Pickup truck roller shutter cover automatic control system based on RF communication and intelligent induction

Abstract

The invention relates to a pickup truck roller shutter cover automatic control system based on RF communication and intelligent induction. The pickup truck roller shutter cover automatic control system is characterized in that environmental conditions around a pickup truck roller shutter cover are monitored in real time by arranging sensors; according to the environmental conditions, the current in-vehicle comfort level is analyzed; and according to the current in-vehicle comfort level, the roller shutter cover of the pickup truck is controlled to be opened and closed by controlling starting and pausing of the roller shutter cover. The problems that in the prior art, wiring is complex, an intelligent sensing function is lacked, changes of environmental conditions cannot be automatically sensed, the state of the roller shutter cover cannot be automatically adjusted according to actual conditions, and the control effect and precision of the roller shutter cover are poor are solved. In addition, the relation between the environment condition and the in-vehicle comfort level is quantified through a deep learning model, the accuracy of control over the roller shutter cover is improved, and the roller shutter cover is opened and closed according to the surrounding environment condition so as to meet the requirement for the in-vehicle comfort level.

Description

Technical Field

[0001] The invention belongs to the technical field of rolling shutter cover control, and relates to an automatic control system for a rolling shutter cover of a pickup truck based on RF communication and intelligent sensing. Background Art

[0002] Traditional pickup truck tonneau covers are usually operated manually, which has some inconveniences during use. For example, when moving goods, the tonneau cover needs to be frequently opened and closed manually, which is not only time-consuming and labor-intensive, but may also affect work efficiency. In addition, in severe weather conditions, such as rainy or windy days, manually operating the tonneau cover will also cause inconvenience and safety hazards to users. In order to solve these problems, some electric rolling shutter cover products have appeared on the market. These products use motors to drive the opening and closing of the roller shutter, which improves the convenience of operation. However, the existing electric rolling shutter cover system still has some limitations in terms of control methods and functions.

[0003] On the one hand, most electric roller shutters are controlled by wires and need to be operated by switches or remote controls in the car. This control method has problems such as complex wiring and inconvenient installation. In addition, the effective control distance of the remote control is limited and it is not flexible enough to use. On the other hand, the existing electric roller shutters are relatively simple in function and lack intelligent sensing functions. For example, it is impossible to automatically sense changes in environmental conditions, such as rainfall, light, etc., and it is impossible to automatically adjust the state of the roller shutter according to actual conditions. In some cases, items in the car may be damaged because the user forgets to close the roller shutter. Summary of the invention

[0004] The present invention provides an automatic control system for a pickup truck rolling cover based on RF communication and intelligent sensing, which aims to intelligently control the opening and closing and start and stop of the pickup truck rolling cover through advanced wireless communication technology and intelligent sensor technology combined with big data analysis models, so as to solve the problems of poor control effect and accuracy of the prior art.

[0005] The purpose of the present invention can be achieved through the following technical solutions: The present application provides an automatic control system for a pickup truck rolling shutter cover based on RF communication and intelligent sensing, including an environment monitoring module, an environment analysis module, an intelligent control module and a voice feedback module, wherein the environment monitoring module, the environment analysis module, the intelligent control module and the voice feedback module are communicatively connected, wherein: The environmental monitoring module monitors the environmental conditions around the pickup truck's rolling shutter cover in real time by arranging sensors; The environmental analysis module is used to analyze the current in-vehicle comfort level according to the environmental conditions, including: S1. Collecting large-scale pickup truck rolling cover environmental conditions and corresponding in-vehicle comfort data in historical periods, wherein the in-vehicle comfort includes human perception index, item preservation index and driving safety index; S2, using environmental conditions as explanatory variables and in-vehicle comfort as response variables, construct a deep learning model; S3, input the current environmental conditions into the deep learning model and output the current in-vehicle comfort; The intelligent control module uses solar cells to generate electricity and is used to control the start and pause of the pickup truck's rolling shutter cover to open and close the rolling shutter cover according to the current comfort level in the vehicle; The voice feedback module is installed at the rear of the rolling door and is used to voice broadcast the status of the rolling door of the pickup truck.

[0006] Furthermore, the environmental conditions include rainfall, light intensity, temperature, humidity and air quality.

