Technical field

The present disclosure relates to a sensor device for analyzing and determining vehicle operating mode, a method for analyzing and determining vehicle operating mode using sensor device and a system for analyzing and determining vehicle operating mode. More specifically, the disclosure relates to a sensor device for analyzing and determining vehicle operating mode, a method for analyzing and determining vehicle operating mode using sensor device and a system for analyzing and determining vehicle operating mode as determined in the introductory parts of claim 1, claim IB and claim 20.

Background art

Prior art systems tend to use a "3-wire installation" and connect a wire directly to the ignition feed in order to detect operation mode of a vehicle.

A problem with the solutions of the prior art is that a 3-wire installation records when the 'power is on', not when the engine is running, which again may lead to over-estimation and false positives.

A further problem is, in general, that a 3-wire-installation is more complex, time-consuming, expensive to install and will require an authorized and dedicated installer.

Other systems has been seen to operate directly connected to the OBD (On-board diagnostics) interface of the vehicle.

The problems with such OBD connected systems can be shortly listed as they: lack reliability in that they must wait until the OBD system is active before being of use, the car manufacturer is reluctant to allow non-original equipment to connect, and further a connection to such interface is not reliable mechanically as the connection easily can be tampered, knocked out or stolen. A more bird view approach to problems with running a fleet of vehicles are to avoid inefficiently and unsafely operation which leads to higher fuel and service costs, is less environmentally friendly, is involved in more accidents and costs more to insure.

There is thus a need for improved system that demands less complex installation, but which provides accurate vehicle operation mode.

Summary

It is an object of the present disclosure to mitigate, alleviate or eliminate one or more of the above-identified deficiencies and disadvantages in the prior art and solve at least the above mentioned problem.

According to a first aspect there is provided a sensor device for analyzing and determining vehicle operating mode of a vehicle it is installed in, the sensor device comprising: one or more vehicle power source voltage sensors, and a processor unit, wherein the processor unit comprise analyzing module for determining, based on at least sensor data from the one or more power source voltage sensors, a vehicle operating mode to be one of at least: parked, idling, moving.

The advantage of such a system is that the installation is self-sustained as far as it only need to connect to a power line reflecting the voltage level of the vehicles power source, battery. The device itself may comprise movement detectors/sensors adding further data to the sensed power level data for the analyzing process.

According to a further embodiment of the first aspect, the senor device further comprises: one or more movement detection modules, and the analyzing module of the processor unit comprise features for determining a vehicle movement mode to be one of at least: rapid acceleration, harsh braking, sharp turn.

According to a further embodiment of the first aspect, the senor device further comprises: one or more accelerometers.

Accelerometer(s) may add directional information to movement data, G-forces and vibration data, further enabling increased accuracy to the analyzing process. According to a further embodiment of the first aspect, the one or more movement detection modules are comprised of one or more of: GPS, odometer, tripmeter, movement sensor, and accelerometer.

According to a further embodiment of the first aspect, the processor unit further comprises: a communication module for communicating one or more of: sensor data, movement data, vehicle operating mode, and analyzed data to a remote computer device.

According to a further embodiment of the first aspect, the processor unit is programmed to analyze movement of the vehicle.

According to a further embodiment of the first aspect, the processor unit is programmed to analyze g-forces imposed to the vehicle by movement.

According to a further embodiment of the first aspect, the processor unit further comprises an alert module for generating warning related to one or more of: rapid acceleration, harsh braking, sharp turn.

According to a further embodiment of the first aspect, the processor unit further comprises a training module for initializing the sensor device and define customized parameters defined by a vehicle during an initializing routine, the customized parameters being at least one or more of: power source voltage level at idling operation mode, power source voltage level at parked operation mode, power source voltage level at moving operation mode.

According to a further embodiment of the first aspect, the sensor device further comprise a monitoring and scoreboard program installed on a remote computer device, wherein the remote computer device is in communicating connection to the communication module of the sensor device.

According to a further embodiment of the first aspect, the monitoring and scoreboard program calculates a score based on a weighted sum of one or more of the sensor data, movement data, vehicle operating mode, and analyzed data.

