JP4495192B2 - Insect control plan decision method - Google Patents

Description

  The present invention relates to a method for determining an insecticidal measure.

Conventionally, the present applicant has proposed various inventions regarding insect repellent devices (attracting insect repellent devices) (see, for example, Patent Document 1 or 2).
JP 2002-51681 A Japanese Patent Laid-Open No. 2007-37429

However, when newly constructing food factories, various product factories, supermarkets, warehouses, etc., plan how to prevent flying insects such as flies, mosquitoes and moths. In order to do so, in response to the surrounding environmental factors such as the newly constructed food factories and weather conditions, etc., any of multiple types of insect repellent devices (attracting insect trap devices) and how many units per unit area Each one relied on human intuition and experience to decide if it was reasonable to install them.
Therefore, depending on the person who made the insect control measures, the type, performance, and number of installed insect repellent devices (attracting insect repellent devices) are excessive quality and the cost is high. There were cases where problems such as insects mixing into chemicals occurred.
Therefore, the present invention aims to provide a method (system) for performing necessary and sufficient insect repellent measures with appropriate quality (level) and cost in response to environmental factors of facilities (buildings, etc.) to be protected against insect repellents. To do.

In order to achieve the above object, the method for determining an insect repellent measure according to the present invention includes a risk point storage step for inputting and storing a risk point indicating the possibility of flying insects for each of a plurality of environmental factors, and ,
A possible insect storage process for identifying a possible insect for each environmental factor and inputting it to a computer for storage;
Insect group classification storage process in which a large number of insects are classified into a plurality of insect groups corresponding to the severity, and stored in a computer,
Insect control plan storage step for pre-inputting and storing the insect control plan corresponding to the combination of each insect group and the total value of the risk points of the survey points to be investigated in the future,
A survey environment factor input process for inputting environmental factors within a predetermined radius around the survey point to a computer;
Summing up the risk points of environmental factors at the survey points,
A possible insect identification step for extracting a possible insect corresponding to the environmental factor of the survey point from the data stored in the potential insect memory step;
An insect group identification step for identifying an insect group based on the data stored in the insect group classification storage step for the specific developable insects extracted in the insect identification step;
Insect control measures corresponding to the combination of the total value of the risk points obtained from the summation step and the insect group specified in the insect group specification step are determined based on the data stored in the insect control measure storage step. And an insect repelling measure plan determining step to be determined.

  The present invention has the following remarkable effects. Regardless of the experience and intuition of conventional people, the type or performance of the optimal insect repellent device (attracting insect repellent device) corresponding to the environmental factors of the survey point --- newly constructed facilities, etc.-reliably and easily And the required number can be determined. In this manner, an appropriate insecticidal measure with an appropriate cost and quality is automatically determined by a small number of inputs.

Hereinafter, the present invention will be described in detail based on the illustrated embodiment.
FIG. 4 is a map 1 showing the surrounding area of the predetermined radius R ₂ centered on the survey point Z, and a single or multiple overlay of a city map, topographic map, and surrounding information map (such as livestock industry and main agricultural products). (Synthesized).

For example, in the map 1 of FIG. 4, the lake 2 exists in the east half, the lakeside line 3 runs north and south, the road 4 also exists along it, the river 5 flows from the west to the east, and the sewage treatment plant 6 It exists in the vicinity of the survey point Z in the southeast direction. A field 7 is also present in the neighborhood, and a bamboo forest 8 and a pine land 9 are also present. 10 is a shrine.
This survey point Z is a point where a building (facility) such as a food factory, various product factories, a supermarket, a warehouse, a hotel, a restaurant, or an apartment building will be built in the future.
The following method (system) determines (determines) what insect repellent measures are required for flying insects.

In FIG. 2, an embodiment of the present invention is shown in a flow chart, and the A process, B process, C process, and D process in FIG. It shows concretely with. In addition, before and after the time of each process A, B, C, and D is in no particular order, and any one is free before and after.
A is a risk point storage step in which risk points P (P ₁ , P ₂ ) indicating the possibility of flying insects being generated for each of a plurality of environmental factors are input to a computer and stored. For example, the settings are made as shown in Table 1 below.