[0007] Furthermore, the deep learning model includes the following construction steps: S21. Data preparation: Clean and preprocess the collected historical data, remove outliers and missing values, and perform data standardization or normalization; S22, model selection: selecting a deep learning model suitable for the regression problem to learn the relationship between environmental conditions and in-vehicle comfort, wherein the deep learning model includes a multi-layer perceptron, a model combining a convolutional neural network and a fully connected layer, and a recurrent neural network model; S23. Model architecture design: For multi-layer perceptrons, a fully connected network with multiple hidden layers is designed. The number of nodes in the input layer corresponds to the number of environmental condition variables, and the number of nodes in the output layer corresponds to the number of in-vehicle comfort variables. The number of nodes in the hidden layer is determined through experiments and parameter adjustment. For the model combining convolutional neural network and fully connected layer, the convolutional neural network is first used to extract features of environmental condition data, and then the extracted features are input into the fully connected layer for regression prediction; For the recurrent neural network model, the environmental condition data is input into the model in time series. Each time step corresponds to an environmental condition observation value. The changing trend of environmental conditions over time and their impact on the comfort level in the car are learned. Finally, the predicted value of the comfort level in the car is output through the fully connected layer. S24, Training and Optimization: Divide the prepared data into training set, validation set and test set; select a loss function to measure the difference between the model prediction value and the true value; use the optimization algorithm to train the model and minimize the loss function by continuously adjusting the model weights and biases; S25. Model evaluation and improvement: Use the test set to evaluate the trained model. Based on the evaluation results, analyze the shortcomings of the model and make corresponding improvements. Retrain and evaluate the improved model until the preset performance is achieved.

[0008] Furthermore, the intelligent control module includes a sending module, a receiving module and an execution module, wherein: The sending module is placed in the cab and is used to generate a control instruction for starting or pausing the rolling shutter cover according to the current comfort level in the vehicle, and send the control instruction via RF wireless communication; The receiving module is placed near the rolling door and is used to receive control instructions; The execution module is used to control the start and pause of the rolling shutter cover of the pickup truck according to the received control instructions.

[0009] Furthermore, sending the control instruction via RF wireless communication comprises the following steps: Instruction encoding: Encode the generated control instructions for starting or pausing the rolling shutter cover, and convert the control instructions into a format suitable for transmission in the RF wireless communication channel; add verification information during the encoding process to determine whether the control instructions have errors during transmission; Modulation signal: modulate the coded control instruction onto the radio frequency signal for wireless transmission, the modulation includes amplitude modulation, frequency modulation and phase modulation; Transmitting signal: The modulated RF signal is transmitted through the antenna of the transmitting module; Monitoring and retransmission: After transmitting the signal, the sending module continuously monitors the transmission status of the signal. If it is found that the signal is lost, erroneous or seriously interfered with during the transmission process, the sending module can take corresponding measures to deal with it.

[0010] Furthermore, the execution module uses PWM to control the start and pause of the rolling shutter cover of the pickup truck.

[0011] Furthermore, the intelligent control module automatically stops the opening and closing action when the resistance encountered during the opening and closing action of the rolling shutter cover when starting or pausing is greater than a set value.

[0012] Furthermore, the intelligent control module also obtains the unlocking and locking status of the rolling shutter cover of the pickup truck through the CAN protocol, and the rolling shutter cover can be opened only in the unlocking state.

[0013] Furthermore, the voice broadcasting of the state of the pickup truck rolling cover includes: Solar battery power notification: When the solar module battery power is lower than the set value, the power notification will be turned on to remind you to charge before use; Fault reporting: When the rolling shutter door is blocked by foreign objects or overloaded, fault reporting will be activated, such as reminding you to clean the foreign objects before using the rolling shutter door. Maintenance report: a report will be issued every three months of use.

[0014] Beneficial effects of the present invention: (1) By arranging sensors, the environmental conditions around the rolling shutter cover of the pickup truck are monitored in real time; according to the environmental conditions, the current comfort level in the vehicle is analyzed; according to the current comfort level in the vehicle, the start and pause of the rolling shutter cover of the pickup truck is controlled to open and close the rolling shutter cover. The present invention solves the problems of the prior art, such as complex wiring, lack of intelligent sensing function, inability to automatically sense changes in environmental conditions, inability to automatically adjust the state of the rolling shutter cover according to actual conditions, and poor control effect and accuracy of the rolling shutter cover.

[0015] (2) The relationship between environmental conditions and in-vehicle comfort is quantified through a deep learning model, which improves the accuracy of roller shutter control and enables the roller shutter to be opened and closed according to the surrounding environmental conditions to meet the in-vehicle comfort requirements. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] In order to facilitate understanding by those skilled in the art, the present invention is further described below with reference to the accompanying drawings.

