A laying hen house environment monitoring method and system based on a multi-sensor data source

Abstract

The application belongs to the technical field of sensors, and provides an egg chicken house environment monitoring method and system based on a multi-sensor data source, the main scheme of which is: obtaining initial configuration information of an egg chicken house, and determining initial breeding densities of each cage based on the initial configuration information; taking each cage as an initial monitoring node, and obtaining first monitoring data and a first monitoring time of a sensor used for monitoring the initial monitoring node; obtaining a dynamic monitoring node based on the first monitoring data and the first monitoring time; assigning a dynamic weight to a sensor used for monitoring the dynamic monitoring node, and obtaining second monitoring data and a second monitoring time of the sensor used for monitoring the dynamic monitoring node based on the dynamic weight; and generating first prompt information for prompting adjustment of the initial breeding densities of each cage, second prompt information for prompting adjustment of air volume, and third prompt information for prompting adjustment of light intensity based on the first monitoring data and the second monitoring data.

Description

Technical Field

[0001] This invention relates to the field of sensor technology, and in particular to a method and system for monitoring the environment of laying hen houses based on multiple sensor data sources. Background Technology

[0002] Egg-laying hen houses are specifically designed for egg-laying hen farming. Raising hens in these houses facilitates their growth and makes manual egg collection easier. Because the structure of egg-laying hen houses is already very common, monitoring programs for these houses have been proposed and implemented to better control the health of the hens and improve their egg production efficiency.

[0003] Currently, monitoring solutions for laying hen houses, such as the patent application with application number CN202411215970.3, disclose an intelligent chicken house environmental concentration monitoring system. This system mainly uses sensor modules to collect various environmental parameters in the chicken house and transmits the collected data to a data acquisition module. The data acquisition module receives the data from the sensor modules, preprocesses the data, and then uploads the preprocessed data to the data processing module through the data transmission module. The data processing module analyzes and processes the data, transforming the collected raw data into useful information that the breeder can understand.

[0004] Although, as the aforementioned patent application points out, it is possible to obtain the model parameters by fitting the model to historical data, which can be used to predict the impact of changes in environmental parameters in chicken coops on chicken farming in different seasons, the simultaneous collection of multiple environmental parameters by sensors to detect environmental anomalies in a timely manner and take corresponding measures will frequently trigger alarm information, prompting on-site staff to adjust relevant environmental parameters. Moreover, in many cases, due to the time delay and inherent error of sensor data collection, the judgment of environmental anomalies may be inaccurate, resulting in higher labor and hardware costs. Summary of the Invention

[0005] The purpose of this invention is to provide a method and system for monitoring the environment of laying hen houses based on multiple sensor data sources. This system can accurately alert to abnormal conditions in laying hen houses through a two-level judgment mechanism based on first and second monitoring data, and will not issue frequent alerts due to system errors caused by a single sensor.

[0006] The technical solution adopted by this invention to solve its technical problem is as follows:

[0007] On the one hand, the present invention provides a method for monitoring the environment of laying hen houses based on multi-sensor data sources, including the following steps:

[0008] Obtain the initial configuration information of the laying hen house, and determine the initial stocking density of each cage based on the initial configuration information;

[0009] Each chicken cage is used as an initial monitoring node, and the first monitoring data and the first monitoring time of the sensor used to monitor the initial monitoring node are obtained;

[0010] Dynamic monitoring nodes are obtained based on the first monitoring data and the first monitoring time.

[0011] Dynamic weights are assigned to sensors used to monitor dynamic monitoring nodes, and second monitoring data and second monitoring time of the sensors used to monitor dynamic monitoring nodes are obtained based on the dynamic weights.

[0012] Based on the first and second monitoring data, the system generates a first prompt message to adjust the initial stocking density of each chicken cage, a second prompt message to adjust the air volume, and a third prompt message to adjust the light intensity.

[0013] As a further optimization, the initial configuration information of the layer chicken house includes the location information of the ventilation openings, the location information of the lighting openings, the location information of each chicken cage, and the installation location information of each type of sensor.

[0014] The various types of sensors include at least: temperature sensors, humidity sensors, airflow monitoring sensors, light sensors, ammonia sensors, carbon dioxide sensors, and image sensors.

[0015] As a further optimization, before acquiring the first monitoring data and the first monitoring time from the sensor used to monitor the initial monitoring node, the method further includes:

[0016] The threshold values ​​for each sensor data of the corresponding initial monitoring node are determined based on the initial configuration information of the laying hen house.

