Intelligent food pathogenic bacterium detection method based on bimodal sensing fusion and application device thereof

Abstract

The invention belongs to the technical field of food safety detection, and particularly relates to an intelligent food pathogenic bacterium detection method based on bimodal sensing fusion and an application device thereof. According to the method, the advantages of electricity and colorimetric bimodal sensing for cooperatively detecting food pathogenic bacterium metabolism volatile organic compounds (VOCs) are creatively integrated, a bimodal detection fusion model is constructed, environmental interference factors are eliminated through a compensation algorithm, and recognition of food pathogenic bacteria is achieved in combination with an artificial intelligence algorithm. The application device comprises a metabolic VOCs acquisition unit, a bimodal sensing unit, an environmental parameter acquisition unit, a display and early warning unit, an intelligent processing unit and a man-machine interaction terminal. Wherein the bimodal sensing unit of the device can synchronously obtain electrical response and color change information of food pathogenic bacteria metabolism VOCs, a detection result is output after algorithm processing, and then reliable identification, real-time early warning and intelligent monitoring of the food pathogenic bacteria are achieved. The bimodal sensing fusion food pathogenic bacterium intelligent detection method and the application device thereof provide an efficient solution for food safety monitoring, and have wide application prospects in the fields of food industry and public health.

Description

Technical Field

[0001] The present invention focuses on the field of food safety detection technology and is positioned in the category of intelligent detection technology. Specifically, an intelligent detection method and its application device for food pathogenic bacteria based on dual-modal sensing fusion are invented to solve the existing problems in the detection of food pathogenic bacteria and escort food safety. Background Art

[0002] The World Health Organization is an authoritative institution in the field of global public health. According to the organization's report, approximately 600 million people worldwide contract diseases each year due to consuming contaminated food, and 420,000 people die (Nature Reviews Bioengineering 2023, 1, 180). Among the many food safety hazards, food pathogenic bacteria occupy a prominent position and are the key factors triggering serious food crises. For example, once infected with Listeria monocytogenes, patients may develop meningitis and sepsis, and pregnant women are at high risk with a very high risk of miscarriage (Advanced Functional Materials 2022, 32, 2107439). Another example is that the intestinal infectious disease caused by Shigella not only has strong infectivity, but also the released toxins will enter the blood, causing systemic toxemia, septic shock and even toxic encephalopathy, endangering the lives of patients (Nature Communications 2021, 12, 4511). Thus, rapid and reliable pathogenic bacteria detection methods and intelligent detection devices are crucial for ensuring public food safety.

[0003] In the field of food pathogenic bacteria detection, traditional detection methods mainly include microbial culture methods, immunological detection methods, and molecular biology detection methods. The microbial culture method requires sample pretreatment and a long incubation process, resulting in a relatively long overall process. Immunological detection methods rely on the specific binding of antigens and antibodies, with a complex and cumbersome detection process and high requirements for the professional skills of experimental personnel. Molecular biology detection methods such as PCR technology are highly sensitive but suffer from problems such as complex operation and susceptibility to contamination. In recent years, with the development of sensing technology, a new food pathogenic bacteria detection method has been reported, that is, detecting the metabolic volatile organic compounds (VOCs) of food pathogenic bacteria through sensing technology to indirectly identify food pathogenic bacteria. In 2024, ACS Nano reported a resistive gas sensor based on single-atom gold-functionalized mesoporous tin oxide nanospheres, which can rapidly and sensitively detect the metabolic gas 3-hydroxy-2-butanone of Listeria monocytogenes (ACS Nano 2024, 18, 22888). In 2021, Nature Food reported a study: researchers achieved the identification of the metabolic VOCs of multiple food pathogenic bacteria based on machine learning colorimetric sensing array technology (Nature Food 2021, 1, 110). Although the above research has made certain progress, there are still many limitations in using only a single sensing technology to detect food pathogenic bacteria. For example, resistive gas sensors are susceptible to environmental temperature, humidity, and gas cross-interference factors, resulting in fluctuations in detection accuracy; while colorimetric sensing arrays, although having certain advantages in multi-component gas identification, are still insufficient in detection accuracy, and the reliability of detection results is difficult to guarantee. These problems limit the industrialization and wide application of single-sensing detection methods. Summary of the Invention

[0004] Aiming at the limitations of existing food pathogenic bacteria detection technologies, the present invention provides an intelligent detection method and its application device for food pathogenic bacteria based on dual-modal sensing fusion. By integrating the advantages of electrical and colorimetric dual-modal sensing for collaborative detection of the metabolic VOCs of food pathogenic bacteria, a dual-modal detection fusion model is constructed. Environmental interference factors are eliminated through a compensation algorithm, and reliable identification, real-time warning, and intelligent monitoring of food pathogenic bacteria are achieved by combining artificial intelligence algorithms, providing an efficient solution for ensuring food safety. To achieve the above object, the technical solutions adopted by the present invention are as follows.