[0017] Figure 1 The structure diagram of the automatic control system of the rolling shutter cover of a pickup truck based on RF communication and intelligent sensing in the present invention.

[0018] Figure 2 The figure is a flow chart of an environment analysis module in one embodiment of the present invention.

[0019] Figure 3 A flowchart of a deep learning model constructed in one embodiment of the present invention. DETAILED DESCRIPTION

[0020] In order to further explain the technical means and effects adopted by the present invention to achieve the predetermined invention purpose, the specific implementation mode, structure, characteristics and effects of the present invention are described in detail below in combination with the accompanying drawings and preferred embodiments.

[0021] See also Figure 1-Figure 3 The present application provides an automatic control system for a pickup truck rolling shutter cover based on RF communication and intelligent sensing, including an environment monitoring module, an environment analysis module, an intelligent control module and a voice feedback module, wherein the environment monitoring module, the environment analysis module, the intelligent control module and the voice feedback module are communicatively connected, wherein: The environmental monitoring module monitors the environmental conditions around the pickup truck's rolling shutter cover in real time by arranging sensors; Furthermore, the environmental conditions include rainfall, light intensity, temperature, humidity and air quality.

[0022] In this embodiment, the environmental monitoring module monitors the environmental conditions such as the amount of rain, light intensity, temperature, humidity and air quality around the rolling shutter cover of the pickup truck in real time by arranging sensors, and provides accurate data support for the automatic control system, thereby realizing intelligent control of the rolling shutter cover and improving the suitability and convenience of the in-vehicle environment. Among them, the monitoring of the amount of rain is crucial to protecting the items in the pickup truck compartment. If the rolling shutter cover is not closed in time, a large amount of rain entering the compartment may damage the cargo, electronic equipment and the interior of the compartment. Rain sensors are usually used to detect the amount of rain. This sensor can determine the intensity of the rain by sensing the size and frequency of raindrops. Some advanced rain sensors can also distinguish different types of precipitation, such as drizzle, light rain, moderate rain and heavy rain.

[0023] Light intensity directly affects the temperature and comfort level inside the vehicle. Strong sunlight can quickly increase the temperature inside the vehicle, which will not only make passengers feel uncomfortable, but may also damage some items, such as electronic products and food. In addition, appropriate light intensity can also provide good lighting inside the vehicle and improve driving safety. Light sensors can measure the light intensity around the pickup truck. These sensors usually work based on the photoelectric effect and can convert light intensity into electrical signals. Light sensors can be installed on the roof, windows or other suitable locations of the pickup truck to ensure that the surrounding light conditions can be accurately measured.

[0024] Temperature is one of the important factors that affect the suitability of the in-vehicle environment. Too high or too low a temperature will affect the comfort and health of passengers. Temperature control is also very important for some special items, such as medicines and food. Temperature sensors can monitor the temperature around the roller shutter cover of pickup trucks in real time. These sensors can measure air temperature, surface temperature of the cabin, etc. Temperature sensors can use contact or non-contact measurement methods, depending on the application scenario and needs.

[0025] Humidity affects the air quality and comfort inside the vehicle. High humidity may cause mold growth, metal corrosion and other problems, while low humidity may make the human body feel dry and uncomfortable. Humidity control is also very important for some humidity-sensitive items, such as paper documents and electronic products. Humidity sensors can measure the air humidity around the pickup truck. These sensors usually work based on capacitive, resistive or other principles. Humidity sensors can be installed inside or outside the vehicle to ensure that the surrounding humidity conditions can be accurately measured.

[0026] Air quality is directly related to the health and comfort of passengers. Air pollution in the car may come from the external environment, vehicle emissions, interior materials, etc. Good air quality can improve the mental state and work efficiency of passengers, and it also helps protect electronic equipment and other items in the car. Air quality sensors can detect the air quality around the pickup truck. These sensors can measure harmful gases, particulate matter, volatile organic compounds, etc. in the air. Air quality sensors can use different detection technologies, such as electrochemical sensors, optical sensors, semiconductor sensors, etc.

[0027] The environmental analysis module is used to analyze the current in-vehicle comfort level according to the environmental conditions, including: S1. Collecting large-scale pickup truck rolling cover environmental conditions and corresponding in-vehicle comfort data in historical periods, wherein the in-vehicle comfort includes human perception index, item preservation index and driving safety index; In this embodiment, the interior suitability of the vehicle is significantly affected by the surrounding environmental conditions and can be characterized by the following aspects: 1. Human body feeling index Comfort rating: A certain number of pickup truck drivers can be surveyed and asked to rate the comfort level in the car under different environmental conditions, such as very comfortable, comfortable, average, uncomfortable, very uncomfortable, etc.

