ADAPTIVE DATA RECOGNITION AND SENSOR VERIFICATION SYSTEM FOR COMMERCIAL VEHICLES AND TRAILERS

Abstract

The invention relates to a system and method for processing CAN bus, GPS, and sensor data obtained from IoT telematics devices mounted on commercial vehicles and trailers. Within the scope of the invention, sensor verification is performed by comparing data from multiple data sources, the data recording interval is variably determined based on the verified data, and status changes related to safety signals are analyzed. Furthermore, data integrity is ensured by checking for data repetitions. The system operates within an edge-cloud hybrid architecture and includes both an on-vehicle decision module and cloud-based data processing components.

Description

ADAPTIVE DATA LOGGING AND SENSOR FOR COMMERCIAL VEHICLES AND TRAILERS VERIFICATION SYSTEM Subject of the Invention The invention is used in commercial vehicles and trailers. It relates to the field of telematics systems, specifically the CAN system on the vehicle. (Controller Area Network) bus, GPS and various sensors a system for processing and recording the obtained data It is related to the system and method. The invention provides speed by utilizing data from multiple sources. by comparing mileage, location and safety signals verification, data recording based on verified data. determining the range and related to safety signals a process that involves analyzing changes in state with a method for carrying out this flow It includes the system structure that implements the method. State of the Art Telematics used in commercial vehicles and trailers. systems, CAN bus, GPS and various on-board systems collecting and processing data from sensors It is widely used for monitoring purposes. This in the systems, vehicle location, speed information, mileage data and Parameters such as safety signals are recorded driving analysis, fleet management and safety monitoring is being carried out. In current telematics systems, data recording operations are mostly based on fixed time intervals This is being implemented. This approach involves transforming data content into information. This leads to registration without considering the value. 1 When the vehicle remains stationary for a long time, unnecessary data is generated. causing and sudden acceleration while the vehicle is in motion changes or security events corresponding to the recording interval technical issues such as inability to detect if it does not arrive This causes problems. Also, relying on a single data source... measurements based on sensor failure or connection interruption in this case, it leads to the generation of erroneous data in the system This reduces its reliability. However, security Temporary or noise-induced changes to signals, recorded even though there was no actual change in the situation This can lead to incorrect data generation. In technology, data recording methods in vehicle telematics systems, regarding the processing and verification of sensor data There are documents that discuss the improvements. As an example of the known state of the art, US8416067B2 A patent document can be provided. This document concerns vehicle telematics. data obtained from their systems for fleet management purposes a system for processing and recording It describes a device located on the vehicle. Data from vehicle sensors via telematics device that the data is collected and that this data is subject to certain conditions It is stated that it was recorded as such. In this context, in the vehicle in case the events that occurred are detected data recording and, in cases where no event occurs, specific based on the principle of recording data at time intervals A structure based on this is explained. Furthermore, it depends on the number of events. Data recording intervals can be configured accordingly. It is stated that it can be adjusted. However, the word the subject of the document is obtained from multiple data sources Sensor validation is performed by comparing the data. The lack of a mechanism to address sensor failures in terms of detection and ensuring data reliability 2 This can create limitations. Also, data recording... the range of multiple parameters obtained from the vehicle together Instead of continuous change based on evaluation, the event based on or at predetermined intervals determining that the registration decision is context-sensitive This can create certain limitations in terms of its creation. In conclusion, the document in question contains vehicle telematics data. While offering a solution for recording, the data verification mechanisms and context-dependent variable logging It has some limitations in terms of determining the range. Another example of the state of the art is US9053591B2. Patent document number [number] may be issued. This document concerns motor vehicles. the collection of operational data from vehicles and It describes a system for analysis. The document describes the data obtained from the vehicle using OBD / CAN and GPS. data such as speed and location are used together determining the parameters and analyzing this data This is explained. Furthermore, it is obtained from multiple data sources. comparing the obtained data to verify data accuracy. Approaches aimed at increasing it are expressed. With this together, the data sources in question in the document error detection based on specific conditions and by determining that one data source is faulty and then using other data a clear decision regarding the preference of its source The absence of a mechanism to determine sensor failures This can create limitations in terms of identification. In addition, the data recording range of the verified data a record decision to be used in determining lack of definition of the mechanism, data processing and recording some in terms of integrated management of processes This can create limitations. Consequently, the document in question... for obtaining vehicle data from multiple sources While offering a solution, data verification and record keeping decisions 3 limitations in terms of the integration of mechanisms It includes. Another example of the known state of the art is US10388161B2. Patent document number [number] may be issued. This document, in particular... Telematics tracking developed for trailers and semi-trailers. It describes the system. In the document, the