Multi-dimensional data monitoring and low-power management system and method

Abstract

The invention discloses a multi-dimensional data monitoring and low-power-consumption management system and a multi-dimensional data monitoring and low-power-consumption management method. The method comprises the following steps: classifying a plurality of sensors into an energy side sensor, an environment and equipment side sensor and a driving side sensor according to function dimensions; an intelligent control center is connected to the sensors through a unified bus structure, and data are read in a centralized mode to form a multi-dimensional data sensing matrix; and according to the current running state of the vehicle, the sensor in the unnecessary working state is automatically dormant. According to the invention, the sensors are subjected to classified integrated management and dynamic power consumption control is carried out according to the operation state, so that the problems of complex wiring, high power consumption and data isolation in the existing scheme are solved, and integrated monitoring and low-power consumption management of the vehicle state are realized.

Description

Technical Field

[0001] This application relates to the field of intelligent vehicle system technology, and more specifically, to a multi-dimensional data monitoring and low-power management system and method. Background Technology

[0002] As a mobile vehicle that combines the attributes of a "house" and a "vehicle," a motorhome integrates a large number of functional systems necessary for living and driving, such as energy systems (batteries, inverters), water systems (fresh water tanks, grey water tanks, water pumps), environmental systems (heaters, temperature and humidity monitoring), and driving safety systems (tire pressure monitoring). To effectively monitor these systems, modern motorhomes are typically equipped with a large number and variety of sensors.

[0003] In existing technologies, these sensors mostly employ independent and decentralized monitoring schemes. For example, battery power monitors, coolant level gauges, and tire pressure monitors are typically three separate systems, each with its own display screen or indicator light, connected via dedicated wiring. This decentralized architecture presents several technical challenges. Complex and redundant wiring increases the difficulty and cost of designing, installing, and maintaining the vehicle's electrical system. The independent operation of each monitoring unit results in high overall system standby power consumption, significantly shortening the range of motorhomes that rely on limited power for off-grid living. Furthermore, the sensor data forms "information silos," preventing effective linkage and collaborative processing, thus limiting the overall intelligence level of the motorhome. For instance, the system cannot automatically adjust sensor monitoring methods based on the vehicle's driving status, leading to frequent false alarms due to drastic fluctuations in coolant level data caused by liquid sloshing during driving, severely impacting the user experience.

[0004] Therefore, how to efficiently integrate the wide variety of sensors in a motorhome, simplify the system structure, achieve deep low power consumption, and improve the accuracy and intelligence of data monitoring is a technical problem that urgently needs to be solved in this field. Summary of the Invention

[0005] This invention provides a multi-dimensional data monitoring and low-power management system and method, which solves the technical problems of existing vehicle monitoring systems, such as complex wiring, high power consumption, isolated data, and susceptibility to accuracy interference.

[0006] To achieve the above objectives, the present invention provides a multi-dimensional data monitoring and low-power management system, including multiple sensors, a unified bus structure, and an intelligent control center.

[0007] The multiple sensors are classified into energy-side sensors, environment and equipment-side sensors, and vehicle-side sensors according to preset functional dimensions.

[0008] The intelligent control center is connected to the multiple sensors through the unified bus structure and is configured to centrally read the data from all sensors, forming a unified multi-dimensional data sensing matrix on its display interface for centralized display and control.

[0009] The intelligent control center is also configured to automatically put sensors in non-essential working states into hibernation based on the vehicle's current operating status.

[0010] Preferably, the energy-side sensor includes at least one of a battery power sensor and a photovoltaic current sensor; the environment and equipment-side sensor includes at least one of a water tank level sensor, an ambient temperature and humidity sensor, and a gas alarm; and the vehicle-side sensor includes at least one of a tire pressure monitoring sensor and a global positioning system module.

[0011] Preferably, the intelligent control hub adopts a dual-core heterogeneous hardware architecture, including: a microcontroller unit; and a system-on-a-chip unit; the microcontroller unit is responsible for polling the underlying data of the multiple sensors; the system-on-a-chip unit is responsible for display interface interaction and complex logic processing; the power supply of the system-on-a-chip unit is controlled by the microcontroller unit, and it is in a power-off or sleep state by default when there is no interactive operation.