[0028] Thermal Sensation Voting: Allow drivers to vote on the thermal sensation inside the car, which is divided into different options such as hot, warm, moderate, cool, and cold to reflect the subjective feeling of the temperature inside the car.

[0029] Air freshness: Drivers evaluate whether the air in the car is fresh, which can be divided into very fresh, fresh, general, not fresh, very not fresh and other levels, reflecting the subjective impact of the air quality in the car on people.

[0030] 2. Item preservation indicators Item status assessment: For items that are often placed in pickup trucks, such as electronic products, documents, tools, etc., they are assessed based on their preservation status under different environmental conditions. For example, whether electronic products are damp, documents are deformed, tools are rusted, etc., and are divided into different levels such as good, average, and poor.

[0031] Item damage rate: Statistics on the proportion of items placed in the car that are damaged due to environmental factors within a certain period of time. The lower the damage rate, the higher the suitability of the car.

[0032] 3. Driving safety indicators Vision clarity: Considers the impact of factors such as lighting and humidity in the car on the driver's vision under different environmental conditions. It can be divided into clear, relatively clear, general, unclear, and very unclear levels to evaluate the impact of the in-car environment on driving safety.

[0033] Operational convenience: For example, whether the driver's operation of vehicle control components (such as steering wheel, gear lever, etc.) is affected in high or low temperature environments, which is divided into levels such as convenient, relatively convenient, average, inconvenient, and very inconvenient.

[0034] S2, using environmental conditions as explanatory variables and in-vehicle comfort as response variables, construct a deep learning model; In this embodiment, judging the comfort level in the car according to the current environmental conditions can improve the control of the roller shutter cover and achieve satisfactory results. However, the existing technology is not familiar with the relationship between environmental conditions and the comfort level in the car, which makes it impossible to accurately judge the comfort level in the car according to the current environmental conditions. Therefore, the deep learning model of this embodiment quantifies the relationship between the two, thereby improving the control accuracy of the roller shutter cover. The following are the steps to build a deep learning model: S21. Data preparation: Clean and preprocess the collected historical data, remove outliers and missing values, and standardize or normalize the data so that the model can learn and converge better.

[0035] S22. Model selection: Choose a deep learning model suitable for regression problems, such as multi-layer perceptron (MLP), convolutional neural network (CNN) combined with fully connected layers for sequence data, recurrent neural network (RNN) especially long short-term memory network (LSTM) or gated recurrent unit (GRU), etc. These models are able to handle different types of input data and learn the complex relationship between environmental conditions and in-vehicle comfort.

[0036] Considering that environmental condition data has time series characteristics (e.g., temperature, humidity, etc. change over time), LSTM or GRU are more appropriate because they can capture long-term dependencies in time series.

[0037] S23. Model architecture design: For MLP, a fully connected network with multiple hidden layers can be designed. The number of nodes in the input layer corresponds to the number of environmental condition variables, and the number of nodes in the output layer corresponds to the number of in-vehicle comfort variables. The number of nodes in the hidden layer can be determined through experiments and parameter adjustment.

[0038] For the model that combines CNN and fully connected layers, CNN can be used to extract features of environmental condition data first. For example, temperature, humidity and other data can be regarded as different channels of the image, and then the extracted features can be input into the fully connected layer for regression prediction.

[0039] For LSTM or GRU, the environmental condition data can be input into the model in time series, and each time step corresponds to an environmental condition observation value. The LSTM or GRU layer can learn the changing trend of environmental conditions over time and their impact on the comfort level in the car, and finally output the predicted value of the comfort level in the car through the fully connected layer.

[0040] S24, Training and Optimization: Divide the prepared data into training set, validation set and test set. The training set is used to learn the model, the validation set is used to adjust the model's hyperparameters and monitor the model's performance, and the test set is used to ultimately evaluate the model's generalization ability.

[0041] Choose an appropriate loss function, such as mean squared error (MSE) or mean absolute error (MAE), to measure the difference between the model's predictions and the true values.

[0042] Use optimization algorithms such as stochastic gradient descent (SGD) and Adam to train the model, and minimize the loss function by continuously adjusting the weights and biases of the model.