vehicle or trailer obtained through various sensors located on it monitoring data and that data of a user It is explained that it will be presented through the interface. In this context, ABS sensors, door sensors and other security components vehicle condition is monitored using the data obtained and The aim is to identify specific events. However, the word the subject of the document is changes related to security signals signal stability or multiple verification methods a verification mechanism based on sensor correlation the absence of providing, temporary or erroneous signal changes are not real which could lead to it being considered an incident This can create limitations. Also, data recording... the decision is dynamic depending on this verification process The lack of a defined mechanism for its creation, some limitations in terms of record accuracy and data quality It can give rise to. As a result, the document in question is a trailer. by offering a solution related to telematics monitoring systems together, signal verification and data logging decision some limitations in terms of developing mechanisms It is available. These documents mention the recording of vehicle data. It appears that systems for this purpose exist. However, this data recording decisions in systems depend on the device status and context. not created, obtained from multiple data sources sensor validation was not performed by comparing the data. and status changes regarding security signals 4 there is no mechanism for verification It is understood that the data recording interval is more than one. depending on the combined evaluation of the parameters not being determined in a variable way and data repetitions The absence of a control structure to prevent this, data limitations in terms of quality and system reliability It constitutes. The disadvantages mentioned above stem from multiple data points. by comparing data obtained from the source Sensor verification is performed, and the verified data is used as the basis. by determining the data recording interval variably, changes in status regarding security signals by verifying and checking for data duplicates The current invention has been improved upon in order to remedy this. In order to overcome the disadvantages mentioned above, suddenly verification of data obtained from multiple data sources, by setting the data recording interval as a variable, Analysis of status changes related to security signals for monitoring and checking for data duplications a telematics data management system and method It has been developed. Detailed Description of the Invention The invention is used in commercial vehicles and trailers. In telematics systems, data is obtained from CAN bus, GPS and sensors. processing, verification and recording of the collected data It is related to a system and method aimed at... One purpose of the invention is to obtain data from multiple data sources. sensor verification by comparing data The goal is to ensure that it is done. Another purpose of the invention is to base its findings on verified data. The aim is to enable the definition of the data recording interval. Another objective of the invention is the situation regarding safety signals. The aim is to enable the analysis of their changes. Another purpose of the invention is to control repetitive data records. The aim is to ensure that it is done. The invention relates to devices mounted on commercial vehicles and / or trailers. It is a telematics system, in its most general form; - CAN bus enables data collection from GPS and sensors. a data collection unit, - data obtained from the aforementioned data collection unit a data processing unit configured for processing, - data obtained from multiple data sources a sensor verification that verifies by comparison mechanism, - verified by the sensor verification mechanism Using the data as input, define the data recording range. variable depending on multiple parameters a structured decision-making unit for determining, - other related changes regarding security signals Verification by evaluating it together with sensor data. a state transition detection mechanism, - data record repetition based on data content a control aimed at prevention through comparison mechanism, - recording and / or transmission of processed data a data management layer that provides, - and the user who enables the presentation of the recorded data. It includes interfaces. 6 In a configuration of the invention, sensor verification mechanism, decision-making mechanism, state transition perception mechanism and control to prevent data duplication The mechanism will work together with the data processing unit. It is structured. In one configuration of the invention, the data processing unit is a CAN bus. A CAN for parsing data obtained from it It includes a signal parsing module. In a configuration of the invention, the sensor verification mechanism data obtained from multiple data sources by analyzing data consistency comparatively It is structured for identification purposes. In a configuration of the invention, the sensor verification mechanism between data obtained from multiple data sources consistency, temporal variation and / or other sensor data taking correlation with the relevant data sources to calculate a confidence score related to It is structured. In a configuration of the invention, sensor verification The mechanism is that the CAN speed data is zero and the kilometer data is zero. In the case where it is zero, the GPS speed data is predetermined. If the value exceeds a threshold, the CAN data source will malfunction. to mark as and GPS data as speed data It is structured for use. In a conceptualization of the invention, the threshold value in question accuracy of sensor data, signal quality and / or vehicle dynamic depending on parameters related to its behavior It is updated accordingly. 