[0012] Preferably, the microcontroller unit is configured to: after acquiring the current sensor value of any sensor, perform a differential comparison between the current sensor value and the corresponding historical sensor value that was previously uploaded to the system-on-a-chip unit; and only when the absolute value of the difference between the current sensor value and the historical sensor value exceeds a preset update threshold, wake up the system-on-a-chip unit and upload the current sensor value to update the multidimensional data sensing matrix.

[0013] Preferably, the system further includes an acceleration sensor and an ignition signal detection unit; the intelligent control center presets at least three state models, including a driving model, a parking life model, and a long-term storage model; the intelligent control center is configured to determine the current state model of the vehicle based on the data from the acceleration sensor and the signal from the ignition signal detection unit.

[0014] Preferably, the intelligent control center is further configured to: configure different sampling periods for different types of sensors according to the determined current state model; and, when it is determined that the vehicle is in the driving model, extend the sampling period of the environmental and equipment side sensors, while shortening the sampling period of the driving side sensors.

[0015] Preferably, the environmental and equipment-side sensors include a water tank level sensor; when the intelligent control center determines that the vehicle is currently in the driving mode, it specifically sets the sampling period of the water tank level sensor to a first preset period value. The first preset period value Greater than the second preset period value set for the water tank level sensor when the vehicle is in the parking life model. .

[0016] This invention also provides a multi-dimensional data monitoring and low-power management method, comprising the following steps:

[0017] The classification step involves pre-classifying multiple sensors in the vehicle according to their functional dimensions. The classification includes at least energy-side sensors, environmental and equipment-side sensors, and driving-side sensors.

[0018] The matrix construction step involves connecting the multiple sensors to the intelligent control center through a unified bus structure. The intelligent control center centrally reads the data from all sensors and forms a unified multi-dimensional data sensing matrix on its display interface for centralized display and control.

[0019] The low-power processing step involves the intelligent control center automatically putting sensors that are not in a necessary operating state into sleep mode based on the vehicle's current operating status.

[0020] Preferably, the matrix construction step and the low-power processing step are specifically executed through a dual-core heterogeneous hardware architecture including a microcontroller unit and a system-on-a-chip unit, and the method further includes:

[0021] The microcontroller unit performs low-level data polling on the multiple sensors to obtain the current sensor values;

[0022] Compare the current sensor value with the pre-stored historical sensor values ​​using a differential comparison.

[0023] And only when the absolute value of the difference exceeds a preset update threshold, the microcontroller unit wakes up the system-on-a-chip unit, which is in a sleep or power-off state by default, and uploads the current sensor value to it.

[0024] Preferably, the low-power processing step further includes:

[0025] Based on the data from the vehicle's acceleration sensor and the ignition signal, the current state model of the vehicle is determined from the preset driving model, parking life model, and long-term storage model.

[0026] Based on the determined state model, the sampling period of different types of sensors is dynamically adjusted;

[0027] Furthermore, when the driving model is determined to be as described, the sampling period of the water tank level sensor is extended.

[0028] The beneficial effects of this invention are as follows:

[0029] 1. By classifying scattered sensors according to functional dimensions and constructing a multi-dimensional data sensing matrix based on a unified bus, the previously isolated monitoring units are managed by a unified intelligent control center, simplifying the electrical wiring inside the vehicle and reducing installation complexity and maintenance costs.

[0030] 2. By adopting a dual-core heterogeneous architecture and combining differential wake-up logic with scene-driven dynamic sampling methods, the system can perform silent monitoring by only the ultra-low-power microcontroller unit when there is no interaction or significant data change. The high-performance system-on-a-chip unit is in a power-off or deep sleep state, thereby reducing the overall standby power consumption of the system to less than one-tenth of that of traditional solutions, significantly extending the vehicle's off-grid range.

[0031] 3. By linking the accelerometer to determine the vehicle's driving status and dynamically extending the sampling period of sensors such as the water tank level that are susceptible to motion interference, coupled with an abnormal interruption mechanism, invalid data jumps caused by physical factors such as liquid sloshing are effectively shielded, avoiding false alarms and unnecessary power consumption. Furthermore, while ensuring the timeliness of emergency response to water leakage, the reliability of the data and the user experience are improved.

