JP5062557B2 - Pest control information processing system - Google Patents

Description

  The present invention relates to a pest control information processing system and a pest control information processing method configured to perform pest control diagnosis and control measures based on information on pests such as pests.

  In order to diagnose control measures for pests (insects) that invade the factories at food factories, etc., we conduct a survey around the factories to understand what insects live and It is necessary to extract insects with a high risk of harm (easiness of invasion and internal generation) and to predict the problem insects. Survey methods include light trap survey (insects that gather in light), bottle trap survey (insects that gather in smell), and pit hole trap survey (insects that gather on foot).

  For example, Patent Document 1 includes information on pests related to a plurality of types of pests that may appear in a manufacturing factory that handles products taken in the body. It has information that associates items such as environmental contents, local names where each pest may appear, the names of each pest, and insect control measures from each pest with each pest, and these items can be searched. It is disclosed.

JP2002236669

  Conventional pest surveys require about two weeks from implementation to analysis, and it takes time. In addition, the survey costs are outsourced and require hundreds of thousands or more, resulting in increased costs. In addition, there was a problem that the survey was not possible during the winter when insects do not live. Furthermore, since the pest information as described in Patent Document 1 does not use specific data such as the risk of actual occurrence of pests and pest invasion routes, effective pest control measures should be taken. There was a problem that it was not possible.

  The present invention solves the above-described problem, and provides a pest control information processing system and a pest control information processing method capable of taking effective control measures in accordance with a specific example of a target facility. It is for the purpose of provision.

In order to achieve such an object, the pest control information processing system of the present invention includes a first storage means for storing pest control diagnosis information relating to the name and characteristics of the pest as a database, and a survey target. A first processing means for creating the pest control diagnostic information in the facility; and an output means for outputting the pest control diagnostic information created by the first processing means . The processing means collects the articles handled in the surveyed facility and various information on the environment inside and outside the site and the building from the items checked in advance from the items described in the data sheet. facilities according to categories, calculated numerically the risk of generation and invasion of pests by an operation combining the risk index that has been configured with different indices, serial to the first storage unit The information database that is a numerical value obtained by multiplying a weighting factor to the risk index of generation and invasion of pests that are created based on the handling article and premises and internal and external information various environments of the building in the facility of the study characterized by creating a control diagnostic information of the pest is in the display information.

  In addition, the pest control information processing system of the present invention has a risk index of occurrence / invasion of pests created on the basis of information on the handling articles in the surveyed facility and various environments inside and outside the site and building. Risk index (A) for “environment”, risk index (B) for “building peripheral facilities”, risk index (C) for “building environment”, and risk index (D) for “item classification” Yes, a numerical value (A × a) obtained by multiplying the risk index (A) by the weight coefficient (a), a numerical value (B × b) obtained by multiplying the risk index (B) by the weight coefficient (b), and the risk index The sum of a numerical value (C × c) obtained by multiplying (C) by the weighting factor (c) and a numerical value (D × d) obtained by multiplying the risk index (D) by the weighting factor (d) is used in the above-mentioned harmful field. It is characterized by calculating biological control diagnosis information.

  In addition, the pest control information processing system of the present invention includes a weighting factor (a) for the risk index (A) of the “surrounding environment” and a weighting factor (b) for the risk index (B) of the “building surrounding facility”. ) And the weighting coefficient (c) for the risk index (C) of the “building environment” and the weighting coefficient (d) for the risk index (D) of the “item classification” depend on the name of the pest. It is characterized by being set.

  In addition, the pest control information processing system of the present invention has “flight intrusion”, “claw / walk intrusion”, “carrying / adhesion intrusion”, “occurrence inside drainage system” as the generation / intrusion route according to the name of the pest. ”And“ Non-drainage internal generation ”are defined, and the respective ratios are set.

  In addition, the pest control information processing system of the present invention is such that the handling articles in the surveyed facility include foods orally taken into the body orally, cosmetics taken into the body from the skin, and containers, It includes a packaging material and printed matter.

  In addition, the pest control information processing system of the present invention provides information on the environment inside and outside the site and building in the surveyed facility, the external natural environment within a certain range from the facility, the water environment around the building, and the disposal of foodstuffs It is information including the presence or absence of a place, the presence or absence of drainage attached to the building or a heat exhaust mechanism.