[0005] On the one hand, the present invention provides an intelligent detection method for food pathogenic bacteria based on dual-modal sensing fusion, including the following steps: (1) Obtain the electrical response and color change information generated by detecting the metabolic VOCs of food pathogenic bacteria by electrical and colorimetric sensors; (2) Obtain environmental parameters including temperature, humidity, air pressure, and light intensity; (3) inputting the environmental parameters into a compensation algorithm to calibrate the electrical response and color change information; (4) fusing the calibrated electrical response and color change information to form a high-dimensional feature vector; (5) Inputting the high-dimensional feature vector into an artificial intelligence algorithm to output the identification results and concentrations of food pathogens.

[0006] Optionally, the electrical sensor includes at least one gas-sensitive element made of a sensitive material; the colorimetric sensor includes at least one colorimetric film element made of a sensitive material; and the electrical response information includes at least one of resistance, capacitance, frequency, voltage and current.

[0007] Optionally, the food pathogens include but are not limited to Escherichia coli, Salmonella, Staphylococcus aureus, Listeria monocytogenes, Pseudomonas aeruginosa, Shigella and Vibrio parahaemolyticus.

[0008] The compensation algorithm constructs a mathematical mapping relationship between the environmental parameters and the electrical response and color change information, uses a polynomial regression algorithm to quantify the influence weight of each environmental parameter, and performs error correction and calibration on the electrical response and color change information.

[0009] The AI algorithm uses a deep learning model based on a convolutional neural network architecture. The model comprises at least three convolutional layers and a fully connected layer, which extract features from the input high-dimensional feature vector layer by layer. Furthermore, based on the extracted key features, the algorithm uses a classification task to identify the species of food pathogens and a regression task to predict the concentration of food pathogens.

[0010] Another aspect of the present invention provides an intelligent detection device for food pathogens based on dual-modal sensing fusion, which includes a metabolic VOCs acquisition unit, a dual-modal sensing unit, an environmental parameter acquisition unit, a display and early warning unit, an intelligent processing unit and a human-computer interaction terminal.

[0011] The metabolic VOCs collection unit includes a micro air pump, a micro fan, a relay, and a relay module circuit composed of multiple resistors and capacitors, which is used to actively collect metabolic VOCs of food pathogens and supply them to the dual-modal sensing unit for detection.

[0012] The dual-modal sensing unit is connected to the metabolic VOCs acquisition unit and the intelligent processing unit, and includes an electrical sensor, an electrical signal acquisition module, a colorimetric sensor and a color change acquisition module, which are used to detect the metabolic VOCs of the food pathogens to obtain electrical response and color change information.

[0013] The environmental parameter acquisition unit is connected to the intelligent processing unit and includes a temperature and humidity sensing module, a barometric pressure sensing module, and a light intensity sensing module, and is used to obtain temperature, humidity, barometric pressure, and light intensity parameters.

[0014] The display and warning unit is connected to the intelligent processing unit and includes a display module and an acoustic-optic warning module, and is used to display and warn the user of the types and concentrations of the food pathogenic bacteria.

[0015] The human-computer interaction terminal is used to monitor the types and concentrations of the food pathogenic bacteria in real time and allows the user to remotely control the display and warning unit.

[0016] The intelligent processing unit includes a communication module, a memory, a processor, and computer programs and algorithms stored on the memory and executable on the processor, and is used to coordinate and control the operation and function implementation of the intelligent food pathogenic bacteria detection device.

[0017] The electrical signal acquisition module is connected to the electrical sensor and includes an operational amplifier, a reference voltage circuit composed of multiple resistors and capacitors, and a filtering circuit, and is used to process the electrical response of the electrical sensor.

[0018] Optionally, the color change acquisition module is connected to the colorimetric sensor and includes at least one of a camera module and a color sensor module, and is used to convert the color change of the colorimetric sensor into digital information.

[0019] Optionally, the display module includes at least one of an LCD display module and an OLED display module.