[0043] During the training process, techniques such as early stopping and learning rate decay can be used to prevent overfitting and improve the generalization ability of the model.

[0044] S25. Model evaluation and improvement: Use the test set to evaluate the trained model and calculate evaluation indicators such as MSE, MAE, R², etc. to understand the performance of the model.

[0045] Based on the evaluation results, analyze the deficiencies of the model and make corresponding improvements. You can try to adjust the model architecture, increase the amount of data, improve the data preprocessing method, adjust the hyperparameters, etc.

[0046] The improved model is trained and evaluated again until satisfactory performance is achieved.

[0047] S3, input the current environmental conditions into the deep learning model and output the current in-vehicle comfort; The intelligent control module uses solar cells to generate electricity and is used to control the start and pause of the pickup truck's rolling shutter cover to open and close the rolling shutter cover according to the current comfort level in the vehicle. It includes a sending module, a receiving module and an execution module, wherein: The sending module is placed in the cab and is used to generate a control instruction for starting or pausing the rolling shutter cover according to the current comfort level in the vehicle, and send the control instruction via RF wireless communication; In this embodiment, RF wireless communication technology is used in the transmission mode of the instruction. RF wireless communication uses radio waves to propagate signals in space. Its working principle is that the sending module modulates the control instruction to a radio frequency signal of a specific frequency and then transmits it through the antenna. The receiving module receives the radio frequency signal through the antenna and demodulates it to restore the control instruction. The frequency range of the radio frequency signal is usually between several hundred megahertz and several gigahertz, and different frequency ranges are suitable for different application scenarios.

[0048] RF wireless communication has many significant advantages. First, it does not require physical connection, which avoids the trouble and restrictions caused by wiring. In this way, the sending module and the receiving module can be installed in different locations more flexibly, which greatly facilitates the design and installation of the entire system. Secondly, RF wireless communication can achieve signal transmission over a certain distance, which is very suitable for larger vehicles such as pickup trucks. The driver sends control instructions in the car, which can be reliably transmitted to the roller shutter actuator module outside the car, and the stability of communication can be guaranteed even at a long distance. Furthermore, RF wireless communication usually considers anti-interference measures in design and can resist external electromagnetic interference to a certain extent. For example, the use of frequency selection, signal encryption and other technologies can improve the reliability and security of communication. Finally, RF wireless communication can support multiple devices to communicate at the same time. In the automatic control system of the pickup truck roller shutter, this means that multiple roller shutter actuator modules can be controlled at the same time, or integrated with other vehicle electronic systems to achieve more intelligent control.

[0049] In actual application scenarios, RF wireless communication performs well. On the one hand, the driver can send control instructions through the sending module in the car to remotely control the start and pause of the pickup truck's rolling cover. Whether in the parking lot or while driving, the rolling cover can be easily operated, which greatly improves the convenience of use. On the other hand, RF wireless communication can be combined with the intelligent sensing module. When the environmental monitoring module detects rain, excessive light, etc., it automatically sends a signal to the sending module. The driver can receive a reminder through RF wireless communication and remotely control the rolling cover to close, effectively protecting the items in the car from rain erosion or sun exposure. In addition, RF wireless communication can also be integrated with other electronic systems of the pickup truck, such as connecting with the vehicle's central control system, navigation system, etc., to achieve integrated control and display, further improving the vehicle's convenience and intelligence.

[0050] Furthermore, sending the control instruction via RF wireless communication comprises the following steps: Instruction encoding: The sending module first encodes the generated control instruction for starting or pausing the rolling shutter cover. The purpose of encoding is to convert the instruction into a format suitable for transmission in the RF wireless communication channel. This may involve the use of specific digital encoding methods, such as binary encoding or more complex encoding schemes, to ensure the accuracy and reliability of the instruction during transmission. At the same time, the encoding process can also add some verification information so that the receiving module can verify after receiving the instruction to determine whether the instruction has an error during transmission.

[0051] Modulation signal: The encoded control instructions need to be modulated onto the RF signal for wireless transmission. There are many modulation methods, the most common of which include amplitude modulation (AM), frequency modulation (FM) and phase modulation (PM). Select the appropriate modulation method based on the specific application requirements and the characteristics of the RF communication system. For example, frequency modulation may perform better in terms of anti-interference and is suitable for more complex environments. The modulated RF signal carries the control instruction information and can be transmitted in space.