[0032] 4. The centralized data matrix provides a solid data foundation for achieving more advanced intelligent management, making intelligent linkage across systems and devices possible. Attached Figure Description

[0033] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0034] Figure 1 This is a structural block diagram of a multi-dimensional data monitoring and low-power management system provided in an embodiment of the present invention.

[0035] Figure 2 This is a flowchart of a multi-dimensional data monitoring and low-power management method provided in an embodiment of the present invention.

[0036] Figure 3 This is a schematic diagram of the hardware structure of the dual-core heterogeneous intelligent control center provided in an embodiment of the present invention. Detailed Implementation

[0037] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0038] To make the objectives, technical solutions, and advantages of this invention clearer, the invention will be described in further detail below.

[0039] Please see Figure 1 This embodiment provides a multi-dimensional data monitoring and low-power management system. Logically, the system can be divided into a control layer 100, an energy and distribution layer 200, and an execution and load layer 300. Its core is the intelligent control hub 101 located in the control layer 100. This intelligent control hub 101 connects and manages multiple sensors and actuators distributed throughout the vehicle via a unified bus structure.

[0040] In this embodiment, the multiple sensors are pre-classified logically according to their functional dimensions to construct a well-structured and easily managed data system. Specifically, the classification includes at least:

[0041] 1. Energy-side sensors: These are specifically designed to monitor the status of a vehicle's core energy system. Examples include battery charge sensors for monitoring remaining battery charge, real-time voltage, and current, and photovoltaic current sensors for monitoring the power output of solar panels.

[0042] 2. Environmental and Equipment-Side Sensors: These are used to monitor environmental parameters and the status of living quarters within the vehicle. Examples include water tank level sensors to monitor the levels of fresh and grey water tanks, ambient temperature and humidity sensors to monitor temperature and humidity inside and outside the vehicle, and gas alarms for safety monitoring.

[0043] 3. Driving-side sensors: These are used to monitor parameters directly related to vehicle driving safety. Examples include tire pressure monitoring sensors and a GPS module for acquiring vehicle location and speed information.

[0044] The intelligent control hub 101, acting as a centralized data gateway and human-machine interface, can be specifically a smart touchscreen embedded in the vehicle's living compartment cabinet panel in this embodiment. It connects to all the aforementioned sensors and lower-level energy hardware and device actuators via a unified bus structure (which can be a combination of various communication protocols such as CAN bus, RS485 bus, and SPI bus). In this unified bus structure, sensors of different categories (such as battery level monitors, water tank level gauges, and tire pressure monitors) no longer require dedicated end-to-end physical lines from the sensors to their respective independent displays. Sensors using different communication protocols are mounted on their corresponding communication trunk lines, which, in addition to differential signal lines, integrate a unified common power supply line and a common ground line. DC power is provided by the intelligent control hub, and terminating resistors with matching resistance values ​​are connected in parallel at the ends of each bus topology to eliminate signal reflection. These different communication trunk lines are physically aggregated and bundled into a single integrated main trunk bundle. As a multi-bus gateway, the intelligent control hub logically integrates data from different hardware trunks into a unified data stream through underlying protocol parsing. This design completely solves the wiring complexity and redundancy problems caused by independent connections of each monitoring unit in existing technologies from a topological and physical perspective. The intelligent control hub 101 centrally reads data from all sensors and displays and controls it in a unified manner in a graphical and matrix-like way on its main touch screen interface, forming an intuitive "multi-dimensional data sensing matrix." For example, the left side of the screen can display a circular progress bar for battery power and precise voltage and current values; the middle area of ​​the screen displays the liquid levels of the fresh water tank and grey water tank in blocks; and the top status bar displays the indoor and outdoor temperatures in real time.

[0045] Specifically, to achieve the aforementioned unified bus structure, the specific hardware pins and bus topology of the microcontroller unit 301 are defined as follows: The microcontroller unit 301 allocates independent hardware interfaces corresponding to different physical trunks through pin multiplexing. For example, PA2 and PA3 pins are multiplexed as RS485 bus interfaces to connect environmental and device-side sensors; PB8 and PB9 pins are multiplexed as CAN bus interfaces to connect energy-side and vehicle-side sensors.