According to a further embodiment of the first aspect, the remote computer device comprise a graphical display unit, and the monitoring and scoreboard program is programmed to display the score. According to a further embodiment of the first aspect, the remote computer device communicates one or more of: sensor data, movement data, vehicle operating mode, and analyzed data to a further remote computer device, the further remote computer being one of mesh connected computer, LAN/WAN connected computer, or cloud based computer.

According to a second aspect there is provided a method for analyzing and determining vehicle operating mode using sensor device according to the first aspect, the method comprise of the following steps: - arranging the sensor device in a vehicle to be analyzed, connecting power source voltage sensors to power lines, and - activating an initialization routine in the sensor device for initializing the sensor device and define customized parameters defined by a vehicle during an initializing routine, the customized parameters being at least one or more of: power source voltage level at idling operation mode, power source voltage level at parked operation mode, power source voltage level at moving operation mode.

The device is therefore custom initialized with a unique reference model to each vehicle during installation process, and variances in make and model do not have any impact on the efficiency of the sensor device. Some vehicle models are however not selectable, and the present invention may not use the voltage level features on all models/makes.

According to a further embodiment of the second aspect, the method comprises the steps wherein the sensor device: - receiving readings from the power source voltage sensors, - analyzing the data, and upon detection of vehicle operating mode - transmit the vehicle operating mode to a remote computer device and optionally to a further remote computer device, the further remote computer being one of mesh connected computer, LAN/WAN connected computer, or cloud based computer.

According to a further embodiment of the second aspect, the method comprises the steps wherein the sensor device: - receiving data from the movement detection modules, - analyzing the data, and upon detection of vehicle movement mode - transmitting the vehicle movement mode to a remote computer device and optionally to a further remote computer device, the further remote computer being one of mesh connected computer, LAN/WAN connected computer, or cloud based computer. According to a further embodiment of the second aspect, a vehicle operating mode is determined as one of at least: parked, idling, and moving, and a vehicle movement mode is determined as one of at least: rapid acceleration, harsh braking, and sharp turn.

According to a further embodiment of the second aspect, the method comprises the steps - calculating a score based on a weighted sum of one or more of the sensor data, movement data, vehicle operating mode, and analyzed data - the monitoring and scoreboard program calculates a score based on a weighted sum of one or more of the sensor data, movement data, vehicle operating mode, and analyzed data.

According to a further embodiment of the second aspect, the method comprises the step: - displaying the score on a graphical display unit of a remote computer device.

According to a further embodiment of the second aspect, the method comprises the step: - communicating the one or more of: sensor data, movement data, vehicle operating mode, and analyzed data to a further remote computer device, the further remote computer being one of mesh connected computer, LAN/WAN connected computer, or cloud based computer.

According to a third aspect there is provided a system for analyzing and determining vehicle operating mode, the system comprising: the sensor device according to the first aspect, the sensors being installed in corresponding vehicles, a remote computer device being in communication with the sensor device over a wireless communication line, and a computer implemented analyzing program.

According to a further embodiment of the third aspect, the system further the system comprises one of mesh connected computer, LAN/WAN connected computer, or cloud based computer being in communication with the remote computer device over a wireless communication line, wherein the one of mesh connected computer, LAN/WAN connected computer, or cloud based computer provides one or more of the following services for the computer device and the sensor device: - uploading sensor device data, - analyzing sensor device data, - analyzing sensor device data using a trained Al-system based on neural network models, - providing result for display on remote computer device, - communicating results to remote computer device, and - communicating results to one of user's WEB or company's WEB. Effects and features of the second and third aspects are to a large extent analogous to those described above in connection with the first aspect. Embodiments mentioned in relation to the first aspect are largely compatible with the second and third aspects.

The present disclosure will become apparent from the detailed description given below. The detailed description and specific examples disclose preferred embodiments of the disclosure by way of illustration only. Those skilled in the art understand from guidance in the detailed description that changes and modifications may be made within the scope of the disclosure.

Hence, it is to be understood that the herein disclosed disclosure is not limited to the particular component parts of the device described or steps of the methods described since such device and method may vary. It is also to be understood that the terminology used herein is for purpose of describing particular embodiments only, and is not intended to be limiting. It should be noted that, as used in the specification and the appended claim, the articles "a", "an", "the", and "said" are intended to mean that there are one or more of the elements unless the context explicitly dictates otherwise. Thus, for example, reference to "a unit" or "the unit" may include several devices, and the like. Furthermore, the words "comprising", "including", "containing" and similar wordings does not exclude other elements or steps.