In addition, the pest control information processing system of the present invention includes a second storage means for storing each data of handled articles, on-site / external environment, and building environment, which is information processed by the first processing means, and a survey. List of pests with high risk of occurrence / invasion in the target facility, third storage means for storing pest occurrence / invasion form / risk level by route, pest data sheet, control check diagnostic check And a fourth storage means for storing a list and a control measure list.

  The pest control information processing method of the present invention includes a step of storing information on names and characteristics of pests in a storage means as a database, a step of creating control diagnosis information on the pests in a facility to be investigated, The pest control diagnostic information includes the steps of creating the pest control measure information based on the organism pest control information and outputting the pest control diagnostic information and the pest control measure information. In the database information stored in the storage means, the quality may be deteriorated due to the handling articles and pests taken into the body from the oral and skin in the research target facility. Taking into account the risk index for the occurrence and invasion of the above-mentioned pests created based on information on the goods and the environment inside and outside the site or building, Characterized in that it comprises a step of generating a control diagnostic information of the serial pest.

  According to the present invention, the following effects can be obtained. (1) It is possible to predict pests (pests) that may occur and invade the facilities subject to the survey without conducting a detailed local survey. (2) The possibility of occurrence and invasion of pests can be predicted regardless of the season. (3) Since processing is performed by a computer, a result can be obtained in a short time. (4) Since detailed investigation at the site is not required, it can be processed at low cost. (5) The processing results can be used as a preliminary survey when conducting a detailed survey on site. (6) By presenting the processing result to the user as a service, a new business opportunity can be expected.

  Hereinafter, embodiments of the present invention will be described with reference to the drawings. FIG. 1 is a block diagram showing the overall configuration of a pest control information processing system 1 according to an embodiment of the present invention. As shown in FIG. 1, the system 1 is composed of computer hardware resources. Reference numeral 2 denotes an input unit made up of a keyboard and a mouse, 3 denotes an arithmetic processing unit made up of a CPU, 4 denotes a storage unit for storing various data and programs, and 5 denotes an output unit made up of a monitor and a printer. The arithmetic processing unit 3 is provided with a pest control diagnosis system 3a (first processing means) and a pest control countermeasure system 3b (second processing means). The storage unit 4 includes a first storage unit 4a, a second storage unit 4b, a third storage unit 4c, and a fourth storage unit 4d. In the first storage unit 4a, a pest such as a pest is classified according to the environment (in the present invention, the pest may be simply referred to as a pest or an insect), and the results are stored in a database. ing. In the embodiment of the present invention, a pest control diagnosis system 3a that creates pest control diagnosis information based on such a database, and a pest that creates pest control measure information based on pest control diagnosis information The pest control information processing system 1 including the control system 3b is configured.

  The second storage unit 4b includes (1) manufacturing items (aquatic fresh foods, livestock processed foods, etc.) of the facility to be investigated, (2) location environment (natural forests, afforestation, paddy fields, etc.), ( 3) Data on each condition of the site environment (turf, pond, drainage treatment facility, etc.) and (4) building environment (cooling tower, drainage trench, etc.) are stored. The third storage means 4c stores (5) a high-risk insect list. Further, (6) the degree of risk for each intrusion form is digitized and output, and the data is stored.

  The fourth storage unit 4d includes (7) pest data sheet (about 50 kinds of pests extracted from the pictorial book) and (8) control measure diagnosis checklist (confirmation items related to architectural control) of the control measure system. (9) The control measure list (menu list of architectural control measures organized by occurrence / intrusion route) is stored. The first storage unit 4a to the fourth storage unit 4d can store not only character information but also image information such as graphs and color photographs as described later.

  FIG. 2 is an explanatory view showing an embodiment of the present invention. 11 is an example of a data sheet regarding the environment around the site of the facility to be investigated. In the (P) column of FIG. 2, in this example, 1. From "High-density natural forest" 17. Up to “city” is set. In the figure, some environmental categories are omitted. -13. This part is indicated by a broken line. Hereinafter, in the present invention, when a description of data is partially omitted, it is represented by a broken line as described above. In the (Q) column, the definition of the environment classification in the (P) column is described. For example, 15. “Coastal coastal area” is defined as “a coastal area without artificial revetment”. In the (R) column, the ratio of the environmental classification in the (P) column within a certain area is described. In this example, the fixed area is within a range of 100 m from the building outer wall of the facility set in a rectangular shape. However, for example, a range within 100 m from the facility site boundary set in a rectangular shape may be set. . In the example of FIG. 2, the division ratio of “urban area” in the certain area is “20%”.