[0052] Transmitting signal: The modulated RF signal is transmitted through the antenna of the transmitting module. The design and performance of the antenna have an important impact on the transmission distance and quality of the signal. The transmitting module needs to ensure that the antenna can effectively radiate the RF signal to the surrounding space and has a certain directionality and gain to improve the transmission efficiency of the signal. In the process of transmitting the signal, the transmitting module can also adjust the transmission power as needed to adapt to different transmission distances and environmental conditions. If the transmission distance is far or there are many obstacles, it may be necessary to increase the transmission power to ensure that the signal can be received by the receiving module.

[0053] Monitoring and retransmission: After transmitting the signal, the sending module continuously monitors the transmission status of the signal. If the signal is found to be lost, erroneous or seriously interfered with during the transmission process, the sending module can take corresponding measures to deal with it. For example, it can automatically retransmit and resend the control command until the receiving module successfully receives the correct command. At the same time, the sending module can also dynamically adjust the transmission power, modulation mode and other parameters according to the monitored signal quality to optimize the signal transmission performance.

[0054] The receiving module is placed near the rolling door and is used to receive control instructions; The execution module is used to control the start and pause of the rolling shutter cover of the pickup truck according to the received control instruction; Furthermore, the execution module uses PWM to control the start and pause of the rolling shutter cover of the pickup truck.

[0055] In this embodiment, the execution module uses PWM (pulse width modulation) to control the start and pause of the rolling cover. PWM is a technology that controls the average power of the output signal by changing the pulse width. The execution module generates a corresponding PWM signal according to the control instruction transmitted by the receiving module. When the rolling cover needs to be started, a high duty cycle pulse signal is output to make the motor rotate forward to drive the rolling cover to roll up; when it is paused, a low duty cycle signal is output to reduce or stop the motor speed. PWM control has the advantages of precise control of motor speed, high efficiency and energy saving, high reliability and easy implementation. It can achieve fine control of the movement speed of the rolling cover, making its start and pause smoother, and can also adjust the motor output power according to actual needs to save energy. At the same time, the motor operation status and the position of the rolling cover are monitored by sensors to achieve closed-loop control and improve the stability and safety of the system.

[0056] Furthermore, the intelligent control module automatically stops the opening and closing action when the resistance encountered during the opening and closing action of the rolling shutter cover when starting or pausing is greater than a set value.

[0057] In this embodiment, when the resistance encountered by the rolling shutter cover during the opening and closing action of starting or pausing is greater than the set value, the opening and closing action is automatically stopped. This function is mainly for safety and protection considerations. On the one hand, if a large resistance is encountered during the opening and closing process but the forceful action is continued, the mechanical structure of the rolling shutter cover may be damaged, such as motor overload, transmission component damage, etc. Automatically stopping the opening and closing action can avoid such mechanical damage and extend the service life of the rolling shutter cover system. On the other hand, excessive resistance may mean that an obstacle blocks the movement of the rolling shutter cover. If it is not stopped in time, objects may be clamped, causing harm to people or objects. Automatically stopping the opening and closing action can prevent such accidents from happening and improve the safety of use. The intelligent control module monitors the resistance during the movement of the rolling shutter cover in real time. Once it detects that the resistance exceeds the set value, it quickly issues a command to stop the motor operation, thereby realizing automatic stopping of the opening and closing action. This function makes the automatic control system of the pickup truck rolling shutter cover more intelligent, reliable and safe.

[0058] Furthermore, the intelligent control module also obtains the unlocking and locking status of the rolling shutter cover of the pickup truck through the CAN protocol, and the rolling shutter cover can be opened only in the unlocking state.

[0059] In this embodiment, the CAN (Controller Area Network) protocol plays a key role. The CAN protocol is a serial communication protocol designed specifically for the automotive industry and is now widely used in many industrial fields. It has many significant features. First, it has extremely high reliability. It uses a variety of error detection and correction mechanisms such as cyclic redundancy check, bit filling and error frame detection to ensure accurate data transmission. Secondly, it has strong real-time performance and can meet the needs of time-sensitive applications. It has a certain transmission delay and a high-priority message priority transmission mechanism to ensure that key information is delivered in a timely manner. Furthermore, the CAN network supports multi-master communication, and multiple nodes can send and receive data at the same time. There is no master-slave relationship, making the system more flexible and scalable. At the same time, it has strong anti-interference ability, uses differential signal transmission and shielding technology, can effectively resist electromagnetic interference and noise, and can work reliably in harsh industrial environments. In the automatic control system of the roller shutter cover of a pickup truck, the CAN protocol is mainly used to obtain the unlocking and locking status of the roller shutter cover. The intelligent control module monitors various vehicle status information in real time by connecting to the vehicle's CAN bus. When the roller shutter cover is in the unlocked state, it receives the corresponding signal and allows the roller shutter cover to be opened. In the locked state, it prohibits opening to ensure operational safety. In addition, the CAN protocol can also be integrated with other vehicle systems to achieve more advanced functions, such as communicating with the central control system and safety system to achieve integrated control and management.