Terminology

The term "Idling" is to be interpreted as referring to running a vehicle's engine when the vehicle is not in motion.

The term remote computer is to be interpreted as referring to any of but not limited to: smartphone, vehicle infotainment system, laptop, desktop computer, Tablet computer, all either wired or wirelessly connected to the sensor device.

Brief descriptions of the drawings

The above objects, as well as additional objects, features and advantages of the present disclosure, will be more fully appreciated by reference to the following illustrative and non-limiting detailed description of example embodiments of the present disclosure, when taken in conjunction with the accompanying drawings. Figure 1A shows the Update Main state flow diagram Figure IB shows the State handler flow diagram

Figure 2AA shows the "I" portion of the Update Main state flow diagram

Figure 2AB shows the "II" portion of the Update Main state flow diagram Figure 2AC shows the "III" portion of the Update Main state flow diagram

Figure 2AD shows the "IV" portion of the Update Main state flow diagram

Figure 2AE shows the "V" portion of the Update Main state flow diagram

Figure 2BA shows the "I" portion of the State handler flow diagram

Figure 2BB shows the "II" portion of the State handler flow diagram Figure 3 shows the Add Accelerometer Sample flow diagram

Figure 4 shows the Check Accelerometer State flow diagram

Figure 5 shows the Main Voltage Measurement System flow diagram

Figure 6 shows the Calculate Voltage State flow diagram

Figure 7 shows the Driving Event flow diagram Figure 8 shows the Position flow diagram

Figure 9 shows graphs for deciding vehicle state based on voltage and difference ratio

Figure 10A and 10B shows flow diagram for the reference voltage measurement system

Figure 12A-D show GUI Dashboard examples

Figure 13A-B show GUI Dashboard or App examples

Figure 14A-F show GUI App examples Figure 15 show GUI map fleet overview examples Figure 15 show GUI map fleet overview examples

Figure 16 show an example of a sample example embodiment of sensor device

Figure 17 shows a system example of plurality of sensor devices in a network environment

Detailed description

The present disclosure will now be described with reference to the accompanying drawings, in which preferred example embodiments of the disclosure are shown. The disclosure may, however, be embodied in other forms and should not be construed as limited to the herein disclosed embodiments. The disclosed embodiments are provided to fully convey the scope of the disclosure to the skilled person.

The state diagrams in the figures illustrates examples of various features and actions performed by the processor unit in the sensor device. Software and/or HW modules in the processing unit is provided to execute some or all of the said features and actions.

The first aspect of this disclosure shows a sensor device for analyzing and determining vehicle operating mode, the sensor device comprising: one or more vehicle power source voltage sensors, and a processor unit, wherein the processor unit comprise an analyzing module for detecting, based on at least sensor data from the one or more power source voltage sensors, a vehicle operating mode to be one of at least: parked, idling, moving.

When the analyzing module is discussed in the following examples it is comprised inthe sensor device, where it would be most efficient. It should however be understood that the analyzing part of the present invention can be implemented in any of the computing resources mentioned in the system description of the present invention. As for example if Artificial Intelligence modules were to be used on fleet data, it is naturally that the analyzing modules partially or completely is provided for example in the cloud/network computing resources. In other embodiments it would be sensible to transfer raw sensor data directly to remote computer and/or further remote computer for analyzing there. In yet other embodiments some of the analyzing features are performed in the sensor device, and other in the remote computer and/or further remote computer The power voltage sensor device may operate according to state diagrams in figure 5 and 6. In figure 5 it is exemplified how the time interval for measurement is defined. The interval is set according to which state the vehicle is in at any time, and may be customized for different implementations of the present invention. In the example given for the state handler in figure 2BA and 2BB it can be seen that the time interval is lOs/ls/ls/ls for corresponding vehicle states parked/driving/idling/disturbance. Time intervals may change over time and may be set by a remote control procedure communicating with the sensor device.

In figure 9 there is exemplified how the voltage state may be defined. Voltage measurements from the battery of the car can be used to detect if the car's engine is on or off, since the measured voltage levels may be different when the engine is on or off.

A voltage control algorithm may be provided for vehicles with usable voltage levels.