[0020] Optionally, the human-computer interaction terminal includes at least one of a smart phone, a computer, and a smart watch.

[0021] The communication module supports wireless communication technology and is used to realize data transmission and instruction interaction between the intelligent food pathogenic bacteria detection device and the human-computer interaction terminal.

[0022] When the computer programs and algorithms are executed by the processor, they can implement all the steps and functions in the above-mentioned intelligent food pathogenic bacteria detection method based on dual-modal sensing fusion.

[0023] Compared with the prior art, the present invention has the following technical advantages: An intelligent detection method and application device for food pathogenic bacteria based on dual-modal sensing fusion provided by the present invention innovatively applies electrical and colorimetric dual-modal sensors to the detection process of food pathogenic bacteria metabolizing VOCs. By integrating the advantages of the electrical and colorimetric sensors working together, more comprehensive and accurate detection information is obtained. At the same time, the present invention incorporates a compensation algorithm to eliminate environmental interference factors, and combines artificial intelligence algorithms to deeply analyze and process the detection data, realizing reliable identification, real-time warning and intelligent monitoring of food pathogenic bacteria, providing a fast and reliable solution for ensuring food safety. The present invention shows broad application prospects in the field of food pathogenic bacteria detection technology, is expected to promote technological innovation and development in this field, bring new breakthroughs to food safety monitoring and guarantee, and greatly improve the efficiency and accuracy of food safety monitoring. BRIEF DESCRIPTION OF THE DRAWINGS

[0024] In order to more clearly illustrate the embodiments of the present invention or the solutions in the prior art, the following will briefly introduce the drawings required for use in the embodiments. Obviously, the drawings described below are only some embodiments of the present invention, and those of ordinary skill in the art can obtain other drawings without creative efforts based on these drawings.

[0025] Figure 1 It is a flowchart of an intelligent detection method for food pathogenic bacteria based on dual-modal sensing fusion provided by an embodiment of the present invention; Figure 2 It is a functional block diagram of an intelligent detection device for food pathogenic bacteria based on dual-modal sensing fusion provided by an embodiment of the present invention; Figure 3 It is a flowchart of an intelligent detection device for food pathogenic bacteria based on dual-modal sensing fusion provided by an embodiment of the present invention; Figure 4 It is a structural unit composition diagram of the first intelligent detection device for food pathogenic bacteria based on dual-modal sensing fusion provided by an embodiment of the present invention; Figure 5 It is a structural unit composition diagram of the second intelligent detection device for food pathogenic bacteria based on dual-modal sensing fusion provided by an embodiment of the present invention; Figure 6 It is a structural unit composition diagram of the third intelligent detection device for food pathogenic bacteria based on dual-modal sensing fusion provided by an embodiment of the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0026] The following will be combined with the accompanying drawings in the embodiments of this application to clearly and completely describe the technical solutions in the embodiments of this application. Obviously, the embodiments described are only part of the embodiments of this application, not all of them. Based on these embodiments in this application, all other embodiments obtained by ordinary technicians in this field are within the scope of protection of this application.

[0027] Example 1 See also Figure 1 , Figure 1 This is a flow chart of a method for intelligent detection of food pathogens based on dual-modal sensor fusion provided by an embodiment of the present invention, including: S100, obtaining electrical response and color change information generated by detecting VOCs metabolized by food pathogens using electrical and colorimetric sensors; S110, obtaining environmental parameters including temperature, humidity, air pressure and light intensity; S120, inputting the environmental parameters into a compensation algorithm to calibrate the electrical response and color change information; S130, fusing the calibrated electrical response and color change information to form a high-dimensional feature vector; S140. Input the high-dimensional feature vector into an artificial intelligence algorithm, and output the identification result and concentration of food pathogens.

[0028] Optionally, the electrical sensor includes at least one gas-sensitive element made of a sensitive material; the colorimetric sensor includes at least one colorimetric film element made of a sensitive material; and the electrical response information includes at least one of resistance, capacitance, frequency, voltage and current.

[0029] Optionally, the food pathogens include but are not limited to Escherichia coli, Salmonella, Staphylococcus aureus, Listeria monocytogenes, Pseudomonas aeruginosa, Shigella and Vibrio parahaemolyticus; the compensation algorithm constructs a mathematical mapping relationship between the environmental parameters and the electrical response and color change information, uses a polynomial regression algorithm to quantify the influence weight of each environmental parameter, and performs error correction and calibration on the electrical response and color change information.