[0017] As a further optimization, the acquisition of the first monitoring data and the first monitoring time from the sensor used to monitor the initial monitoring node includes:

[0018] A first processor and a first memory are set up on-site in the laying hen house, and the first memory stores the sensor data thresholds of each of the determined initial monitoring nodes.

[0019] The first monitoring time of each initial monitoring node is set in the first processor, and the first transmission interval of the signals of each type of sensor used to monitor the current initial monitoring node is unified.

[0020] During the first monitoring period, the first processor receives real-time monitoring data and real-time monitoring time from various types of sensors used to monitor each initial monitoring node.

[0021] Based on real-time monitoring data, it is determined whether the sensor data has reached the corresponding sensor data threshold. If it has not reached the threshold, the real-time monitoring data that has not reached the sensor data threshold is stored in the first memory.

[0022] As a further optimization, when installing the first processor and the first memory on-site in the laying hen house, it also includes:

[0023] A second processor and a second memory are installed on-site in the egg-laying hen house;

[0024] When the sensor data reaches the corresponding sensor data threshold, the real-time monitoring data that has reached the sensor data threshold is stored in the second memory and the second processor is notified.

[0025] As a further optimization, when the second processor receives a notification from the second memory, it obtains a dynamic monitoring node based on the first monitoring data and the first monitoring time.

[0026] The acquisition of dynamic monitoring nodes based on the first monitoring data and the first monitoring time refers to:

[0027] Query the real-time monitoring data in the first and second memories, filter and confirm the type and installation location information of the sensors that have reached the sensor data threshold in the second memory;

[0028] For the sensors that have been screened and confirmed, the sensors are grouped according to the difference range of the sensor data thresholds;

[0029] Sensors within the same group are used as dynamic monitoring nodes.

[0030] As a further optimization, assigning dynamic weights to sensors used for monitoring dynamic monitoring nodes refers to:

[0031] Obtain the number of times the sensor data threshold is reached within the same group, and use it as the first weight;

[0032] Assign a first weight coefficient to the first weight;

[0033] Obtain the farthest distance between two sensors of the same type within the same group, filter out the sensor type with the largest farthest distance, and use the farthest distance between two sensors of that type as the second weight;

[0034] Assign a second weight coefficient to the second weight;

[0035] The dynamic weight is the sum of the first weight multiplied by the first weight coefficient and the second weight multiplied by the second weight coefficient.

[0036] As a further optimization, the acquisition of the second monitoring data and the second monitoring time of the sensor used to monitor the dynamic monitoring node based on dynamic weights refers to:

[0037] Set the second monitoring time for the dynamic monitoring node and unify the second signal transmission interval for monitoring the various types of sensors of the current dynamic monitoring node;

[0038] During the second monitoring period, the second processor receives real-time monitoring data and real-time monitoring time from various types of sensors used to monitor each dynamic monitoring node.

[0039] Based on dynamic weights, real-time monitoring data from corresponding types of sensors are fused from multiple sources, and the fused data is used as the second monitoring data and stored in the second memory.

[0040] As a further optimization, the first prompt message for adjusting the initial stocking density of each chicken cage, the second prompt message for adjusting the air volume, and the third prompt message for adjusting the light intensity, generated based on the first and second monitoring data, refer to:

[0041] Based on the first monitoring data, real-time monitoring data that reaches the sensor data threshold is acquired, as well as the first activity frequency information, first wind volume information, and first light intensity information of the target to be monitored within the initial monitoring node;

[0042] When the first activity frequency and / or the first air volume information and / or the first light intensity information reach the corresponding first preset value, a first prompt message and / or a second prompt message and / or a third prompt message are generated.

[0043] When at least two types of prompts are generated, the second monitoring data is obtained based on the real-time monitoring data that has reached the sensor data threshold.

[0044] Based on the second monitoring data, obtain the second activity frequency information, second wind volume information and second light intensity information of the target to be monitored in the dynamic monitoring section;

[0045] When the second activity frequency and / or the second air volume information and / or the second light intensity information reach the corresponding second preset value, a first prompt message and / or a second prompt message and / or a third prompt message are generated.

[0046] When a first prompt message and / or a second prompt message and / or a third prompt message are generated based on both the first monitoring data and the second monitoring data, the first prompt message and / or the second prompt message and / or the third prompt message are sent to the management terminal.