7 In a conceptualization of the invention, the threshold value in question It is nominally defined as being in the range of 2-3 km / h. In the structuring of an invention, from different data sources used for the difference between the obtained speed data the tolerance range dynamically depending on vehicle speed It is being adjusted. In a structuring of an invention, the decision-making mechanism is data recording. the interval varies between 30 seconds and 15 minutes. It is structured in a way that will determine this. In the structuring of an invention, the decision-making mechanism is data. recording interval history of speed, acceleration, and route segments. dynamic depending on event intensity and time parameters to identify and critical events, exceeding the speed limit, and If anomalies are detected, the data in question will reduce the recording interval to a shorter time interval It is structured in this way. Anomalies and risks in the design of an invention. an evaluation calculated with a score on the scale of 0-1 this is done through and this score is a dynamic threshold It is compared with its value. In a structuring of an invention, the decision-making mechanism is the route. representing past event intensity based on segments using parameters to define the data recording interval It is structured accordingly. In a conceptualization of the invention, the segments in question number 500. It is defined in meter-long sections. In a conceptualization of the invention, state transition detection. mechanism, changes related to safety signals, 8 by filtering out vibration-induced noise, the signal It will filter according to its determination It is structured. In a conceptualization of the invention, state transition detection. The mechanism uses 200-500 to verify signal changes. It uses a time window in milliseconds. In a conceptualization of the invention, state transition detection. changes in the mechanism's security signals by analyzing and evaluating multiple signal relationships It is structured accordingly. In a conceptualization of the invention, state transition detection. evaluation of the mechanism based on multiple signal analysis as a result, to verify signal stability. It is structured. In a structuring of the invention, to prevent data repetition. The control mechanism for this purpose involves creating a data fingerprint. The issue is to prevent repeated registrations based on data fingerprinting. It is structured accordingly. In a conceptualization of the invention, the data fingerprint tool based on identity, time information and data content It is structured to facilitate its creation. In a structuring of the invention, to prevent data repetition. The control mechanism for this, a central recording time It includes a synchronization structure based on... In a conceptualization of the invention, the data processing unit is the tool. making local decisions and transmitting data to the cloud 9 IoT telematics device and edge decision module It includes. In a conceptualization of the invention, the data management layer includes data. It includes storage and data access structures. In a structuring of the invention, user interfaces, web and / or mobile-based for viewing data It includes interface components. The invention also applies to commercial vehicles and / or trailers. for data processing in an assembled telematics system It is a method, in its most general form; - Receiving data from CAN bus, GPS and sensors, - parsing the CAN bus data in question, - data obtained from multiple data sources comparison, - data consistency as a result of the comparison in question determining the related parameters, - using specified parameters to access data sources calculating the related confidence scores, - CAN speed data, mileage data and GPS speed data joint evaluation, - CAN speed data is zero and mileage data is zero. In this case, the GPS speed data is predetermined. If it is above the threshold value, the CAN data source incorrect determination and GPS speed data usage, - the data recording range of verified data used in determining, - data recording interval to speed, acceleration, and trajectory segments depending on past event density and time parameters calculated as follows, - critical events, speed limit violations, and anomaly situations If detected, the data recording interval will be shorter. setting a time interval - detecting changes in security signals being done, - vibration-induced noise from the changes in question processing by filtering, - changes along with multiple sensor data evaluation, - depending on signal stability verification of changes, - based on the data content of data records comparison, - Data fingerprinting, - the data in question is based on repeating records according to fingerprints. preventing, - steps for recording and / or transmitting data It includes. In one configuration of the invention, the data recording interval is 30 seconds. It is selected between 1 and 15 minutes. In a structuring of the invention, the path is segmented. splitting and past events for those segments Its density is being calculated. In a conceptualization of the invention, the segments in question number 500. It is created in sections of one meter each. In a configuration of the invention, safety signals related changes along with multiple sensor data. is being evaluated. In a conceptualization of the invention, these changes are signaled. It is verified depending on its consistency. 11 In a conceptualization of the invention, the data fingerprint tool based on identity, time information and data content is being created. In one design of the invention, data records are centralized. It is synchronized according to the time reference. This invention is designed for mounting on commercial vehicles and trailers. CAN bus and GPS data from IoT telematics devices, a multi-layered decision engine powered by machine learning It is a method and system that enables recording through it. The invention combines three key innovations. First, the vehicle's current status, past route experiences, and recording frequency by considering the environmental context together an adaptive register that learns by defining a continuous spectrum It is the engine. Secondly, multiple speeds such as CAN bus and GPS. weighted by the reliability scores of the source a system where sensors are combined and sensor failures are detected It is a sensor reliability management system. The third one is, Vibration prevention for state transitions in safety signals (debounce) and a multiple signal correlation confirming it. It is an incident detection mechanism. These three components form an edge-cloud hybrid. By working in architecture, both decision-making on the vehicle and It enables analysis to be performed in the cloud. The vast majority of current telematics systems use fixed-time. data at intervals, for example every 30 seconds. This approach takes into account the informational value of the data. It does not take. A truck left parked for 8 hours overnight. In this situation, 960 unnecessary records are created, and these records... It repeats the same information. While the vehicle is in motion. critical situations such as sudden braking or ABS activation However, these events may fall within the recording intervals and be detected. 