[0030] The artificial intelligence algorithm adopts a deep learning model based on a convolutional neural network architecture, which includes at least three convolutional layers and a fully connected layer. The model performs layer-by-layer feature extraction operations on the input high-dimensional feature vector through the convolutional layers and the fully connected layers. Furthermore, based on the extracted key features, the types of food pathogens are identified through classification tasks, and the concentration of food pathogens is predicted using regression tasks.

[0031] Example 2 See also Figure 2 , Figure 2This is the overall functional block diagram of an intelligent food pathogenic bacteria detection device based on dual - modality sensing fusion provided by an embodiment of the present invention, which includes a metabolic VOCs collection unit, a dual - modality sensing unit, an environmental parameter collection unit, a display and warning unit, an intelligent processing unit, and a human - machine interaction terminal, where: The metabolic VOCs collection unit is connected to the dual - modality sensing unit; the intelligent processing unit is connected to all other functional units; the intelligent processing unit can be remotely connected and communicate with the human - machine interaction terminal through wireless communication technology.

[0032] Optionally, the wireless communication technology includes, but is not limited to, WiFi communication technology and Bluetooth communication technology.

[0033] Embodiment 3 Based on the above content, please refer to Figure 3 , Figure 3 This is the working flow chart of an intelligent food pathogenic bacteria detection device based on dual - modality sensing fusion provided by an embodiment of the present invention, including: S200. Actively collect the metabolic VOCs of food pathogenic bacteria through the metabolic VOCs collection unit and supply them to the dual - modality sensing unit for detection; The metabolic VOCs collection unit includes a micro air pump, a micro fan, a relay, and a relay module circuit composed of multiple resistors and capacitors.

[0034] S210. Detect the metabolic VOCs of food pathogenic bacteria through the dual - modality sensing unit to obtain electrical response and color change information; The dual - modality sensing unit includes an electrical sensor, an electrical signal acquisition module, a colorimetric sensor, and a color change acquisition module; the electrical signal acquisition module is connected to the electrical sensor and includes an operational amplifier, a reference voltage circuit composed of multiple resistors and capacitors, and a filtering circuit for processing the electrical response of the electrical sensor.

[0035] Optionally, the color change acquisition module is connected to the colorimetric sensor and includes at least one of a camera module and a color sensor module for converting the color change of the colorimetric sensor into digital information.

[0036] Optionally, the electrical sensor includes at least 1 gas - sensitive element made of a sensitive material; the colorimetric sensor includes at least 1 colorimetric film element made of a sensitive material; the electrical response information includes at least 1 of resistance, capacitance, frequency, voltage, and current.

[0037] S220. Obtain temperature, humidity, air pressure, and light intensity parameters through the environmental parameter collection unit; The environmental parameter collection unit includes a temperature and humidity sensing module, an air pressure sensing module, and a light sensing module.

[0038] S230. Analyze and process the electrical response, color change, temperature, humidity, air pressure, and light intensity parameters through an intelligent processing unit; The intelligent processing unit includes a communication module, a memory, a processor, and computer programs and algorithms stored on the memory and executable on the processor, and is used to coordinate and control the operation and function implementation of the food pathogenic bacteria intelligent detection device.

[0039] The communication module supports wireless communication technologies, including but not limited to WiFi module and Bluetooth module.

[0040] When the computer programs and algorithms are executed by the processor, all steps and functions in the described intelligent detection method for food pathogenic bacteria based on dual-modal sensing fusion can be realized.

[0041] S240. Real-time display the types and concentrations of food pathogenic bacteria through a display and warning unit. If the concentration exceeds the threshold, perform acoustic and optical warnings; The display and warning unit includes a display module and an acoustic and optical warning module; the display module includes at least one of an LCD display module and an OLED display module; the threshold is set through the computer program according to the actual application scenario.

[0042] S250. Real-time monitor the types and concentrations of the food pathogenic bacteria through a human-computer interaction terminal, and allow the user to remotely control the display and warning unit; The human-computer interaction terminal includes at least one of a smart phone, a computer, and a smart watch, and realizes data transmission and instruction interaction with the food pathogenic bacteria intelligent detection device through the communication module.