[0047] On the other hand, the present invention also provides a multi-sensor data source-based environmental monitoring system for layer hen houses, applied to the aforementioned multi-sensor data source-based environmental monitoring method for layer hen houses, comprising:

[0048] The information configuration unit is used to obtain the initial configuration information of the laying hen house and determine the initial stocking density of each cage based on the initial configuration information.

[0049] The first monitoring unit; the first data uses each chicken cage as an initial monitoring node and acquires the first monitoring data and the first monitoring time from the sensors used to monitor the initial monitoring nodes;

[0050] The second monitoring unit is used to obtain dynamic monitoring nodes based on the first monitoring data and the first monitoring time, assign dynamic weights to the sensors used to monitor the dynamic monitoring nodes, and obtain the second monitoring data and the second monitoring time of the sensors used to monitor the dynamic monitoring nodes based on the dynamic weights.

[0051] The prompt information generation unit is used to generate, based on the first monitoring data and the second monitoring data, a first prompt information for adjusting the initial stocking density of each chicken cage, a second prompt information for adjusting the air volume, and a third prompt information for adjusting the light intensity.

[0052] The beneficial effects of this invention are: by setting initial monitoring nodes and dynamic monitoring nodes, and by using the comprehensive judgment of the first monitoring data and the second monitoring data, this invention can accurately know the specific locations in the laying hen house where the stocking density, air volume and light need to be adjusted. This avoids the misjudgment of abnormal conditions in the laying hen house in traditional laying hen house environmental monitoring schemes, and will not generate frequency alarm prompts, thus avoiding the problem of reduced production capacity due to excessive human intervention. Attached Figure Description

[0053] Figure 1 This is a flowchart of a method for monitoring the environment of a layer hen house based on multiple sensor data sources, as described in Embodiment 1 of the present invention.

[0054] Figure 2 This is a schematic diagram of the composition structure of an environmental monitoring system for laying hens based on a multi-sensor data source, as shown in Embodiment 2 of the present invention. Detailed Implementation

[0055] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, 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. The components of the embodiments of the present invention described and shown in the accompanying drawings can generally be arranged and designed in various different configurations.

[0056] Example 1

[0057] This embodiment provides a method for monitoring the environment of a layer hen house based on multiple sensor data sources. See the flowchart below. Figure 1 The method includes the following steps:

[0058] S1. Obtain the initial configuration information of the laying hen house and determine the initial stocking density of each cage based on the initial configuration information;

[0059] S2. Take each chicken cage as an initial monitoring node, and acquire the first monitoring data and the first monitoring time of the sensor used to monitor the initial monitoring node;

[0060] S3. Obtain dynamic monitoring nodes based on the first monitoring data and the first monitoring time;

[0061] S4. Assign dynamic weights to the sensors used to monitor the dynamic monitoring nodes, and obtain the second monitoring data and the second monitoring time of the sensors used to monitor the dynamic monitoring nodes based on the dynamic weights.

[0062] S5. Based on the first and second monitoring data, generate a first prompt message to adjust the initial stocking density of each chicken cage, a second prompt message to adjust the air volume, and a third prompt message to adjust the light intensity.

[0063] In this embodiment, the initial configuration information of the layer hen house can generally be confirmed after the house is built. However, if on-site equipment (such as chicken cages or sensors) requires manual intervention for maintenance, repair, or replacement during daily operation, the configuration parameters after maintenance or repair will be used as the basis for subsequent steps. Although layer hen houses can be divided into various types such as open and closed houses, once confirmed, the initial stocking density in the cages can be determined. Therefore, in this embodiment, it is first necessary to confirm the initial configuration information of the layer hen house and the initial stocking density of each cage to guide the subsequent adjustment of stocking density and other on-site equipment parameters.

[0064] Generally, many factors can affect the productivity of a layer hen house. However, the main factors are usually ventilation, lighting, and stocking density in each cage. Therefore, in this embodiment, the initial information to be obtained for the layer hen house should at least include the location information of the ventilation openings, lighting openings, the location information of each cage, and the installation location information of each type of sensor. Correspondingly, layer hen houses are generally equipped with various types of sensors to effectively monitor different areas within the house. Therefore, in this embodiment, the various types of sensors should at least include: temperature sensors, humidity sensors, airflow monitoring sensors, lighting sensors, ammonia sensors, carbon dioxide sensors, and image sensors.