12 It cannot be done. The problem is not the length of the interval, but the constant Some advanced systems use threshold-based registration. However, these systems handle state transitions. It fails to capture, lacks contextual information, and has fixed thresholds. It cannot be adapted to different conditions. For example, 120 on the highway. While 80 km / h is considered normal in some areas, it is dangerous within the city. It is possible. Current systems generally rely on a single method for speed. It is source-dependent. In case of CAN bus connection interruption... Speed ​​and distance data can be read as zero, and the system this is in the form of the vehicle being parked It can interpret. Also, CAN bus in stationary vehicles 1–2 It can generate erroneous signals at the km / h level, and this situation This can lead to the creation of unnecessary records. The core innovation of the invention is that it learns from past data. an adaptive register that improves decision-making over time It is the engine. The recording interval is 30 seconds instead of fixed values. The duration is determined as a variable between minutes. The vehicle speed, acceleration, density of past events along the route, and recording interval is determined by considering the time of day. The system calculates based on route segments. analyzing past events and using this information It is used across the fleet. Sensor fusion at every speed. a confidence score is assigned to the source and a three-way correlation is used. A CAN fault is being detected. State transition detection is occurring. Debounce and multiple signal correlation used to identify errors. Alarms are reduced thanks to the edge-cloud hybrid architecture. Decisions can be made on the vehicle. The vehicle's CAN bus, GPS, and sensors collect raw data. collecting and developing IoT telematics devices and edge decision modules. Through this system, both local decisions are made and data is collected. It is transmitted to the cloud. The CAN signal is parsed in the cloud. The module parses raw data to analyze parameters such as speed, ABS, and ROP. 13 It converts into parameters. Confidence-scoring sensor fusion. The module assigns a confidence score to CAN and GPS speed data, and this It combines data. CAN speed and mileage. the value is zero, but the GPS speed is greater than zero In such cases, a CAN malfunction is detected and the system GPS It is based on data. Reliable speed data is obtained. After that, the adaptive recording decision engine, critical event, speed By evaluating overshoots and anomalies, the recording interval It determines. The intelligent state transition detection module, monitoring security signals and changes This confirms it. Distributed deduplication when the registration decision is made. The module prevents repeated registrations; approved data is stored in the cloud. is written to the data layer and through user interfaces. It is presented. Within the sensor verification mechanism, the confidence score is fixed. Instead of a simple threshold-based approach; multiple signals consistency, temporal stability, and contextual validation with a hybrid method in which the criteria are evaluated together is calculated. The system calculates each data source (e.g., CAN) (for bus speed data, GPS speed data and accelerometer outputs) It generates a dynamically updated confidence score. In this process, firstly, the same information is obtained from different sources. Data on physical quantities are compared using different sources. Consistency analysis is performed between them. For example, CAN speed In a situation where the GPS speed is greater than zero, This leads to a decrease in the confidence score of the relevant data source. As the amount of inconsistency increases, the confidence score becomes linear. It is reduced by a non-existent function. In the second stage, the sensor data over time Temporal stability assessment by analyzing behavior This is being done. In this context, sudden jumps, physically 14 impossible changes or low-speed noise situations, variance and change over a sliding time window This is determined by ratio calculations and lowers the confidence score. It creates an effect. The third stage involves contextual validation. Sensor data correlates with other vehicle signals. This is being evaluated. For example, when ABS is active, the brakes... the pressure is also expected to increase or if the vehicle is moving The change in position needs to be observed. This type of If correlations are not established, the relevant data source... The confidence score is being reduced. All these components are combined into a single unit using a weighted bonding approach. These scores are converted into confidence scores and used in sensor fusion. More reliable combined data is obtained by using this method. Furthermore, the system uses historical data performance to determine this. weights and decision thresholds using machine learning methods We are constantly optimizing; so that we can determine which sensor is which It is being found to be more reliable in conditions such as noise and Error patterns are automatically adapted and the system Constantly adapting without adhering to fixed rules This approach improves the classic threshold-based approach. or much higher compared to fixed-weight systems Accurate sensor verification and fault detection are provided. GPS speed data is considered greater than zero, therefore it is constant and unique. It is not based on a threshold value, but on system connection and signaling. an adaptive system that adjusts dynamically depending on its quality It uses a threshold mechanism. In this context, low speed noise (e.g., GPS-generated false positives between 0.5–2 km / h) (motion signals) in order to eliminate a nominal lower A threshold is defined, and this value is typically 2–3. It is started within the km / h range. This threshold is not fixed