[0043] Embodiment 4 Optionally, please refer to Figure 4 , Figure 4 which is the structural unit composition diagram of the first food pathogenic bacteria intelligent detection device based on dual-modal sensing fusion provided by the embodiment of the present invention, specifically: The metabolic VOCs are actively collected by the micro air pump and micro fan in the metabolic VOCs collection unit and supplied to the dual - mode sensing unit; the metabolic VOCs are detected by the dual - mode sensing unit, the electrical signal acquisition module processes and outputs the electrical response information of the electrical sensor, and the camera module converts the color change of the colorimetric sensor into digital information and outputs it; the temperature, humidity, air pressure and light intensity parameters are obtained and output by the temperature and humidity sensing module, air pressure sensing module and light sensing module in the environmental parameter collection unit; the types and concentrations of food pathogenic bacteria are obtained by analyzing and processing the electrical response, color change, temperature, humidity, air pressure and light intensity information through the computer programs and algorithms stored in the intelligent processing unit; the types and concentrations of food pathogenic bacteria are displayed in real - time by the OLED display module in the display and warning unit, and if the concentration exceeds the threshold set by the computer program, sound and light warning are carried out; wireless communication with a smart phone is realized through the WiFi module in the intelligent processing unit to monitor the types and concentrations of food pathogenic bacteria in real - time and allow users to remotely control the display and warning functions.

[0044] Embodiment 5 Optionally, please refer to Figure 5 , Figure 5 is the structural unit composition diagram of the second intelligent food pathogenic bacteria detection device based on dual - mode sensing fusion provided by the embodiment of the present invention, specifically: The metabolic VOCs are actively collected by the micro air pump and micro fan in the metabolic VOCs collection unit and supplied to the dual - mode sensing unit; the metabolic VOCs are detected by the dual - mode sensing unit, the electrical signal acquisition module processes and outputs the electrical response information of the electrical sensor, and the camera module converts the color change of the colorimetric sensor into digital information and outputs it; the temperature, humidity, air pressure and light intensity parameters are obtained and output by the temperature and humidity sensing module, air pressure sensing module and light sensing module in the environmental parameter collection unit; the types and concentrations of food pathogenic bacteria are obtained by analyzing and processing the electrical response, color change, temperature, humidity, air pressure and light intensity information through the computer programs and algorithms stored in the intelligent processing unit; the types and concentrations of food pathogenic bacteria are displayed in real - time by the LCD display module in the display and warning unit, and if the concentration exceeds the threshold set by the computer program, sound and light warning are carried out; wireless communication with a smart watch is realized through the WiFi module in the intelligent processing unit to monitor the types and concentrations of food pathogenic bacteria in real - time and allow users to remotely control the display and warning functions.

[0045] Embodiment 6 Optionally, please refer to Figure 6 , Figure 6 is the structural unit composition diagram of the third intelligent food pathogenic bacteria detection device based on dual - mode sensing fusion provided by the embodiment of the present invention, specifically: The micro air pump and micro fan in the metabolic VOCs collection unit are used to actively collect the metabolic VOCs and supply them to the dual - mode sensing unit; the dual - mode sensing unit is used to detect the metabolic VOCs, the electrical signal acquisition module processes and outputs the electrical response information of the electrical sensor, and the color sensor module converts the color change of the colorimetric sensor into digital information and outputs it; the temperature and humidity sensing module, air pressure sensing module and light sensing module of the environmental parameter collection unit are used to obtain and output the parameters of temperature, humidity, air pressure and light intensity; the computer program and algorithm stored in the intelligent processing unit are used to analyze and process the electrical response, color change, temperature, humidity, air pressure and light intensity information to obtain the types and concentrations of food - borne pathogenic bacteria; the LCD display module in the display and warning unit is used to display the types and concentrations of food - borne pathogenic bacteria in real time. If the concentration exceeds the threshold set by the computer program, acoustic and optical warnings will be given; the Bluetooth module in the intelligent processing unit is used to achieve wireless communication with the computer, monitor the types and concentrations of food - borne pathogenic bacteria in real time, and allow users to remotely control the display and warning functions.

Claims

1. An intelligent detection method for food pathogenic bacteria based on bimodal sensing fusion, characterized in that, This innovative approach integrates the advantages of electrical and colorimetric dual-modal sensing to collaboratively detect volatile organic compounds (VOCs) metabolized by food pathogens. A dual-modal detection fusion model is constructed. A compensation algorithm is used to eliminate interference from environmental factors, and an artificial intelligence algorithm is used to achieve reliable detection of food pathogens. The specific steps include: (1) Obtaining electrical response and color change information generated by detecting VOCs metabolized by food pathogens using electrical and colorimetric sensors; (2) Obtain environmental parameters including temperature, humidity, air pressure and light intensity; (3) inputting the environmental parameters into a compensation algorithm to calibrate the electrical response and color change information; (4) fusing the calibrated electrical response and color change information to form a high-dimensional feature vector; (5) Inputting the high-dimensional feature vector into an artificial intelligence algorithm to output the identification results and concentrations of food pathogens.