The voltage levels may vary from vehicle to vehicle, and the algorithm may be used for providing a dynamic reference model of the voltage sensor data, and the algorithm may further comprise a verification feature for deciding if the measurements are valid and usable.

The building of the reference model associated with the vehicle may involve some or all of the following: the voltage will be read at certain intervals while the vehicle is driving or parked. In order to make good models, the state of the vehicle must be controlled before the measurement can be put in the reference data. Data from sensor units such as accelerometer and GPS may be used to verify the state. The reference voltages may be divided in one set each for driving and parked, and the minimum, maximum, and average voltages for each state are stored. When a new voltage measurement is added, it's checked if it's a new maximum or minimum value, and the average is recalculated.

Each time a new voltage is added to the reference set, a quality control may be executed on the reference data, to ensure that the data is valid and usable.

This quality control will ensure that there are different voltage levels for driving and parked states, and it may be assumed that the voltage levels for a driving vehicle will be higher than those of parked vehicle. It is checked that the maximum and minimum voltage readings from parked state are respectively lower than the maximum and minimum voltage readings from driving state. Then it is checked that the voltage averages of the two states are sufficiently different. If the reference data is good, voltage measurements may be used to decide if the vehicle is driving or parked. If reference voltages from the two states don't overlap, the measured voltage is categorized as driving if the voltage is higher than the minimum of the driving reference data set. It will be categorized as parked if it is below the maximum of the park voltage set. If the measured voltage is between the minimum drive and maximum park voltage, or there is overlap between the voltage measurement reference sets, the ratio between the difference of the measured voltage and the park and driving average voltage values is used to decide what state the measured voltage most likely indicates. This ratio may look like the graph illustrated in figure 9. The average driving voltage is in the example shown at the zero-point = 14.2 V, while the average parked voltage is at the maximum ratio = 12 V. If the ratio is above a certain upper limit ratio it indicates parked, if the ratio is below the lower limit ratio it indicates driving, and if it is between the two limits the state is uncertain (either between the averages, or very high or low).

Using one or more of a well-built reference model, a trained algorithm, or even a trained neural network, it may be possible to decide not only if the vehicle is running or at a standstill, but also if the vehicle is nonmoving and idling.

In figure 10 A and figure 10 B flow diagrams for the reference voltage measurement system is exemplified. Measurements are made more often during trip, for example every 5 minutes, and less often when parked, for example once an hour. Speed and accelerometer may be checked in order to avoid false measurements.

In a further embodiment of the first aspect of this disclosure shows a sensor device for analyzing and determining vehicle operating mode, the sensor device comprising: one or more movement detection modules, and the analyzing module of the processor unit comprise features for detecting a vehicle movement mode to be one of at least: rapid acceleration, harsh braking, sharp turn.

In a further embodiment of the first aspect of this disclosure shows a sensor device for analyzing and determining vehicle operating mode, the senor device further comprises: one or more accelerometers.

The use of the movement detection module and even more an accelerometer may be used in combination with the one or more vehicle power source voltage sensors, in order to simplify the analysis of the sensor data and to make an even higher quality assessment of the vehicle operation mode, and specifically to detect if the vehicle is idling.

Flow diagrams in figure 2AA to 2AE explains how one embodiment of using the accelerometer in combination with the power voltage data to decide whether the vehicle operation mode is in one of driving, idling or parked.

The detection process of how to detect an operation mode being idle can in one embodiment of the present invention be defined as follows:

Firstly, the sensor device listen to the accelerometer for a limited period, for example 4-8 seconds recording accelerometer data. The accelerometer data is then ran through an FFT analysis module comprised in the sensor device as shown in figure 3 and figure 4, to provide the vibrational spectrum. In the vibrational spectrum clear regular frequencies, max. 3, which do not move represents vehicle idling. If so, we set "accelerometer state" to "idle". This state can also indicate whether the vehicle is at rest, for example by measuring noise only, or out and about defined by a lot of random vibration frequencies.

Secondly, the sensor device check the voltage system as discussed above, and evaluates if the voltage indicates that the motor is "on" which in most vehicles is detected by the charging voltage while driving. A separate system monitors the voltage over time and verifies whether it is possible use the voltage alone to indicate whether the motor is "on". This can be determined by detecting presence of charging voltage while the vehicle is moving. Alternatively can this be verified by analysing GPS positions and accelerometer data.