  FIG. 3 is an explanatory diagram showing an embodiment of the present invention. 12 is an example of a data sheet relating to the environment around the building of the facility to be investigated. The data sheet 12 describes data of outdoor facilities existing within a certain distance, for example, within a range of 20 m from the outer wall of the building set in a rectangular shape of the facility. The data of the outdoor facility shall not be limited to the inside or outside of the facility site. In the (P) column of FIG. From "pond (fountain pond), open-type fire prevention water tank" Up to “incineration facilities” are set. In the (Q) column, the definition of the environment classification in the (P) column is described. For example, 3. “Uncovered waterway / drainage dredging in use” is defined as “a waterway / fault that is used as a drainage channel and is not completely darkened”. In the (R) column, a check column for the presence / absence of the environmental classification in the (P) column is described.

  FIG. 4 is an explanatory view showing an embodiment of the present invention. 13 is an example of a data sheet relating to the building adjacent environment of the facility to be investigated. The data sheet 13 describes a facility / environment that is attached to the building of the facility. In the (P) column of FIG. From "Open type cooling tower", 15. Up to “building greening facility” has been established. In the (Q) column, the definition of the building adjacent environment in the (P) column is described. For example, 2. “Air-conditioning outdoor unit” is defined as “air-conditioning wastewater discharged directly outdoors”. In the (R) column, a check column for the presence / absence of the building adjacent environment in the (P) column is described.

  FIG. 5 is an explanatory diagram showing an embodiment of the present invention. 14 is an example of a data sheet for manufacturing item classification of a facility to be investigated. In the (P) column of the data sheet 14, the environmental classification of the manufactured item of the facility is 1. From “Aquatic Fresh Food”, 20. "Other products" is set. In this environmental category, in addition to oral ingestions such as foods and pharmaceuticals, articles such as cosmetics that are ingested into the body from the skin are described. Furthermore, the articles including containers, packaging materials, and printed materials in which harmful substances such as pathogenic bacteria may be taken into the body from the skin when contacting the articles are also targeted. Note that these containers, packaging materials, printed materials, and the like may be eroded by the pests and impair the quality of the articles themselves even when the pests do not directly affect the human body. In the present invention, a facility that manufactures an article that may impair quality due to such pests is also characterized in that it is set as the environmental category. For this reason, it becomes possible to take finer pest control measures. In other words, the environmental categories of the manufactured items are set to cover articles that may be ingested by pests such as pests and pathogens that are borne by pests. The facility selects one main item from among the environmental categories 1 to 20 among items handled as raw materials and products. In the (Q) column, the definition of the environment classification in the (P) column is described. For example, 18. “Pharmaceuticals / cosmetics, etc.” is defined as “basically including health foods”. In the (R) column, a column for checking items corresponding to the environmental classification in the (P) column of the surveyed facility is described. In the example of FIG. 5, “cereals / flour etc.” is checked.

  FIGS. 6 to 8 are explanatory diagrams of examples showing specific numerical values of the risk of occurrence of pests such as pests corresponding to the environment classification around the site of the facility corresponding to FIG. In FIG. 6, reference numeral 15a denotes an environmental classification data sheet. In this data sheet 15a, the pests are classified as “stink bug” to “bean weevil”, but a part of the classification of the pests is described. In addition, as shown in FIG. 16, several tens of kinds of pests are set in the data. FIG. 16 shows classification symbols 1. From “stink bug”, the classification symbol 53. Up to “Hanaab” is set.

  The environment division (P) column and the definition (Q) column in FIGS. 6 to 8 are the same as those in FIG. The (Ta) column in FIG. 6 assigns a weighting coefficient to risk index data indicating numerically the risk of occurrence of pests in a certain environmental category. For example, environmental classification 5. The weight coefficient of the risk index for the occurrence of “stink bugs” at the facility in “high-rise planting” is set to “0.1”. The data in the (Tb) column of the calculation data sheet 15b in FIG. 7 is obtained by multiplying the weighting factor for the risk index in FIG. 6 by the data in the (Tc) column of the ratio data sheet 15c in FIG.