In Table 1 Te at, the 500m distance, (will be described with reference to FIG. 4) a small predetermined radius R ₁ about the survey site Z set to 500m indicate the area within the radius R ₁ In addition, the 1000 m range indicates an annular area surrounded by both radii R ₁ and R ₂ with a large predetermined radius R ₂ set to 1000 m. Of course, a small radius R within ₁ ─── 500 meters distance ─── risk point, rather than the magnitude radius R _2, the annular zone in ───1000m within ─── risk points surrounded formed by R ₁ ,large.
In addition, in forests, paddy fields, and fields, risk points are set in stages according to the area ratio. It can also be seen that rivers are one of the environmental factors that cause many flying insects. The setting of these risk points P ₁ and P ₂ is a numerical value based on a large amount of past measurement (experiment) data.

  In FIG. 1, B is a possible insect storage process in which a possible (flying) insect is identified and input to a computer and stored for each environmental factor such as a river, irrigation channel, paddy field, field, sewage treatment plant, etc. is there. For example, the setting is made as shown in Table 2 below based on a large amount of past measurement (experiment) data.

  C classifies multiple types of insects into multiple insect groups (i) (ii) (iii) (iv) (v) corresponding to severity (also called severity) and stores them in a computer An insect group classification memory process is shown. Here, seriousness (severity) refers to the degree of a problem that occurs when mixed in foods. Table 3 below is arranged in order from the group with the highest severity (seriousness) to the group with the smaller severity.

  D is the total sum of the risk points of the survey point Z where the future survey will be conducted, and the insect control measures corresponding to each insect group (i) (ii) (iii) (iv) (v) combination. An insect-control measure storage process that is input and stored in advance is shown.

  Table 4 below shows the case where the facility (building) built at the survey point Z is a food / product factory, Table 5 shows the case of a super shopping center, and Table 6 shows the case of a warehouse or the like. On the top and bottom of the left end, the total risk point value increases from the bottom to the top, and the risk point total value is differentiated step by step. ~ 35 (points) are displayed as "normal", 36-51 (points) as "high", and 52 (points) or higher as "remarkably high". Insect groups (i) (ii) (iii) (iv) (v) are displayed side by side from the largest to the smallest, and the insect control measures are displayed in the vertical and horizontal crossing frames. Yes.

In Table 4, Table 5, and Table 6, “Super Clean Ecoline” as the above-mentioned insecticidal countermeasure plan is a product name of Ikari Sanitizing Co., Ltd. This refers to a high-performance attracting and catching device equipped with a function that automatically sucks insect dead bodies. “Clean Ecoline Mini” is a product name of Ikari Sanitizing Co., Ltd., and refers to a medium-performance attracting and catching device with similar functions. “Optocrine” is a product name of Ikari Sanitizing Co., Ltd., and refers to a low-performance attracting insect trap device that has an insect light and sticky insect trapping paper but does not have a fan or electric shock killing function. "Optron" is a product name of the company, and is a sheet (insect attracting prevention screen) that closes the important points of facilities such as factories and warehouses so as not to attract and attract the flying insect gathering wavelength range, In Tables 4, 5 and 6, “Optron” is disposed so as to close the entire surface in all frames. Further, in the frame, whether to place the attractant trapping device what m ² high, medium and low for each performance for each of the facilities by one also shown in Table 4, Table 5, the upper left corner of the table 6 It shows that one of the most powerful attracting insect traps should be installed per narrow floor area, and the performance of attracting trap traps gradually decreases from the upper left corner to the lower right corner. In the lower right corner, there will be only “Optron”.
And the anti-insect measures are strictly (high density) in order of Table 6 → Table 5 → Table 4.
Insect control measures illustrated in Table 4, Table 5, and Table 6 (which can also be expressed as a table in this way) are input and stored in advance in a computer in Step D of FIGS.

After the above-described steps A to D are completed, a map of the surrounding area (see FIG. 4) is obtained using the actual construction planned site of various facilities (buildings) as the survey point Z, and FIG. ), The environmental factor within the predetermined radius R ₂ is input to the computer (this will be referred to as “E process”). Specifically, the predetermined radius R _{2 is set} to 1000 m, and In FIG. 4, a circle of 500 m is drawn as a smaller predetermined radius R ₁ , and the environmental factors are divided into the small radius R ₁ and the annular region surrounded by both radii R ₁ and R ₂ . Enter (if it exists).
In FIG. 4, a lake 2, a river 5, a sewage treatment plant 6, a pine land 9, a bamboo forest 8, and a field 7 exist within a circle having a small radius R ₁ (500 m). In addition, the lake 2 exists and the interchange 10 also exists in the annular area surrounded by the large radius R ₂ and the small radius R ₁ .