A unique feature of the present invention is that very little memory is spent to determine whether the voltage system is "valid" or not. This is achieved by deriving an "exponential moving average", with a starting point of " voltage references prediction" (guesswork), and allowing the value to adjust by learning over time. By developing these according to Evolutionary algorithms is performed to optimimize parameters of the system.

Thirdly, a further verification check if movement has been detected on the GPS positions may be performed, to verify that the vehicle is actually idling. If the GPS indicates steady motion, it is likely the vehicle is driving, for example rather slowly, instead of idling.

The results of these 3 checks above are then used in a large state machine, which assesses whether the vehicle is idling or not as exemplified in figures 1A, IB, 2AA-2AE, and 2BA-2BB. The one or more movement detection modules of present invention is not limited to GPS and accelerometers, but may be of any movement detecting instrument, and at least selected form a list comprising: GPS, odometer, tripmeter, movement sensor, and accelerometer.

The processor unit of present invention may further comprises: a communication module for communicating one or more of: sensor data, movement data, vehicle operating mode, and analyzed data to a remote computer device. It is also within the inventive concept to provide for a controlling maintenance module in one of the remote computers, cloud based computers, back-end computer or the like. The controlling maintenance module may communicate date comprising one or more of: new SW, Firmware updates to the sensor device, parameters for timing, sensor levels, voltage levels and the like, and further: communication protocols, alert settings and the like.

In even further embodiments of the invention the processor unit is programmed to analyze movement of the vehicle, and for example g-forces imposed to the vehicle by movement. This may be used for analysis of driving patterns, and for detecting driving patterns such as for example rapid acceleration, harsh braking, sharp turn. The sensor device and connected remote computer devices and SW programs may be provided with features for alerting the driver or other entities, such as a supervisor, of the driving pattern of one or more of vehicles.

A further feature of the present invention is to provide for a monitoring and scoreboard program which may calculate a score based on a weighted sum of one or more of the sensor data, movement data, vehicle operating mode, and analyzed data. And the weighted sum may be presented on a remote computer device which comprise a graphical display unit.

The remote computer device may communicate one or more of: sensor data, movement data, vehicle operating mode, and analyzed data to a further remote computer device, the further remote computer being one of mesh connected computer, LAN/WAN connected computer, cloud based computer, or other network connected computer resource, any of which may be connected via wired, wireless or a combination of the two connection.

The second aspect of this disclosure shows a method for analyzing and determining vehicle operating mode using sensor device according to the first aspect, the method comprise the following steps: - arranging the sensor device in a vehicle to be analyzed, connecting power source voltage sensors to power lines, and - activating an initialization routine in the sensor device for initializing the sensor device and define customized parameters defined by a vehicle during an initializing routine, the customized parameters being at least one or more of: power source voltage level at idling operation mode, power source voltage level at parked operation mode, power source voltage level at moving operation mode.

The method may further comprise the steps wherein the sensor device: - receiving readings from the power source voltage sensors, - analyzing the data, and upon detection of vehicle operating mode - transmit the vehicle operating mode to a remote computer device and optionally to a further remote computer device, the further remote computer being one of mesh connected computer, LAN/WAN connected computer, or cloud based computer.

The method may further comprise the steps wherein the sensor device: - receiving data from the movement detection modules, - analyzing the data, and upon detection of vehicle movement mode - transmitting the vehicle movement mode to a remote computer device and optionally to a further remote computer device, the further remote computer being one of mesh connected computer, LAN/WAN connected computer, or cloud based computer.

The method may further comprise that a vehicle operating mode is determined as one of at least: parked, idling, and moving, and a vehicle movement mode is determined as one of at least: rapid acceleration, harsh braking, and sharp turn.

The method may further comprises the steps - calculating a score based on a weighted sum of one or more of the sensor data, movement data, vehicle operating mode, and analyzed data - the monitoring and scoreboard program calculates a score based on a weighted sum of one or more of the sensor data, movement data, vehicle operating mode, and analyzed data.

The method may further comprises the step: - displaying the score on a graphical display unit of a remote computer device.