  The data in the (Tc) column of FIG. 8 is obtained by quantifying a general pest generation ratio in the environmental classification. The data in the (Tc) column in FIG. 8 is stored in advance in, for example, the first storage unit 4a in FIG. In the example of FIG. The risk index (first risk index) for the occurrence of “stink bugs” in “high-rise planting” is set to “2”. In the (Tb) column of the calculation data sheet 15b in FIG. 7, for example, the risk index for occurrence of “stink bug” is “0” obtained by multiplying the weight coefficient “0.1” in FIG. 6 by the risk index “2” in FIG. .2 ". That is, the risk index (second risk index) in FIG. 7 is a weight set according to the environmental classification of the target facility in the general pest risk index (first risk index) in the environmental classification. Calculated by multiplying by a coefficient. The present invention is characterized in that the risk of pest occurrence is quantified using a weighting factor set according to the specific environmental classification of the target facility.

  The (Tb) column of the calculation data sheet 15b in FIG. 7 shows the specific numerical value of the risk of occurrence of a specific pest corresponding to each environmental classification of the facility. In the example of FIG. In addition to “high-rise planting”, 1. "High-density natural forest"-17. A risk index is calculated for the relevant environmental category up to "city". The total (X) in the data sheet 15a of FIG. 6 describes the total value of the risk index (second risk index) of each pest in the facility.

  In this example, “0.2+... +0.2” is calculated as the total value in the (Tb) column of the calculation data sheet 15b of FIG. 1.8 "is obtained. In the embodiment of the present invention, the risk index is obtained by multiplying the occurrence data of general pests in the environmental classification by the weighting factor set in the facility to be investigated as described above. For this reason, it becomes possible to acquire accurate prediction data of the occurrence of pests that are pests according to the specific environmental classification for each facility to be investigated.

  FIG. 9 to FIG. 11 are explanatory diagrams of examples showing specific numerical values of the risk of occurrence of pests such as pests corresponding to the building surrounding environment classification of the facility corresponding to FIG. 3. 9a in FIG. 9 is a data sheet for environmental classification, 16b in FIG. 10 is a data sheet for calculation, and 16c in FIG. 11 is a ratio data sheet. The environment classification (P) column and its definition (Q) column in FIGS. 9 to 11 are the same as those in FIG. In the data sheet 16a of FIG. 9, the (Ta) column assigns a weighting factor to risk index data that numerically represents the risk of pest occurrence in a certain environmental category.

  In the column of (Tc) of the ratio data sheet 16c in FIG. 11, data (first risk index) in which the ratio of the occurrence of general pests in each environmental category is quantified is set. In the calculation data sheet 16b of FIG. 10, a value obtained by multiplying the weighting coefficient of FIG. 9 in each environmental classification by the numerical value of the ratio data sheet of FIG. 11 is set. For example, in the case of “stink bug”, the environmental classification 3. “Uncovered water channel / drainage dredging in use” has the risk index weight coefficient “1” shown in FIG. 9 and the ratio data sheet shown in FIG. The indicated risk index (second risk index) is “1”. Therefore, the numerical value in the total (X) column in the environmental classification data sheet 16a in FIG. 9 is the total value in the (Tb) column in the calculation data sheet 16b in FIG. 10, which is “5” in this example. The number of environmental divisions (number of checks) using a weighting coefficient in the table, which is a value “1” divided by “5” in this example. The calculated value (Y) column is the reciprocal number of the number of the environmental categories that are checked.

FIGS. 12 to 14 are explanatory diagrams of examples showing specific risks of the occurrence of pests such as pests corresponding to the building environment classification of the facility corresponding to FIG. 4. In FIG. 12, 17a is a data sheet for environmental classification, 17b in FIG. 13 is a data sheet for calculation, and 17c in FIG. 14 is a ratio data sheet. The environment division (P) column and its definition (Q) column in FIGS. 12 to 14 are the same as those in FIG. In the data sheet 17a of FIG. 12, the (Ta) column assigns a weighting factor to risk index data indicating numerically the risk of occurrence of pests in a certain environmental category. In the column of (Tc) in the ratio data sheet 17c of FIG. 14, data (first risk index) is set in which the ratio of the occurrence of general pests in each environmental category is quantified.