The risk points can be calculated (summed) by the computer as the next F step by the environmental factor input (E step) within the A step and the predetermined radii R ₁ and R ₂ .
For example, the total value “67” of risk points as shown in Table 7 below is obtained. In addition, the point of interchange 10 is minus (negative) because insects are attracted to interchange 10 with bright lighting. Moreover, in Table 7, it divides into 4 areas by the north-south line and the east-west line that pass through the survey point Z, and calculates the risk point total value (column of 1/4 point azimuth total) of each division, and then all directions In the total points column, four areas are added up as the total risk point value “67”.

  Table 7 shows an example in which the risk points are corrected (programmed in advance) from April to October so as to correct the risk points according to the wind direction.

Next, as shown in FIG. 2, it is determined whether or not the total value of risk points exceeds the reference value as the G step. For example, 1 may be set as the reference value. If this reference value is not exceeded, it is determined that insect control measures are not required 11, and if it exceeds the reference value, the process proceeds to step H.
That is, in the process H, the insects generated corresponding to the environmental factors at the survey point are extracted. For this H process, "Environmental factors within a predetermined radius centered on the survey point" entered in the E process and "Possible insects (names) for each environmental factor" entered and stored in the B process Data is required. Thus, it can be said that the H process is a process for identifying a possible insect.

Next, the process proceeds from the H process to the J process. In this J process, the insect group (i) (ii) (iii) (iv) (v) (see Table 3) to which the developable insect extracted in the H process belongs is specified. At this time, the data input and stored in the above-described C process is necessary. Thus, it can be said that J process is an insect group identification process.
Next, the process proceeds from the J process, the F process, and the D process to the K process. In this K process, the total value of the risk points obtained in the F process, the data of the specified insect group obtained in the J process, and the “insect control measures” input and stored in the D process (Tables 4 to 6) Is necessary). At that time, when the facility (building) newly established at the survey point Z is a food / product factory, the “insect remediation plan” shown in Table 4 is applied. "Insect protection plan" shown in Table 6 is applied in the case of a warehouse.

In addition to Tables 4 to 6, “insect protection measures” corresponding to various other facilities can be freely input and stored in the D step.
Thus, it can be said that the process K is an insecticidal measure plan determination process.

By the way, in the flowchart of FIG. 2, the G step is omitted, and the H step is followed by the F step. Instead, the anti-insect measures are shown in Tables 4, 5 and 6 as “Insect control measures”. It is also free to set the “unnecessary” frame to the lowest level (or the frame in the lower right corner). In FIG. 2, it may be preferable (free) to replace the F process and the HJ process before and after.
FIG. 3 illustrates a block diagram corresponding to the flowcharts of FIGS. 1 and 2. The whole of FIG. 3 consists of the same or separate computers. 3 correspond to the lowercase alphabets a, b, c, d, e... In FIG. 3 and the uppercase alphabets A, B, C, D, E. Although the display 13 and the printer 14 are connected to the insect-control measure determining means k, one of many frames such as Table 4, Table 5, or Table 6 is specified and displayed or printed out. The

If the present invention is expressed as an insect repellent measure decision system based on FIG. 3, it is as follows. That is, the insect-control measure decision system according to the present invention includes a risk point storage means a for storing a risk point P indicating the possibility of flying insects for each of a plurality of environmental factors, and an insect that can be generated for each of the environmental factors. A possible insect memory means b that identifies and memorizes and classifies multiple types of insects into a plurality of insect groups (i) (ii) (iii) (iv) (v) corresponding to the severity, Corresponds to the combination of memorizing insect group (classification) storage means c, risk point total value of survey point Z to be investigated in the future, and each insect group (i) (ii) (iii) (iv) (v) Insect control measure storage means d for storing an insect control measure plan, survey environment factor input means e for inputting an environmental factor within a predetermined radius R ₂ around the survey point Z to the computer, and the survey point Z Summing up the risk factors of environmental factors f and the environmental factors at the survey point Z A possible insect extracting means h for extracting the developable insects from the data stored in the possible insect storage means b, and the developable insects extracted by the developable insect extracting means h, the insect group (Classification) An insect group discriminating means j for classifying by data stored in the storage means c, a total value of risk points obtained from the summing means f, and an insect group specified by the discriminating means j, An insect repellent measure plan determining unit k that determines a repellent measure plan corresponding to the combination based on data stored in the insect repellent measure plan storage unit d.