[0065] It should be noted that there are various types of data sensed by different types of sensors in the laying hen house, resulting in inconsistent data sizes to be processed after sensing corresponding data by different sensors. Some data are small, such as temperature data, while others are large, such as image sensor data. At the same time, the transmission latency from different types of sensors to the processor is also different. Therefore, if we want to accurately determine the area in the laying hen house that needs to be warned using the two-level determination mechanism in this embodiment, we need to limit the sensor data thresholds. Therefore, in this embodiment, before obtaining the first monitoring data and the first monitoring time of the sensor used to monitor the initial monitoring node, it should also include: determining the sensor data thresholds of each corresponding initial monitoring node based on the initial configuration information of the laying hen house.

[0066] Specifically, in this embodiment, each chicken cage is first used as an initial monitoring node, and then dynamic monitoring nodes are determined. After each chicken cage is used as an initial monitoring node, its corresponding first monitoring data and first monitoring time also need to be comprehensively judged. For sensors above the sensing data threshold, if abnormal monitoring data occurs at the corresponding monitored location, a first alert message needs to be generated. After that, the second monitoring data is used to determine whether a second alert message should be generated. If generated, an alert message is sent to the on-site management terminal, thereby achieving a precise alarm function. Therefore, in this embodiment, obtaining the first monitoring data and first monitoring time of the sensor used to monitor the initial monitoring node may include:

[0067] A first processor and a first memory are set up on-site in the laying hen house, and the first memory stores the sensor data thresholds of each of the determined initial monitoring nodes.

[0068] The first monitoring time of each initial monitoring node is set in the first processor, and the first transmission interval of the signals of each type of sensor used to monitor the current initial monitoring node is unified.

[0069] During the first monitoring period, the first processor receives real-time monitoring data and real-time monitoring time from various types of sensors used to monitor each initial monitoring node.

[0070] Based on real-time monitoring data, it is determined whether the sensor data has reached the corresponding sensor data threshold. If it has not reached the threshold, the real-time monitoring data that has not reached the sensor data threshold is stored in the first memory.

[0071] Here, because different sensor data have different sizes, the processing delay of the processor when processing these sensor data of different sizes also varies. Therefore, in order to solve the data processing pressure and data storage pressure caused by too many sensors being deployed on-site in the laying hen house, this embodiment sets up a first processor, a first memory, a second processor, and a second memory.

[0072] Therefore, in this embodiment, when the first processor and the first memory are installed on-site in the laying hen house, the following additional components are also required:

[0073] A second processor and a second memory are installed on-site in the egg-laying hen house;

[0074] When the sensor data reaches the corresponding sensor data threshold, the real-time monitoring data that has reached the sensor data threshold is stored in the second memory and the second processor is notified.

[0075] In practical applications, to achieve accurate two-level judgment and avoid false alarms from a single sensor, this embodiment requires the following: when the second processor receives a notification from the second memory, it acquires dynamic monitoring nodes based on the first monitoring data and the first monitoring time. Specifically, acquiring dynamic monitoring nodes based on the first monitoring data and the first monitoring time means: first, querying the real-time monitoring data in the first and second memories, filtering and confirming the type and installation location information of sensors in the second memory that have reached the sensor data threshold; second, grouping the filtered and confirmed sensors according to the difference range of their sensor data thresholds; and then, using the sensors in the same group as dynamic monitoring nodes.

[0076] It should be noted that the setting of dynamic weights depends on the monitoring results of each sensor at the initial monitoring node. Since the initial monitoring node is each chicken cage, and once the layer hen house is selected, the chicken cages within the layer hen house are fixed. Therefore, if only the chicken cage is used as a single monitoring unit, accurate alarm function cannot be achieved, and frequent false alarms from individual sensors may require manual intervention. Therefore, this embodiment also requires the selection of dynamic nodes. Before selecting dynamic nodes, it is necessary to consider the monitoring results of the initial monitoring node. If some sensors frequently reach their corresponding sensor thresholds, it indicates that the corresponding monitoring location may need to have its ventilation, lighting, or stocking density changed. Therefore, in this embodiment, assigning dynamic weights to the sensors used to monitor the dynamic monitoring nodes means:

[0077] Obtain the number of times the sensor data threshold is reached within the same group, and use it as the first weight;

[0078] Assign a first weight coefficient to the first weight;

[0079] Obtain the farthest distance between two sensors of the same type within the same group, filter out the sensor type with the largest farthest distance, and use the farthest distance between two sensors of that type as the second weight;

[0080] Assign a second weight coefficient to the second weight;

[0081] The dynamic weight is the sum of the first weight multiplied by the first weight coefficient and the second weight multiplied by the second weight coefficient.