[0060] The voice feedback module is installed at the rear of the rolling door and is used to voice broadcast the status of the rolling door of the pickup truck.

[0061] Furthermore, the voice broadcasting of the state of the pickup truck rolling cover includes: Solar battery power notification: When the solar module battery power is lower than the set value, the power notification will be turned on to remind you to charge before use; Fault reporting: When the rolling shutter door is blocked by foreign objects or overloaded, fault reporting will be activated, such as reminding you to clean the foreign objects before using the rolling shutter door. Maintenance report: a report will be issued every three months of use.

[0062] In this embodiment, the voice broadcast function in the automatic control system of the pickup truck rolling shutter cover has many important significances. First, let's look at the solar cell power broadcast. When the battery power of the solar module equipped with the system is lower than the set value, the voice broadcast will sound in time to remind the user to charge before use. This function is crucial because the solar cell provides power for the automatic control system, reducing the dependence on the vehicle power supply and enhancing the autonomy and sustainability of the system. When the power is insufficient, timely reminding the user can avoid the system from not working properly due to power shortage, thereby ensuring the convenience of using the rolling shutter cover. For fault broadcasting, when the rolling shutter door is blocked by foreign objects or is in an overloaded operating state, the system can detect abnormal conditions through sensors. At this time, the voice broadcast will start quickly, for example, reminding the user that "the rolling shutter door is blocked by foreign objects, please clean it before use." This function allows users to understand the problem at the first time and take the correct treatment method to avoid further damage to the mechanical structure and motor of the rolling shutter cover, while also eliminating potential safety hazards. Maintenance broadcasts are also indispensable. Every three months of use, the system will make a voice broadcast to remind users to maintain the pickup truck rolling shutter cover. Regular maintenance helps extend the life of the rolling shutter cover and ensure the performance and reliability of the system. Through voice reminders, users can develop good maintenance habits and perform maintenance work such as inspection, cleaning, and lubrication in a timely manner.

[0063] The above description is only a preferred embodiment of the present invention and does not limit the present invention in any form. Although the present invention has been disclosed as a preferred embodiment as above, it is not used to limit the present invention. Any technical personnel in this field can make some changes or modify the technical contents disclosed above into equivalent embodiments without departing from the scope of the technical solution of the present invention. However, any brief modifications, equivalent changes and modifications made to the above embodiments based on the technical essence of the present invention without departing from the content of the technical solution of the present invention are still within the scope of the technical solution of the present invention.

Claims

1. An automatic control system for a pickup truck rolling shutter cover based on RF communication and intelligent sensing, characterized in that: It includes an environment monitoring module, an environment analysis module, an intelligent control module and a voice feedback module, wherein the environment monitoring module, the environment analysis module, the intelligent control module and the voice feedback module are communicatively connected, wherein: The environmental monitoring module monitors the environmental conditions around the pickup truck's rolling shutter cover in real time by arranging sensors; The environmental analysis module is used to analyze the current in-vehicle comfort level according to the environmental conditions, including: S1. Collecting large-scale pickup truck rolling cover environmental conditions and corresponding in-vehicle comfort data in historical periods, wherein the in-vehicle comfort includes human perception index, item preservation index and driving safety index; S2, using environmental conditions as explanatory variables and in-car comfort as response variables, construct a deep learning model; S3, input the current environmental conditions into the deep learning model and output the current in-vehicle comfort; The intelligent control module uses solar cells to generate electricity and is used to control the start and pause of the pickup truck's rolling shutter cover to open and close the rolling shutter cover according to the current comfort level in the vehicle; The voice feedback module is installed at the rear of the rolling door and is used to voice broadcast the status of the rolling door of the pickup truck.

2. The automatic control system for the rolling shutter cover of a pickup truck based on RF communication and intelligent sensing according to claim 1 is characterized in that: The environmental conditions include rainfall, light intensity, temperature, humidity and air quality.