The method may further comprises the step: - communicating the one or more of: sensor data, movement data, vehicle operating mode, and analyzed data to a further remote computer device, the further remote computer being one of mesh connected computer, LAN/WAN connected computer, or cloud based computer.

The third aspect of this disclosure shows a system for analyzing and determining vehicle operating mode, the system comprising: the first aspect sensor device according to the first aspect - a remote computer device being in communication with the sensor device over a wireless communication line, and - a computer implemented analyzing program.

The system may further comprises one of mesh connected computer, LAN/WAN connected computer, or cloud based computer being in communication with the remote computer device over a wireless communication line, wherein the one of mesh connected computer, LAN/WAN connected computer, or cloud based computer provides one or more of the following services for the computer device and the sensor device: - uploading sensor device data, - analyzing sensor device data, - analyzing sensor device data using a trained Al- system based on neural network models, - providing result for display on remote computer device, - communicating results to remote computer device, and - communicating results to one of user's WEB or company's WEB.

In one embodiment as exemplified in figure 17, wherein the three vehicles represents standalone vehicle implementation as well as fleet implementations communicating directly to a cloud based computer resource or via a more local remote computer system.

Now a discussion of the GUI of a variation of types of remote computers, and services provided by the further remote computer resources. For simplicity the further remote computer resources is called the cloud based computer, and the remote computer system is called the computer. All variations of the two are still valid as discussed above.

Figure 12A-D, 13A-B, 14A-F, and 15 are examples of how information provided by the sensor device of the present invention may be provided. It should be understood that the design of and content of the GUI, dashboard and warnings may well be provided in GUI figures, menus, and the likes having different design that the ones shown here without moving away from the inventive concept of present invention.

The dashboard as presented in figure 12A and figure 12B illustrates a company overview wherein a score is calculated based on measured sensor data compared with an idle score, which may include values measured as an average representing vehicles operation in a larger entity. A score in this dashboard of 100 is best. Like a percentage of a perfect result. In figure 12A a company overview is presented with further information on Trend score and Comparison score. In one aspect of the invention the score may be calculated on 1 week, one month, or one year basis, or any other time span. The trend and comparison graphs may include any of the sensor outcomes or any of parameters based on the sensor data.

In figure 12B it is seen that the sensor data collected is braked down to individual drivers behavior. The outcome of the dashboard program may be to present the driver or his superiors with a tool that correctly pictures the drivers habits and skills, and may be used to assess or improve each individual driver.

The dashboard may be provided as a fleet/company tool for use by fleet/company to monitor and assess the drivers reporting through the system, or as a standalone toolset for use by individuals.

Figure 12 C shows an alert example of a message provided for presentation through a GUI to a driver for making the driver conscious of that the driving pattern is reflected on the cost of operating his/her vehicle, and in this particular alert the cost of idling is presented.

In figure 12D an example of an idling report for a company is presented on a GUI screenshot. Typically such information is presented after being collected by the cloud computer resource after firstly the sensor device in each vehicle has collected and preprocessed/analyzed the data before transmitting the data to a remote computer and/or to the cloud computing resource. The remote computer may present a selection of data and analyzed and processed data directly to the driver through a GUI of the remote computer resource. For example can this be given trough the infotainment system of the vehicle itself. As seen in figure 17, the data transfer may be performed directly between sensor device and remote computer, directly between sensor device and cloud computing resource, between sensor devices without any middle computer resource, or between a sensor device via a computer resource to a cloud computing resource. The communication may be based on a simple one way communication protocol, wherein sensor data and analyzed sensor data is sent from the sensor device to a computer resource of the system, or it may support 2-way communication for transfer of sensor data one way, and for example configuration and/or warning/messaging data the other. In figure 13A and figure 13B, it is shown two examples of alerts/messages sent to a driver and presented on a remote computing device , here typically a smart phone running an app for maintaining the features of the sensor device. The first is an update of how the company's total driving score is at present time compared with the rest of the registered drivers in UK. optimal result from such a message is that each company driver focuses on his/hers driving habits to improve the company's performance.

The second example illustrates how a competition internally in the company may be used to visualize and reward the best performers of the company.

Figure 14A to 14F is examples of how a smartphone app may be used to relay driving skill and statistics to individual users of the system. The score values may be measured and compared with company averages, company policies/targets, nationwide average, individually set targets or other.