and depends on the system's GPS signal accuracy (HDOP / satellite). number), position change consistency and accelerometer data by evaluating them together, dynamically adjusting the threshold value. It updates. For example, a high-precision GPS signal. where it exists and the change of location has been confirmed The threshold is being lowered; weak signal or In the presence of jitter observed in the steady state, the threshold value is being upgraded. Also, the system only displays the instantaneous speed value. not making a decision based on; a short time window within it position change and velocity continuity together. by analyzing, distinguishing real motion from sensor noise. This allows for the evaluation of GPS speed data. Based on multiple validation criteria instead of a fixed threshold, an adaptive and context-aware decision-making mechanism This is accomplished through... The threshold values ​​used in the decision-making process are not fixed, initially defined, but data quality during the study and intervals that are dynamically updated depending on the context The system is designed to ensure secure operation during initial setup. For this purpose, nominal thresholds are used, and then these values depends on sensor consistency, signal quality and vehicle behavior. It is being adapted accordingly. Speed ​​between different sources in the sensor verification process Initially, a tolerance range of approximately 5–10 km / h is required for the difference. is being used, and this range is narrowed at low speeds, It is expanded at high speeds. Speed ​​determination and For motion detection using GPS data, the nominal lower threshold is 2–3 km / h. This value relates to GPS accuracy (e.g., number of satellites and location). dynamically increased based on jitter and acceleration data is being reduced. 16 In the state transition detection (debounce) mechanism, the signal type depending on the time range, approximately 200–500 ms The window is used. Nominal value in speed detection. Values ​​above 90–100 km / h are generally considered as a reference, however This threshold depends on the road type, vehicle class, and driving context. It is being adapted. In anomaly and risk assessment, instead of a fixed threshold, depends on speed, acceleration, sensor consistency, and route data. A score calculated on the range of 0–1 is used, and this The score is compared against a dynamic threshold. The invention's decision-making mechanism consists of five basic algorithms. It consists of these algorithms. Each data packet is processed by these algorithms. They are evaluated sequentially. Within the scope of Algorithm 1. Sensor fusion and CAN fault detection are performed. CAN bus and Dynamic confidence scores are assigned to GPS data, and these scores... It is constantly being updated. CAN speed and mileage values. in cases where the speed is zero and the GPS speed is greater than zero A connection drop is detected and the system retrieves the GPS data. It uses GPS location changes in low-speed situations. By evaluating the acceleration data together, the true signal can be determined. It is determined whether the source is movement or noise. Status of security signals within Algorithm 2. The transitions are being verified. Signal changes are directly accepted. not being done, remaining stable for a certain period of time is expected. Also, with other relevant sensor data. A correlation check is performed. No correlation is found. In this case, the event is considered invalid. Adaptive recording decisions are made within the scope of Algorithm 3. First, critical events are controlled, then speed. The overshoot is being verified, and finally, speed, acceleration, and risk score. 17 The recording interval is determined by evaluating them together. This The interval varies between 30 seconds and 15 minutes. Route learning and risk mapping within Algorithm 4. The route is being created in 500-meter segments. dividing and analyzing event intensity for each segment This analysis is performed. As a result of this analysis, a risk score is calculated and This score is updated over time. The information obtained is used for the fleet. It is shared nationwide. Preventing duplicate registrations within Algorithm 5. This is provided. A data fingerprint is created for each record. and compared with existing records. The same data Records containing this content are blocked. Additionally, each record... The reason for registration information is stored here. In the overall flow, each data packet sequentially processes sensor fusion and status. from the steps of verification of passage, registration decision and re-check It passes through and is then recorded in the database. Critical route risk map in case of incident detection It is being updated. The invention is designed for commercial vehicle and trailer fleets in their current structure. While the same approach applies to buses and public transportation, transport vehicles, construction and mining vehicles, agricultural machinery, maritime systems, railway applications and cold chain It can also be applied in different fields such as logistics. Furthermore, from an architectural perspective, the entire decision engine is located on the vehicle. A full edge version can be created by embedding it into the device. The entire system will operate on the vehicle. It is configurable. 18 One advantage of the system described in the invention is that the sensor data... The goal is to reduce the generation of erroneous data through verification. Another advantage of the system described in the invention is data recording. By defining the range as variable, it is unnecessary The goal is to reduce data records. Another advantage of the system described in the invention is that it eliminates data repetition. Data integrity is protected through monitoring. One advantage of the invented method is that it uses multiple data points. by comparing data obtained from the source Its purpose is to ensure the creation of a reliable dataset. Another advantage of the method described in the invention is data recording. the range, together with the data obtained Its purpose is to ensure that it is determined based on its evaluation. Another advantage of the method described in the invention is safety. Analysis of changes in the status of signals This helps reduce false alarm detections. 19