[0082] Here, although the first weight represents the number of times and the second weight represents the distance, a uniform weight coefficient of the same type and proportion can be set to balance the differences between the data and thus obtain accurate dynamic weights. For example, if a temperature sensor in the same group reaches the sensor data threshold 3 times, and the sensor type with the largest distance selected in the same group is an image sensor with a distance of 35m, then in a small-scale egg-laying hen house, the image sensor's farthest image distance is too far. Therefore, the second weight assigned to it should be relatively small to ensure more accurate dynamic weights. In this case, the second weight coefficient can be assigned to 0.2, and the first weight coefficient can be assigned to 0.8.

[0083] It should be noted that, since the types and number of sensors deployed on-site in the laying hen house may be quite large, in order to reduce data processing latency and pressure, this embodiment requires storing monitoring data that has not reached the sensor data threshold in the first memory and storing monitoring data that has reached the sensor data threshold in the second memory. Furthermore, after selecting a dynamic monitoring node, all sensor data used to monitor that node is stored in the second memory. Therefore, in this embodiment, obtaining the second monitoring data and the second monitoring time of the sensors used to monitor the dynamic monitoring node based on dynamic weights refers to:

[0084] Set the second monitoring time for the dynamic monitoring node and unify the second signal transmission interval for monitoring the various types of sensors of the current dynamic monitoring node;

[0085] During the second monitoring period, the second processor receives real-time monitoring data and real-time monitoring time from various types of sensors used to monitor each dynamic monitoring node.

[0086] Based on dynamic weights, real-time monitoring data from corresponding types of sensors are fused from multiple sources, and the fused data is used as the second monitoring data and stored in the second memory.

[0087] Even though the sensors have been grouped before, each sensor in the same group is likely to contain multiple sensors of different types. Therefore, in this embodiment, when the second processor processes the monitoring data of the dynamic monitoring nodes, it is necessary to perform multi-source data fusion in order to accurately determine the specific location in the laying hen house that needs to be alarmed.

[0088] In practical applications, since this embodiment generates two prompt messages before finally confirming and sending an alarm to the on-site management terminal to prompt relevant personnel to adjust the airflow and / or lighting and / or stocking density at specific locations, in this embodiment, the generation of the first prompt message to adjust the initial stocking density of each chicken cage, the second prompt message to adjust the airflow, and the third prompt message to adjust the lighting intensity based on the first and second monitoring data refers to:

[0089] Based on the first monitoring data, real-time monitoring data that reaches the sensor data threshold is acquired, as well as the first activity frequency information, first wind volume information, and first light intensity information of the target to be monitored within the initial monitoring node;

[0090] When the first activity frequency and / or the first air volume information and / or the first light intensity information reach the corresponding first preset value, a first prompt message and / or a second prompt message and / or a third prompt message are generated.

[0091] When at least two types of prompts are generated, the second monitoring data is obtained based on the real-time monitoring data that has reached the sensor data threshold.

[0092] Based on the second monitoring data, obtain the second activity frequency information, second wind volume information and second light intensity information of the target to be monitored in the dynamic monitoring section;

[0093] When the second activity frequency and / or the second air volume information and / or the second light intensity information reach the corresponding second preset value, a first prompt message and / or a second prompt message and / or a third prompt message are generated.

[0094] When a first prompt message and / or a second prompt message and / or a third prompt message are generated based on both the first monitoring data and the second monitoring data, the first prompt message and / or the second prompt message and / or the third prompt message are sent to the management terminal.

[0095] Example 2

[0096] Based on Example 1, this example provides an environmental monitoring system for layer hen houses based on multi-sensor data sources. See the schematic diagram of its structure. Figure 2 The system includes:

[0097] The information configuration unit is used to obtain the initial configuration information of the laying hen house and determine the initial stocking density of each cage based on the initial configuration information.

[0098] The first monitoring unit; the first data uses each chicken cage as an initial monitoring node and acquires the first monitoring data and the first monitoring time from the sensors used to monitor the initial monitoring nodes;

[0099] The second monitoring unit is used to obtain dynamic monitoring nodes based on the first monitoring data and the first monitoring time, assign dynamic weights to the sensors used to monitor the dynamic monitoring nodes, and obtain the second monitoring data and the second monitoring time of the sensors used to monitor the dynamic monitoring nodes based on the dynamic weights.