In figure 14A, the GUI has received analyzed sensor data from for example an accelerometer sensor, and decided that the performance is not up to standard, for example the driver is a bit heavy on the gas pedal, and accelerates to rapid at occasions. An individual acceleration score is calculated to be 51.

In figure 14B, the opposite is recognized, the driver is not accelerating/decelerating to hard, and receives a score of 100.

In figure 14C, the accelerometer, or other sensor or a combination of sensors, has detected that the driver tends to take corners to the left a bit to sharply, and receives a score of 58 on left cornering. This may not be serious as the driver may drive on a road with many roundabouts with counterclockwise driving direction, but if driving in a residential area the warnings may have higher relevance.

In figure 14D the GUI is provided with a user selectable menu, giving instant feedback to the driver on an individual level and on a company/group comparison level. In the example it can be seen that the driver scores excellent on idling and breaking, but not so good on acceleration left and right turns. The total score is estimated to be 76, which rates the driver to be no. 15 of 59 in the company.

I figure 14E it can be seen that depending on score value a variation of messages may be sent to the driver via the smart phone app. When a score number of cornering left sharply of as low as 18 has been "earned" by the driver a sharp correctional message is sent to remind the driver on how to remediate the wrongly performed driving habits.

In figure 14F it is shown how the sensor device smart phone app is integrated in traditional driving log toolsets.

Figure 15 is an example of how the fleet senor devices may be reported through a map tool interface. Here typically giving a supervisor an instant picture of where and in what state each vehicle is within a selected map section.

A very simple installation procedure may be executed for installing the sensor device, as pictured in one embodiment in figure 16, in a vehicle, being exemplified below:

1

Clean dirt with the cleansing wipe. Use paper towel to dry off. A wet surface will ruin the adhesive sticker.

2

Before mounting, make sure the unit and the cables will not interfere with any hot surfaces or moving parts. Please do not mount under metal. The device requires clear view of the sky.

3

Use a multimeter to identify the three needed connections:

• Connect the red wire to the positive permanent power source

• Connect the black wire to the negative power source or ground (earth)

• If you have bought Vendors Usage Log please connect the yellow wire to a power source which is only active when the equipment, machinery or vehicle ignition is on. This input can be a digital signal or 0-30V analog voltage

• The fuse is located on the red (positive) wire. Never replace the fuse with other values than indicated on the product label

4 If the unit is receiving power, the LED light will blink red for 1 minute, and then blink blue for up to 9 minutes. When start up is complete, the LED will stop blinking.

5

Note the serial number of the box MUSxxxxxx, and other necessary information to add to the GUI user interface. Return the details to your administrator.

The sensor device and supporting toolset and systems gives a user or group if users insights into the drivers' driving data and helps to improve how the drivers use for example their company's vehicles on a daily basis. A fleet that runs efficiently and safely has lower fuel and service costs, is more environmentally friendly, is involved in fewer accidents and costs less to insure.

Some of the likely improvements to fleet performance when using some or all of the sensor device and system according to present invention comprise:

Reduced fuel consumption, service costs and insurance premium.

Reduced risk of accidents by providing the necessary monitoring, training and motivation

Get a safer and more environmentally friendly fleet Save money by optimizing how the fleet is used See exactly where an event happened on a digital map

The sensor device and supporting toolset and systems compiles a summary of all key information about the drivers' driving. This allows creation of visual overviews that can compare the drivers' performance and put in the necessary actions and training where needed. This can improve the fleet's total utilization, reduce the number of accidents and improve the company's reputation.

The sensor device and supporting toolset and systems ensures that each vehicle in the fleet becomes more efficient. By reducing cases of less good driving and wild driving, fuel consumption will be lower and service costs will decrease. The fleet becomes more environmentally friendly, safer, cheaper and can potentially stay on the roads for a longer time. Event key information is logged and displayed in for example a Google integrated digital map. For example, if there has been a situation where hard braking has been recorded, it may be possible to see exactly when and where this happened.

The person skilled in the art realizes that the present disclosure is not limited to the preferred embodiments described above. The person skilled in the art further realizes that modifications and variations are possible within the scope of the appended claims. Additionally, variations to the disclosed embodiments can be understood and effected by the skilled person in practicing the claimed disclosure, from a study of the drawings, the disclosure, and the appended claims.