Claims

1. A device mounted on commercial vehicles and / or trailers. It is a telematics system; its feature is: - CAN bus enables data collection from GPS and sensors. a data collection unit, - data obtained from the aforementioned data collection unit a data processing unit configured for processing, - data obtained from multiple data sources a sensor verification that verifies by comparison mechanism, - verified by the sensor verification mechanism Using the data as input, define the data recording range. variable depending on multiple parameters a structured decision to determine mechanism, - other related changes regarding security signals Verification by evaluating it together with sensor data. a state transition detection mechanism, - data record repetition based on data content a control aimed at prevention through comparison mechanism, - recording and / or transmission of processed data a data management layer that provides, - and the user who enables the presentation of the recorded data. It includes interfaces.

2. It is a telematics system according to claim 1, and its characteristic is; sensor. verification mechanism, decision-making mechanism, situation transition detection mechanism and data repetitions data processing unit of the preventive control mechanism It is configured to work together with...

3. According to claim 1, it is a telematics system whose characteristic is data. the processing unit receives data via the CAN bus a CAN signal parsing module It includes.

4. It is a telematics system according to claim 1, and its characteristic is; sensor. verification mechanism obtains data from multiple sources by comparatively analyzing the collected data structured to determine consistency It is the fact that.

5. A telematics system according to claim 4, whose characteristic is; sensor the verification mechanism from multiple data sources consistency between the obtained data, temporal variation and / or correlation with other sensor data is taken into consideration by establishing trust in the data sources in question. It is structured for calculating the score.

6. A telematics system according to claim 4 or 5, whose characteristic is; sensor verification mechanism, CAN speed data zero and GPS speed when the kilometer data is zero the data above a predetermined threshold value If this happens, the CAN data source is incorrect. using GPS data as marker and speed data It is structured accordingly.

7. According to claim 6, it is a telematics system, the characteristic of which is; speech The subject is the accuracy of the sensor data, the signal, and the threshold value. parameters relating to quality and / or vehicle behavior It is updated dynamically depending on the situation.

8. According to claim 7, it is a telematics system, the characteristic of which is; speech The threshold value in question is nominally in the range of 2-3 km / h. It is defined. 21 9. It is a telematics system according to claim 5, and its characteristic feature is that it is different speed data between data sources The tolerance range used for the difference depends on the vehicle speed. It is the dynamic adjustment of the system.

10. It is a telematics system according to claim 1, and its characteristic is; the decision-making mechanism's data recording interval is 30 to 15 seconds. to determine as a variable between minutes It is structured.