[0046] In terms of bus topology, a multi-bus composite topology is adopted. The CAN bus and RS485 bus are physically independent, but their physical cables are laid out with independently shielded twisted-pair structures to suppress electromagnetic coupling and crosstalk between differential signals. They are aggregated and wrapped into a comprehensive trunk harness by an outer insulating sleeve for whole-vehicle wiring.

[0047] In the communication protocol control process, the microcontroller unit 301, acting as the core gateway of the intelligent control hub, internally runs a protocol parsing algorithm. When receiving RS485 messages or CAN bus data frames, the microcontroller unit 301 first performs low-level protocol parsing to extract valid sensor data. Then, it uniformly converts and encapsulates this heterogeneous data into a standard internal serial data frame format recognizable by the system-on-a-chip unit 302. Through this technique of independent aggregation of physical trunk lines combined with low-level gateway protocol conversion, unified communication and management of multiple sensors are achieved at the logical level.

[0048] To achieve significant low power consumption management, one of the core innovations of this invention lies in the hardware architecture of the intelligent control hub 101 and the intelligent algorithm it runs on.

[0049] Please see Figure 3 This illustrates the preferred hardware architecture of the intelligent control hub 101 in this embodiment—a dual-core heterogeneous hardware architecture. This architecture comprises two core processing units: an ultra-low-power microcontroller unit 301 and a high-performance system-on-a-chip unit 302. Specifically:

[0050] Microcontroller Unit 301: A model known for its low power consumption can be selected. As the system's "outpost," it is directly powered by the vehicle's battery via a low-dropout linear regulator, ensuring continuous operation and keeping its resident power consumption below 50mW. The core responsibility of Microcontroller Unit 301 is to perform low-level, periodic data polling and protocol parsing for all connected sensors.

[0051] System-on-a-chip (SoC) unit 302: A model with strong multimedia processing capabilities and computing power can be selected, typically running a complex operating system. SoC unit 302 is responsible for driving the high-definition touch display 303, handling the rendering of the display interface, responding to touch events, and executing complex upper-layer application logic.

[0052] Furthermore, the power supply circuit of the system-on-a-chip unit 302 is not directly connected to the main power supply, but is connected in series with a PMOS switch 304 controlled by the general-purpose input / output pins of the microcontroller unit 301. When there is no system interaction and all sensor data does not change significantly, the microcontroller unit 301 controls the PMOS switch 304 to be in the off state by default, thereby completely powering down the system-on-a-chip unit 302 and its peripheral circuits or putting them into a deep sleep state at the nanoampere level. This is the basis for achieving significantly low power consumption in the system. The microcontroller unit 301 and the system-on-a-chip unit 302 communicate via a serial interface and have dedicated signal lines, such as wake-up signal lines and heartbeat signal lines.

[0053] Based on this dual-core heterogeneous architecture, the system runs a "state machine polling algorithm based on differential thresholds" to minimize the number of wake-ups of the system-on-a-chip unit 302 while ensuring the real-time performance of critical data. The core logic of this algorithm is differential wake-up. The microcontroller unit 301 acquires the current sensor value V from any sensor through its analog-to-digital converter interface or communication interface. curr Afterwards, it will not immediately wake up the system-on-a-chip unit 302. Instead, it will access the corresponding historical sensor value V stored in its internal memory, which was successfully uploaded to the system-on-a-chip unit 302 last time. last And perform a difference comparison operation. In a preferred embodiment, the above calculation logic is implemented through the following formula:

[0054] ΔV = |V curr - V last |

[0055] Where ΔV represents the absolute value of the difference between the current sensor value and the historical sensor value.

