the data gathering capabilities of the system. A middleware layer is responsible for data processing, e.g. converting values in the temperature sensor from volts to degrees Celsius, data acquisition that will gather the data from the FreeRTOS and communication, which allows data to be exchanged with a remote device, possibly via Bluetooth. Finally, the application layer represents the possibility for an external app, e.g. mobile app, to communicate with the device to support general configurations. All of the data gathered by the user will be stored inside a SD card connected to the microcontroller.

[0068] As illustrated in Figure 4, this system according to an embodiment includes a toolkit with general position sensors 5, e.g., temperature, air quality; a toolkit with back facing sensors 6, e.g., Lidar; a toolkit having front facing sensors, and sensors that can gather data from the bicycle handlebar movement 7, e.g., Lidar and accelerometer and a toolkit that contains sensors that need access to the bike pedals 8, e.g., cadence sensor.

[0069] The term "comprising" whenever used in this document is intended to indicate the presence of stated features, integers, steps, components, but not to preclude the presence or addition of one or more other features, integers, steps, components or groups thereof. [0070] It will be appreciated by those of ordinary skill in the art that unless otherwise indicated herein, the particular sequence of steps described is illustrative only and can be varied without departing from the disclosure. Thus, unless otherwise stated the steps described are so unordered meaning that, when possible, the steps can be performed in any convenient or desirable order.

[0071] The disclosure should not be seen in any way restricted to the embodiments described and a person with ordinary skill in the art will foresee many possibilities to modifications thereof. The above-described embodiments are combinable. The following claims further set out particular embodiments of the disclosure.

[0072] References

[1] Garmin Edge. Garmin has a few devices that allow the connection of extra sensors, but these devices have a very limited number of available sensors, mostly only cadence sensors, https://www.clevertraining.com/garmin-edge-530-gps-cycling- computer

[2] Cateye Stealth 50. GPS unit that allows the user to connect extra sensors using ANT+ protocol. https://www.cateye.com/intl/support/manual/data/doc/CC-GL50_HP_ENG_v4-l.pdf

Claims

C L A I M S Data collection kit of parts, for attaching to a bicycle for acquiring mobility and environmental data, comprising at least two sensor-fixture sets, each sensorfixture set comprising a sensor for acquiring external physical quantities and a fixture for coupling the sensor to the bicycle at a specific location; wherein the sensor comprises a transducer for acquiring an external physical quantity, an electronic data processor and a wireless communication means; wherein the fixture comprises a poka-yoke mounting for a specific bicycle location for each sensor-fixture set which is incompatible with the specific bicycle location of the other sensor-fixture set. Data collection kit, wherein each sensor-fixture set comprises an inertial measurement unit comprising an accelerometer, or a magnetometer, or an accelerometer and a magnetometer, and the electronic data processor is configured to: acquire the orientation of each sensor-fixture set using the respective inertial measurement unit; compare the acquired orientation of each sensor-fixture set against a predetermined orientation; compare the acquired orientation of each sensor-fixture set against the acquired orientation of other sensor-fixture set; triggering an alarm if any of the comparisons exceeds a predetermined threshold. Data collection kit according to the previous claim wherein the electronic data processor is configured to make said orientation comparisons in one axis, in two axes or in three axes. Data collection kit according to any of the previous claims wherein one of the sensor-fixture sets comprises a geolocation sensor. Data collection kit according to any of the previous claims wherein a transducer of said sensor-fixture sets is an inertial measurement sensor comprising an accelerometer, a magnetometer, and a gyroscope for acquiring movement data of the bicycle. Data collection kit according to any of the previous claims wherein a transducer of said sensor-fixture sets is a LIDAR or RADAR sensor for acquiring ranging distances, a gas concentration sensor, an air particle sensor, a light intensity sensor, a humidity sensor, an atmospheric pressure sensor, or a temperature sensor. Data collection kit according to any of the previous claims wherein the electronic data processor comprises a non-volatile memory for recording data and the electronic data processor is further configured for recording the acquired external physical quantities in said non-volatile memory. Data collection kit according to any of the previous claims wherein each sensorfixture set comprises a rechargeable power source. Data collection kit according to any of the previous claims wherein the wireless communication means is a Bluetooth or Wi-Fi wireless communication means. Data collection kit according to any of the previous claims wherein the bicycle specific location is a top of a head tube, at a front handlebar, at a seat post, a top tube of a bicycle frame, a seat tube of a bicycle frame, a down tube of a bicycle frame, a chainstay tube, or a pole-based attachment to the bicycle. Data collection kit according to any of the previous claims, wherein the electronic data processor is further configured to use wireless communication for self-identifying and capability self-inventory to other sensor-fixture sets. Data collection kit according to any of the previous claims, wherein the fixture and the sensor are detachable. Data collection kit according to any of the previous claims comprising a plurality of charging stations arranged to receive and charge the fixture-sensor sets. Method of operation of the data collection kit according to any of the previous claims, comprising the steps of: acquiring the orientation of each sensor-fixture set using the respective inertial measurement unit; comparing the acquired orientation of each sensor-fixture set against a predetermined orientation; comparing the acquired orientation of each sensor-fixture set against the acquired orientation of other sensor-fixture set; triggering an alarm if any of the comparisons exceeds a predetermined threshold.

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