11. It is a telematics system according to claim 10, and its characteristic is; the decision-making mechanism, data recording interval, speed, acceleration, historical event density and time for route segments dynamically determined based on its parameters and critical events, speed limit violations and anomaly situations if detected, the relevant data recording interval to reduce it to a shorter time interval It is structured.

12. It is a telematics system according to claim 11, and its characteristic is; anomaly and risk assessment in the 0-1 range This is done based on a calculated score and this It is a comparison of the score with a dynamic threshold value.

13. It is a telematics system according to claim 11, and its characteristic is; decision-making mechanism history based on route segments data using parameters representing event intensity Structured for defining the recording interval. It is the fact that.

14. It is a telematics system according to claim 13, and its characteristic is; the segments in question in 500-meter sections It is defined. 22 15. It is a telematics system according to Claim 1, and its characteristic is; state transition detection mechanism, security changes in signals, vibration-related by filtering out noise and adjusting signal stability. It is configured to perform filtering.

16. It is a telematics system according to claim 15, and its characteristic is; the state transition detection mechanism, signal changes A time interval of 200-500 ms for verification purposes. It is the use of the window.

17. It is a telematics system according to Claim 1, and its characteristic is; state transition detection mechanism to safety signals by analyzing changes in the relationship through multiple signal relationships It is structured for evaluation purposes.

18. It is a telematics system according to claim 17, and its characteristic is; state transition detection mechanism, multiple signals signal as a result of evaluation based on analysis structured to verify its commitment It is the fact that.

19. It is a telematics system according to Claim 1, and its characteristic is; control mechanism to prevent data duplication by creating a data fingerprint, to that data fingerprint according to prevent re-registrations It is structured.

20. It is a telematics system according to claim 19, and its characteristic is; Data includes fingerprint, vehicle identification, time information, and data. to be created based on its content It is structured. 23 21. It is a telematics system according to claim 19, and its characteristic is; a control mechanism to prevent data duplication, a central recording time-based synchronization structure It includes.

22. It is a telematics system according to Claim 1, and its characteristic is; the data processing unit, making local decisions on the vehicle and IoT telematics devices for transmitting data to the cloud. It includes an edge decision module.

23. It is a telematics system according to Claim 1, and its characteristic is; data management layer, data storage and data access It includes structures.

24. It is a telematics system according to Claim 1, and its characteristic is; user interfaces, data display web and / or mobile-based interface components for It includes.

25. Mounted on commercial vehicles and / or trailers / sedans a method for processing data in a telematics system Its characteristic is; - Receiving data from CAN bus, GPS and sensors, - parsing the CAN bus data in question, - data obtained from multiple data sources comparison, - data consistency as a result of the comparison in question determining the related parameters, - using specified parameters to access data sources calculating the related confidence scores, - CAN speed data, mileage data and GPS speed data joint evaluation, - CAN speed data is zero and mileage data is zero. In this case, the GPS speed data is predetermined. 24 If it exceeds the threshold value, the CAN data source will be affected. incorrect determination and GPS speed data usage, - the data recording range of verified data used in determining, - data recording interval to speed, acceleration, and trajectory segments depending on past event density and time parameters calculated as follows, - critical events, speed limit violations, and anomaly situations If detected, the data recording interval will be shorter. setting a time interval - detecting changes in security signals being done, - vibration-induced noise from the changes in question processing by filtering, - changes along with multiple sensor data evaluation, - depending on signal stability verification of changes, - based on the data content of data records comparison, - Data fingerprinting, - the data in question is based on repeating records according to fingerprints. preventing, - steps for recording and / or transmitting data It includes.

26. It is a method according to claim 25, and its characteristic is data recording. The interval is selected between 30 seconds and 15 minutes.

27. It is a method according to claim 25, and its characteristic is that the route segmentation and the history for those segments It is the calculation of event intensity.

28. It is a method according to claim 27, and its characteristic is that; segments in 500-meter sections is the creation of.

29. It is a method according to claim 25, and its characteristic is security. Changes in signals with multiple sensor data It is a joint assessment.

30. It is a method according to claim 29, and its characteristic is that; changes depending on signal stability It is a verification.

31. It is a method according to claim 25, and its characteristic is; data fingerprinting. the track is based on vehicle identity, time information and data content. It includes the step of creating it.

32. It is a method according to claim 25, and its characteristic is; data synchronize the records according to a central time reference. It is done. 26