The present invention has been described in detail above, and it is also preferable to input weather factors such as annual wind direction, temperature / humidity factors, and rainfall factors in the same manner (or separately) as in step A and store them as risk points. The Super Clean Ecoline, Clean Ecoline Mini, Optoclin, Optron, etc. shown in Table 4, Table 5, and Table 6 are not limited to these, but are gradually increasing in performance from insect performance to low performance. If selected, it can be set freely regardless of the manufacturer name. Alternatively, the capacity of the insect repellent device itself shown in Table 4, Table 5, and Table 6 can be reduced sequentially from the upper left corner to the lower right corner. Furthermore, the vertical and horizontal divisions (number of frames) in Table 4, Table 5 and Table 6 are reduced to make rough divisions, and conversely, the vertical and horizontal divisions (number of frames) are increased to make fine (accuracy). It is free even though it is a measure for classification.
Furthermore, in FIG. 4, it is possible to input and store environmental factors based on the environmental factors within a single circle centered on the survey point Z. It may be preferable to classify and input and store environmental factors.

In the present invention, as described above, the risk point storage step A for storing a risk point P indicating the possibility of occurrence of flying insects for each of a plurality of environmental factors by inputting it to a computer, and the occurrence for each environmental factor. A possible insect memory step B for identifying and inputting a possible insect to a computer and storing it, and a plurality of insect groups (i) (ii) (iii) (iv) ( v) Insect group classification storage process C stored in the computer and stored in the computer, the total value of the risk points of the survey point Z to be investigated in the future, and each insect group (i) (ii) (iii) (iv) (v) Insect control plan storage step D for storing the insect control plan corresponding to the combination in advance and storing the environmental factor within the predetermined radius R ₂ centering on the survey point Z to the computer Risk factors of environmental factors at process E and survey point Z above A summing process F, a potential insect identification process H for extracting a potential insect corresponding to the environmental factor at the survey point Z from the data stored in the potential insect memory process B, and the insect Insect group identification process J for identifying the insect group identified from the data stored in the insect group classification storage process C, and the risk points obtained from the above summation process F Insect control plan determination step of determining the insect control plan corresponding to the combination of the total value and the insect group specified in the insect group specification step J based on the data stored in the insect control plan storage step D Since K is a method for determining an insect repellent countermeasure, it can be rationalized into numerical values, and it is possible to perform an accurate and appropriate insect repellent without requiring skill (experience). In other words, even if you are a relatively inexperienced person, you can rely on the experience and intuition to determine the countermeasure plan, resulting in excessive quality, abnormally high costs, or conversely, inadequate quality. This makes it possible to rationally plan accurate, high-precision and appropriate insect control measures.

It is explanatory drawing of the main processes which show one Embodiment of this invention. It is a flowchart figure. It is explanatory drawing of the system which concerns on this invention. It is explanatory drawing which shows an example of a map.

Explanation of symbols

1 Map A, B, C, D, E, F, G, H, J, K Process P, P ₁ , P ₂ Risk point R ₁ , R ₂ radius Z Survey point
(i) (ii) (iii) (iv) (v) Insect group

Claims (1)

A risk point storage step (A) in which a risk point (P) indicating the possibility of flying insects for each of a plurality of environmental factors is input to a computer and stored;
A possible insect storage step (B) in which a possible insect is identified for each of the environmental factors and input to a computer and stored;
Insect group classification storage step (C) in which a large number of insects are classified into a plurality of insect groups (i) (ii) (iii) (iv) (v) corresponding to seriousness and stored in a computer;
Enter the total value of risk points for future survey points (Z) and the insect control measures corresponding to each insect group (i) (ii) (iii) (iv) (v) combination. Insect proof measure memorization process (D) to memorize,
A survey environment factor input step (E) for inputting environmental factors within a predetermined radius (R ₂ ) around the survey point (Z) to the computer;
Summing up the risk points of the environmental factors at the survey point (Z) (F) and the possible insects corresponding to the environmental factors at the survey point (Z) as the potential insect memory step (B) A possible insect identification step (H) to be extracted from the data stored in
An insect group identification step (J) for identifying the insect group identified by the data stored in the insect group classification storage step (C) with the specific developable insects extracted in the insect identification step (H);
Insect control measures corresponding to the combination of the total value of the risk points obtained from the summing step (F) and the insect groups specified in the insect group specification step (J) An insect repellent measure plan deciding method characterized by comprising an insect repellent measure plan determining step (K) to be determined based on the data stored in (D).

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