[0056] Subsequently, the microcontroller unit 301 compares the calculated difference ΔV with a preset update threshold V for the sensor. th Comparison is required only when ΔV > V. thOnly when certain conditions are met does it indicate a meaningful change in sensor data. At this point, the microcontroller unit 301 will turn on the PMOS switch 304 by pulling the wake-up signal line high, waking up the system-on-a-chip unit 302. It will then upload a batch of updated data cached in its internal circular buffer to the system-on-a-chip unit 302 via the SPI bus to refresh the multi-dimensional data sensing matrix on the display interface. If the difference is within the threshold range, the microcontroller unit 301 only updates the data locally, and the system-on-a-chip unit 302 remains in sleep mode. The threshold Vth can be set according to the physical meaning of different sensors and the dynamic state of the vehicle. For example, for battery voltage, the threshold can be set as a dynamic proportional value, while for in-vehicle temperature, it can be set to 1°C and its normal fluctuation range. Specifically, for energy-side sensors: the threshold for the battery charge sensor can be dynamically set in segments based on the nonlinear characteristics of the battery discharge curve (e.g., based on a 2% change in state of charge (SOC) as the threshold), to overcome the deficiency that static voltage thresholds cannot reflect actual power consumption; the threshold for the photovoltaic current sensor can be set to 0.5A, to shield against minor disturbances in natural light caused by cloud cover. For environmental and equipment-side sensors: the threshold for in-vehicle temperature can be set to 1℃, and the threshold for ambient humidity can be set to 5%, based on matching the reasonable perception accuracy of human body temperature and humidity; the threshold for the water tank level sensor can be set to 5%, based on filtering out reading jumps caused by tiny ripples on the water surface when the vehicle is stationary; the concentration threshold for the gas alarm can be set to 1% of the lower explosive limit (LEL), based on filtering the sensor's background noise while ensuring high-sensitivity safety warnings. For driving-side sensors: the pressure threshold for the tire pressure monitoring sensor can be dynamically adjusted upwards using a temperature compensation model combined with tire temperature data (e.g., the threshold is increased to 0.4 Bar during driving), based on preventing the natural pressure rise caused by normal tire warming during driving from causing the microcontroller unit to continuously and frequently wake up the system-on-a-chip unit; the position threshold for the GPS module can be set to 50 meters, based on filtering out GPS signal drift interference when the vehicle is statically parked. The above settings ensure that the system's wake-up and update mechanism is only triggered when there is a significant change in sensor data with actual physical meaning.

[0057] To further enhance the system's intelligence and data accuracy, this system also introduces a scenario-driven dynamic management method. The system additionally integrates a three-axis accelerometer and an ignition signal detection unit for detecting the vehicle's ignition status. The intelligent control center 101 (specifically executed by the microcontroller unit 301) determines the vehicle's current macroscopic operating state based on these two input sources. The system presets at least three state models:

[0058] Driving model: When the ignition signal voltage V is detected acc > 12V, or the Z-axis vibration frequency f measured by an accelerometer.vib When the frequency reaches >5Hz and continues for 10 seconds, the system determines that the vehicle has entered driving mode.

[0059] Parking life model: When the ignition signal voltage V is detected acc = 0V and vibration frequency f vib When the frequency is less than 1Hz and remains below 1Hz for 5 minutes, the system determines that the vehicle has entered a parking / camping state.

[0060] Long-term storage mode: When the vehicle remains in the parked life mode for more than 24 hours without any interactive operation, the system enters the long-term storage mode with the lowest power consumption, at which time more unnecessary sensors will be put into hibernation.

[0061] After determining the current state model, the microcontroller unit 301 executes the dynamic frequency conversion sampling method, that is, it configures dynamically changing sampling periods T for different types and characteristics of sensors. poll .For example:

[0062] When the vehicle is determined to be in a driving mode, the system will shorten the sampling period of the driving-side sensors, which is of paramount importance for driving safety. For example, the tire pressure monitoring period will be shortened from 1 minute when the vehicle is parked to 1 second, so as to achieve near real-time warning.