[0100] The prompt information generation unit is used to generate, based on the first monitoring data and the second monitoring data, a first prompt information for adjusting the initial stocking density of each chicken cage, a second prompt information for adjusting the air volume, and a third prompt information for adjusting the light intensity.

[0101] As can be seen from the description of Embodiment 1, the application scenario and implementation principle of this embodiment are the same as those of Embodiment 1, so they will not be repeated here.

[0102] The above are merely preferred embodiments of the present invention and are not intended to limit the present invention. Various modifications and variations can be made to the present invention by those skilled in the art. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the scope of protection of the present invention.

Claims

1. A method for monitoring the environment of a layer hen house based on multiple sensor data sources, characterized in that, Includes the following steps: Obtain the initial configuration information of the laying hen house, and determine the initial stocking density of each cage based on the initial configuration information; Each chicken cage is used as an initial monitoring node, and the first monitoring data and the first monitoring time of the sensor used to monitor the initial monitoring node are obtained; The process of obtaining dynamic monitoring nodes based on first monitoring data and first monitoring time refers to: Query the real-time monitoring data in the first and second memories, filter and confirm the type and installation location information of the sensors that have reached the sensor data threshold in the second memory; For the sensors that have been screened and confirmed, the sensors are grouped according to the difference range of the sensor data thresholds; Sensors within the same group are used as dynamic monitoring nodes; Assigning dynamic weights to sensors used for monitoring dynamic monitoring nodes, and obtaining second monitoring data and second monitoring time of the sensors used for monitoring dynamic monitoring nodes based on the dynamic weights, wherein assigning dynamic weights to sensors used for monitoring dynamic monitoring nodes refers to: Obtain the number of times the sensor data threshold is reached within the same group, and use it as the first weight; Assign a first weight coefficient to the first weight; Obtain the farthest distance between two sensors of the same type within the same group, filter out the sensor type with the largest farthest distance, and use the farthest distance between two sensors of that type as the second weight; Assign a second weight coefficient to the second weight; The sum of the first weight multiplied by the first weight coefficient and the second weight multiplied by the second weight coefficient is used as the dynamic weight. Based on the first and second monitoring data, the system generates a first prompt message to adjust the initial stocking density of each chicken cage, a second prompt message to adjust the air volume, and a third prompt message to adjust the light intensity.

2. The method for monitoring the environment of a layer hen house based on multiple sensor data sources according to claim 1, characterized in that, The initial configuration information of the laying hen house includes the location information of the ventilation openings, the location information of the light outlets, the location information of each chicken cage, and the installation location information of each type of sensor. The various types of sensors include at least: temperature sensors, humidity sensors, airflow monitoring sensors, light sensors, ammonia sensors, carbon dioxide sensors, and image sensors.

3. The method for monitoring the environment of a layer hen house based on multiple sensor data sources according to claim 2, characterized in that, Before acquiring the first monitoring data and the first monitoring time from the sensor used to monitor the initial monitoring node, the method further includes: The threshold values ​​for each sensor data of the corresponding initial monitoring node are determined based on the initial configuration information of the laying hen house.

4. The method for monitoring the environment of a layer hen house based on a multi-sensor data source according to claim 3, characterized in that, The acquisition of the first monitoring data and the first monitoring time from the sensor used to monitor the initial monitoring node includes: A first processor and a first memory are set up at the egg-laying hen house, and the determined sensor data thresholds corresponding to the initial monitoring nodes are stored in the first memory. The first monitoring time of each initial monitoring node is set in the first processor, and the first transmission interval of the signals of each type of sensor used to monitor the current initial monitoring node is unified. During the first monitoring period, the first processor receives real-time monitoring data and real-time monitoring time from various types of sensors used to monitor each initial monitoring node. Based on real-time monitoring data, it is determined whether the sensor data has reached the corresponding sensor data threshold. If it has not reached the threshold, the real-time monitoring data that has not reached the sensor data threshold is stored in the first memory.

5. The method for monitoring the environment of a layer hen house based on a multi-sensor data source according to claim 4, characterized in that, When installing the first processor and the first memory on-site in the laying hen house, it also includes: A second processor and a second memory are installed on-site in the egg-laying hen house; When the sensor data reaches the corresponding sensor data threshold, the real-time monitoring data that has reached the sensor data threshold is stored in the second memory and the second processor is notified.