2. The intelligent detection method of food pathogenic bacteria based on bimodal sensing fusion according to claim 1, wherein, The electrical sensor includes at least one gas-sensitive element made of a sensitive material; the colorimetric sensor includes at least one colorimetric film element made of a sensitive material; and the electrical response information includes at least one of resistance, capacitance, frequency, voltage and current.

3. The intelligent detection method for food pathogenic bacteria based on bimodal sensing fusion according to claim 1, characterized in that, The food pathogens include but are not limited to Escherichia coli, Salmonella, Staphylococcus aureus, Listeria monocytogenes, Pseudomonas aeruginosa, Shigella and Vibrio parahaemolyticus.

4. The intelligent detection method for food pathogenic bacteria based on bimodal sensing fusion according to claim 1, wherein, The compensation algorithm constructs a mathematical mapping relationship between the environmental parameters and the electrical response and color change information, uses a polynomial regression algorithm to quantify the influence weight of each environmental parameter, and performs error correction and calibration on the electrical response and color change information. The artificial intelligence algorithm uses a deep learning model based on a convolutional neural network architecture, which includes at least three convolutional layers and a fully connected layer. The convolutional and fully connected layers perform layer-by-layer feature extraction on the input high-dimensional feature vector. Furthermore, based on the extracted key features, the classification task is used to identify the types of food pathogens, and the regression task is used to predict the concentration of food pathogens.

5. An intelligent detection device for food pathogenic bacteria based on bimodal sensing fusion, characterized in that, It includes a metabolic VOCs collection unit, a dual-modal sensing unit, an environmental parameter collection unit, a display and warning unit, an intelligent processing unit, and a human-computer interaction terminal, including: The metabolic VOCs collection unit includes a micro air pump, a micro fan, a relay, and a relay module circuit composed of multiple resistors and capacitors, which is used to actively collect the metabolic VOCs of food pathogens and supply them to the dual-mode sensing unit for detection; The dual-modal sensing unit is connected to the metabolic VOCs acquisition unit and the intelligent processing unit, and includes an electrical sensor, an electrical signal acquisition module, a colorimetric sensor, and a color change acquisition module, for detecting the metabolic VOCs of the food pathogens to obtain electrical response and color change information; The environmental parameter acquisition unit is connected to the intelligent processing unit and includes a temperature and humidity sensing module, an air pressure sensing module and a light sensing module for acquiring temperature, humidity, air pressure and light intensity parameters; The display and warning unit is connected to the intelligent processing unit and includes a display module and an audio-visual warning module for displaying and warning the user of the type and concentration of the food pathogens; The human-computer interaction terminal is used to monitor the types and concentrations of the food pathogenic bacteria in real time and allows the user to remotely control the display and warning unit; The intelligent processing unit includes a communication module, a memory, a processor, and computer programs and algorithms stored on the memory and executable on the processor, and is used to coordinate and control the operation and function implementation of the intelligent food pathogenic bacteria detection device.

6. The intelligent detection device for food pathogenic bacteria based on bimodal sensing fusion according to claim 5, wherein The electrical signal acquisition module is connected to the electrical sensor and includes an operational amplifier, a reference voltage circuit composed of multiple resistors and capacitors, and a filtering circuit, and is used to process the electrical response of the electrical sensor; the color change acquisition module is connected to the colorimetric sensor and includes at least one of a camera module and a color sensor module, and is used to convert the color change of the colorimetric sensor into digital information.

7. An intelligent detection device for food pathogenic bacteria based on dual-modal sensing fusion according to claim 5, characterized in that: The display module includes at least one of an LCD display module and an OLED display module; the human-computer interaction terminal includes at least one of a smart phone, a computer, and a smart watch; the communication module supports wireless communication technology and is used to realize data transmission and instruction interaction between the intelligent food pathogenic bacteria detection device and the human-computer interaction terminal.

8. An intelligent detection device for food pathogenic bacteria based on dual-modal sensing fusion according to claim 5, characterized in that, When the computer programs and algorithms are executed by the processor, the steps and functions of the intelligent food pathogenic bacteria detection method based on dual-modal sensing fusion according to any one of claims 1 to 4 can be realized.

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