3. The automatic control system for rolling shutter cover of pickup truck based on RF communication and intelligent sensing according to claim 1, characterized in that: The deep learning model includes the following construction steps: S21. Data preparation: Clean and preprocess the collected historical data, remove outliers and missing values, and perform data standardization or normalization; S22, model selection: selecting a deep learning model suitable for the regression problem to learn the relationship between environmental conditions and in-vehicle comfort, wherein the deep learning model includes a multi-layer perceptron, a model combining a convolutional neural network and a fully connected layer, and a recurrent neural network model; S23. Model architecture design: For multi-layer perceptrons, a fully connected network with multiple hidden layers is designed. The number of nodes in the input layer corresponds to the number of environmental condition variables, and the number of nodes in the output layer corresponds to the number of in-vehicle comfort variables. The number of nodes in the hidden layer is determined through experiments and parameter adjustment. For the model combining convolutional neural network and fully connected layer, the convolutional neural network is first used to extract features of environmental condition data, and then the extracted features are input into the fully connected layer for regression prediction; For the recurrent neural network model, the environmental condition data is input into the model in time series. Each time step corresponds to an environmental condition observation value. The changing trend of environmental conditions over time and their impact on the comfort level in the car are learned. Finally, the predicted value of the comfort level in the car is output through the fully connected layer. S24, Training and Optimization: Divide the prepared data into training set, validation set and test set; select a loss function to measure the difference between the model prediction value and the true value; use the optimization algorithm to train the model and minimize the loss function by continuously adjusting the model weights and biases; S25. Model evaluation and improvement: Use the test set to evaluate the trained model. Based on the evaluation results, analyze the shortcomings of the model and make corresponding improvements. Retrain and evaluate the improved model until the preset performance is achieved.

4. The automatic control system for the rolling shutter cover of a pickup truck based on RF communication and intelligent sensing according to claim 1 is characterized in that: The intelligent control module includes a sending module, a receiving module and an execution module, wherein: The sending module is placed in the cab and is used to generate a control instruction for starting or pausing the rolling shutter cover according to the current comfort level in the vehicle, and send the control instruction via RF wireless communication; The receiving module is placed near the rolling door and is used to receive control instructions; The execution module is used to control the start and pause of the rolling shutter cover of the pickup truck according to the received control instructions.

5. The automatic control system for the rolling shutter cover of a pickup truck based on RF communication and intelligent sensing according to claim 1 is characterized in that: The sending of the control instruction via RF wireless communication comprises the following steps: Instruction encoding: Encode the generated control instructions for starting or pausing the rolling shutter cover, and convert the control instructions into a format suitable for transmission in the RF wireless communication channel; add verification information during the encoding process to determine whether the control instructions have errors during transmission; Modulation signal: modulate the coded control instruction onto the radio frequency signal for wireless transmission, the modulation includes amplitude modulation, frequency modulation and phase modulation; Transmitting signal: The modulated RF signal is transmitted through the antenna of the transmitting module; Monitoring and retransmission: After transmitting the signal, the sending module continuously monitors the transmission status of the signal. If it is found that the signal is lost, erroneous or seriously interfered with during the transmission process, the sending module takes corresponding measures to deal with it.

6. The automatic control system for the rolling shutter cover of a pickup truck based on RF communication and intelligent sensing according to claim 4 is characterized in that: The execution module uses PWM to control the start and pause of the rolling shutter cover of the pickup truck.

7. The automatic control system for rolling shutter cover of pickup truck based on RF communication and intelligent sensing according to claim 1, characterized in that: The intelligent control module automatically stops the opening and closing action when the resistance encountered during the opening and closing action of the rolling shutter cover when starting or pausing is greater than a set value.

8. The automatic control system for rolling shutter cover of pickup truck based on RF communication and intelligent sensing according to claim 1, characterized in that: The intelligent control module also obtains the unlocking and locking status of the rolling shutter cover of the pickup truck through the CAN protocol, and the rolling shutter cover can be opened only in the unlocking state.

9. The automatic control system for rolling shutter cover of pickup truck based on RF communication and intelligent sensing according to claim 1, characterized in that: The voice broadcasting of the state of the pickup truck rolling cover includes: Solar battery power notification: When the solar module battery power is lower than the set value, the power notification will be turned on to remind you to charge before use; Fault reporting: When the rolling shutter door is blocked by foreign objects or overloaded, fault reporting will be activated, such as reminding you to clean the foreign objects before using the rolling shutter door. Maintenance report: a report will be issued every three months of use.

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