6. The method for monitoring the environment of a layer hen house based on a multi-sensor data source according to claim 5, characterized in that, When the second processor receives a notification from the second memory, it acquires the dynamic monitoring node based on the first monitoring data and the first monitoring time.

7. The method for monitoring the environment of a layer hen house based on a multi-sensor data source according to claim 5, characterized in that, The acquisition of the second monitoring data and the second monitoring time of the sensor used to monitor the dynamic monitoring node based on dynamic weights refers to: Set the second monitoring time for the dynamic monitoring node and unify the second signal transmission interval for monitoring the various types of sensors of the current dynamic monitoring node; During the second monitoring period, the second processor receives real-time monitoring data and real-time monitoring time from various types of sensors used to monitor each dynamic monitoring node. Based on dynamic weights, real-time monitoring data from corresponding types of sensors are fused from multiple sources, and the fused data is used as the second monitoring data and stored in the second memory.

8. A method for monitoring the environment of a layer hen house based on a multi-sensor data source according to claim 7, characterized in that, The first prompt message for adjusting the initial stocking density of each chicken cage, the second prompt message for adjusting the air volume, and the third prompt message for adjusting the light intensity, generated based on the first and second monitoring data, refer to: Based on the first monitoring data, real-time monitoring data that reaches the sensor data threshold is acquired, as well as the first activity frequency information, first wind volume information, and first light intensity information of the target to be monitored within the initial monitoring node; When the first activity frequency and / or the first air volume information and / or the first light intensity information reach the corresponding first preset value, a first prompt message and / or a second prompt message and / or a third prompt message are generated. When at least two types of prompts are generated, the second monitoring data is obtained based on the real-time monitoring data that has reached the sensor data threshold. Based on the second monitoring data, obtain the second activity frequency information, second wind volume information and second light intensity information of the target to be monitored in the dynamic monitoring section; When the second activity frequency and / or the second air volume information and / or the second light intensity information reach the corresponding second preset value, a first prompt message and / or a second prompt message and / or a third prompt message are generated. When a first prompt message and / or a second prompt message and / or a third prompt message are generated based on both the first monitoring data and the second monitoring data, the first prompt message and / or the second prompt message and / or the third prompt message are sent to the management terminal.

9. A multi-sensor data source-based environmental monitoring system for layer hen houses, applied to the multi-sensor data source-based environmental monitoring method for layer hen houses as described in any one of claims 1-8, characterized in that, include: The information configuration unit is used to obtain the initial configuration information of the laying hen house and determine the initial stocking density of each cage based on the initial configuration information. First monitoring unit; The first data uses each chicken cage as an initial monitoring node and acquires the first monitoring data and the first monitoring time from the sensors used to monitor the initial monitoring nodes. The second monitoring unit is used to acquire dynamic monitoring nodes based on the first monitoring data and the first monitoring time, assign dynamic weights to the sensors used to monitor the dynamic monitoring nodes, and acquire the second monitoring data and the second monitoring time of the sensors used to monitor the dynamic monitoring nodes based on the dynamic weights. Acquiring dynamic monitoring nodes based on the first monitoring data and the first monitoring time means: Query the real-time monitoring data in the first and second memories, filter and confirm the type and installation location information of the sensors that have reached the sensor data threshold in the second memory; For the sensors that have been screened and confirmed, the sensors are grouped according to the difference range of the sensor data thresholds; Sensors within the same group are used as dynamic monitoring nodes; Assigning dynamic weights to sensors used for monitoring dynamic monitoring nodes refers to: Obtain the number of times the sensor data threshold is reached within the same group, and use it as the first weight; Assign a first weight coefficient to the first weight; Obtain the farthest distance between two sensors of the same type within the same group, filter out the sensor type with the largest farthest distance, and use the farthest distance between two sensors of that type as the second weight; Assign a second weight coefficient to the second weight; The sum of the first weight multiplied by the first weight coefficient and the second weight multiplied by the second weight coefficient is used as the dynamic weight. The prompt information generation unit is used to generate, based on the first monitoring data and the second monitoring data, a first prompt information for adjusting the initial stocking density of each chicken cage, a second prompt information for adjusting the air volume, and a third prompt information for adjusting the light intensity.

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