[0063] Meanwhile, in the driving model, the real-time requirements for data from certain environmental and equipment sensors are reduced, and they are more susceptible to motion interference. A typical example is the water tank level sensor. To shield against invalid data jumps caused by violent sloshing of the liquid inside the water tank due to road bumps, the system will change the sampling period of the water tank level sensor from the second preset period value under the parking life model. (For example, 5 seconds) significantly extended to the first preset cycle value. (For example, 60 seconds). Simultaneously, the microcontroller unit incorporates unidirectional trend detection logic based on sliding window filtering at the underlying level. Once a continuous abnormal drop in liquid level exceeding the normal sloshing range is detected, a leak safety interruption alarm can be immediately triggered. This mechanism, which uses accelerometer data linkage to adjust the sampling frequency and supplements it with abnormal interruption, physically shields against invalid data interference. This not only avoids frequent false alarms on the display interface but also reduces unnecessary power waste caused by differential wake-up logic triggered by drastic data fluctuations. Furthermore, while ensuring the timeliness of emergency responses such as leaks, it achieves dual optimization of data accuracy and system power consumption.

[0064] Please see Figure 2 This invention also provides a multi-dimensional data monitoring and low-power management method corresponding to the above-described system. This method can be executed by the intelligent control center 101 of the above-described system, and specifically includes the following steps:

[0065] Step S201: Classification Step. During system initialization or configuration, multiple sensors within the vehicle are pre-classified according to their functional dimensions, including at least energy-side sensors, environmental and equipment-side sensors, and driving-side sensors. Step S202: Matrix Construction Step. After system startup, the microcontroller unit 301 within the intelligent control hub polls all sensors at the low-level data level through a unified bus structure, centrally reading the data. When the system-on-a-chip unit 302 is operational, it receives data from the microcontroller unit 301 and forms a unified multi-dimensional data sensing matrix on its display interface for centralized display and control.

[0066] Step S203: Low-power processing step. This step S203 runs continuously as a background process. The intelligent control center 101 automatically and intelligently executes a series of energy-saving and data optimization processes based on the vehicle's current operating status.

[0067] Specifically, the low-power processing step S203 includes a variety of cooperative sub-methods described in the foregoing embodiments.

[0068] It utilizes a dual-core heterogeneous hardware architecture to perform differential wake-up. Specifically, the microcontroller unit 301 polls for data, obtains the current sensor value, and compares it differentially with historical values. Only when the absolute value of the difference exceeds a preset threshold will the system-on-a-chip unit 302, which is in default sleep mode, be woken up and the data is uploaded.

[0069] Secondly, this step also includes scenario judgment and dynamic frequency adjustment. Specifically, based on data from the onboard acceleration sensor and ignition signal, the vehicle's current state is determined within preset driving, parking, and long-term storage models. Then, based on the determined state model, the sampling period of different types of sensors is dynamically adjusted. Specifically, when the vehicle is judged to be in driving mode, the sampling period of the coolant level sensor is extended to actively shield against data interference caused by liquid sloshing.

[0070] In summary, this application, by classifying and matrixing vehicle sensors and adopting a dual-core heterogeneous architecture, combined with wake-up logic based on differential thresholds and a dynamic sampling frequency adjustment method based on vehicle state models, not only achieves centralized monitoring of multi-dimensional vehicle data and simplifies system wiring, but more importantly, it significantly reduces system standby power consumption while ensuring the real-time performance of key data, and improves data monitoring accuracy in specific scenarios through intelligent algorithms, thus providing a more reliable, energy-efficient, and intelligent vehicle user experience.

[0071] It should be noted that the various embodiments in this specification are described in a progressive manner, with each embodiment focusing on the differences from other embodiments. Similar or identical parts between embodiments can be referred to interchangeably. It will be apparent to those skilled in the art that the present invention is not limited to the details of the above exemplary embodiments, and that the invention can be implemented in other specific forms without departing from its spirit or essential characteristics. Therefore, the embodiments should be considered exemplary and non-limiting in all respects. The scope of the invention is defined by the appended claims rather than the foregoing description, and all changes falling within the meaning and scope of the equivalents of the claims are intended to be included within the present invention.

Claims

1. A multi-dimensional data monitoring and low-power management system, comprising multiple sensors, a unified bus structure, and an intelligent control hub; characterized in that, The multiple sensors are classified into energy-side sensors, environment and equipment-side sensors, and vehicle-side sensors according to preset functional dimensions. The intelligent control center is connected to the multiple sensors through the unified bus structure and is configured to centrally read the data from all sensors, forming a unified multi-dimensional data sensing matrix on its display interface for centralized display and control. The intelligent control center is also configured to automatically put sensors in non-essential working states into hibernation based on the vehicle's current operating status.

2. The system according to claim 1, characterized in that, The energy-side sensor includes at least one of a battery power sensor and a photovoltaic current sensor; the environment and equipment-side sensor includes at least one of a water tank level sensor, an ambient temperature and humidity sensor, and a gas alarm; the vehicle-side sensor includes at least one of a tire pressure monitoring sensor and a global positioning system module.

3. The system according to claim 1, characterized in that, The intelligent control hub adopts a dual-core heterogeneous hardware architecture, including: a microcontroller unit; and a system-on-a-chip unit; the microcontroller unit is responsible for polling the underlying data of the multiple sensors; the system-on-a-chip unit is responsible for display interface interaction and complex logic processing; the power supply of the system-on-a-chip unit is controlled by the microcontroller unit, and it is in a power-off or sleep state by default when there is no interactive operation.

4. The system according to claim 3, characterized in that, The microcontroller unit is configured to: after acquiring the current sensor value of any sensor, perform a differential comparison between the current sensor value and the corresponding historical sensor value that was previously uploaded to the system-on-a-chip unit; and only when the absolute value of the difference between the current sensor value and the historical sensor value exceeds a preset update threshold, wake up the system-on-a-chip unit and upload the current sensor value to update the multidimensional data sensing matrix.

5. The system according to claim 1, characterized in that, The system also includes an acceleration sensor and an ignition signal detection unit; the intelligent control center presets at least three state models, including a driving model, a parking life model, and a long-term storage model; the intelligent control center is configured to determine the current state model of the vehicle based on the data from the acceleration sensor and the signal from the ignition signal detection unit.

6. The system according to claim 5, characterized in that, The intelligent control center is also configured to: configure different sampling periods for different types of sensors according to the determined current state model; and, when it is determined that the vehicle is in the driving model, extend the sampling period of the environmental and equipment side sensors, while shortening the sampling period of the driving side sensors.

7. The system according to claim 6, characterized in that, The environmental and equipment-side sensors include a water tank level sensor; when the intelligent control center determines that the vehicle is currently in the driving mode, it specifically sets the sampling period of the water tank level sensor to a first preset period value. The first preset period value Greater than the second preset period value set for the water tank level sensor when the vehicle is in the parking life model. .

8. A multi-dimensional data monitoring and low-power management method, characterized in that, Includes the following steps: Classification steps: The multiple sensors in the vehicle are pre-classified according to their functions. The classification includes at least energy-side sensing, environmental and equipment-side sensing, and driving-side sensing. Matrix construction steps: The multiple sensors are connected to the intelligent control center through a unified bus structure. The intelligent control center centrally reads the data from all sensors and forms a unified multi-dimensional data sensing matrix on its display interface for centralized display and control. Low-power processing steps: The intelligent control center automatically puts sensors that are in a non-essential working state into sleep mode based on the current operating status of the vehicle.

9. The method according to claim 8, characterized in that, The matrix construction step and the low-power processing step are specifically executed through a dual-core heterogeneous hardware architecture, which includes a microcontroller unit and a system-on-a-chip unit. The microcontroller unit is responsible for polling the underlying data of the multiple sensors, and the system-on-a-chip unit is responsible for display interface interaction and complex logic processing. The method further includes: The underlying data of the multiple sensors is polled to obtain the current sensor values; Compare the current sensor value with the pre-stored historical sensor values ​​using a differential comparison. And only when the absolute value of the difference exceeds a preset update threshold, the system-on-a-chip unit, which is in a sleep or power-off state by default, is woken up and the current sensor value is uploaded to it.

10. The method according to claim 8, characterized in that, The low-power processing steps also include: Based on the data from the vehicle's acceleration sensor and the ignition signal, the current state model of the vehicle is determined from the preset driving model, parking life model, and long-term storage model. Based on the determined state model, the sampling period of different types of sensors is dynamically adjusted; Furthermore, when the driving model is determined to be as described, the sampling period of the water tank level sensor is extended.

Images