  In the calculation data sheet 17b of FIG. 13, a value obtained by multiplying the weighting coefficient of FIG. 12 in each environmental category by the numerical value (first risk index) of the ratio data sheet of FIG. 14 is set. For example, in the case of “stink bug”, the environmental classification 3. “Rooftop Ditch / Drainage” is shown in FIG. 13 because the weighting factor of the risk index shown in FIG. 12 is “1” and the numerical value in the ratio data sheet shown in FIG. 14 is “1”. The risk index (second risk index) is “1”. Therefore, the numerical value in the total (X) column in the environmental classification data sheet 17a in FIG. 12 is the total value in the (Tb) column in the calculation data sheet 17b in FIG. The number of environment divisions (number of checks) using a weighting factor in the table, which is a value “1” divided by “6” in this example. The calculated value (Y) column is the reciprocal number of the number of the environmental categories that are checked.

  FIG. 15 is an explanatory diagram showing a data sheet 18a corresponding to the manufactured item of FIG. In FIG. 15, “stink bug” to “bean weevil” are described as pest names. The pest names in FIG. 15 describe a part of the related pests. As described above, the explanatory symbols in FIG. Classification symbol from “stink bug” 53. Up to "Hanaab" is described. In the (X) column of the data sheet 18a, the risk index of each pest occurrence in a certain environmental category is described.

  FIG. 17 is an explanatory diagram showing an example of the risk index for each pest generation / invasion route in the survey target facility. In the (u) column of the data sheet 19 in FIG. 17, the pest generation / intrusion route {(f) to (j)}, the environmental classification {(k) to (n)}, and the manufacturing item {(p) to (S)} items are set. In the (v) column, an arithmetic expression Z for each pest occurrence / intrusion route is set. In the (w) column, setting data and calculation result data are described.

In FIG. 17, the pest generation / intrusion route is “flight intrusion”, “claw / walk intrusion”, “import / attachment intrusion”, “drainage”, as described in columns (f) to (j). "System internal generation", "Non-drainage system internal generation". The generation / intrusion route of the pest classification “stink bug” with respect to the facility has a “flying intrusion” ratio of “0.60” and a “import / attachment intrusion” ratio of “0.40”. Here, “carry-in / adhesion / intrusion” indicates a ratio of adhering and entering these materials when carrying in raw materials or parts.

  The surrounding environment in column (k), the facility surrounding the building in column (l), the building environment in column (m), and the item classification in column (n) correspond to the environmental categories described in FIGS. Yes. The data in the (k) column corresponds to the numerical value of the total (X) in FIG. The data in the (l) column, the (m) column, and the (n) column correspond to the data in FIGS. 11, 14, and 15, respectively.

  “Food design field” in column (p) indicates the risk index when building a new food manufacturing plant, and “Non-food design field” in column (q) indicates the risk index when building a new non-food manufacturing plant. Show. In addition, “food renovation field” in column (r) indicates a risk index when refurbishing (renewal) a food manufacturing factory, and “non-food renovation field” in (s) column renovates a non-food manufacturing factory ( Renewal) shows the risk index.

The calculation formulas Z in the (p) column to the (s) column indicate the risk index of each pest in the “food design field”, “non-food design field”, “food modification field”, and “non-food modification field”, respectively. Set the calculation formula to be calculated. Equation Z is
Z = (A × a) + (B × b) + (C × c) + (D × d). Here, A is the risk index of “Ambient environment” in column (k), B is the risk index of “Facilities around building” in column (l), C is the risk index of “Building environment” in column (m), D Corresponds to the risk index of “item classification” in column (n). In addition, for a to d, numerical values of 0 ≦ a, b, c, d ≦ 1, that is, numerical values of 0 to 1 are appropriately selected. Thus, columns (p) to (s) depend on whether the surveyed facility is a food manufacturing plant or a non-food manufacturing plant, and whether the food manufacturing plant and non-food manufacturing plant are newly constructed or renovated. , A new risk index (third risk index) is obtained by calculation based on the risk indices in columns (k) to (n). Here, whether the surveyed facility is a food manufacturing plant, whether it is a new construction or a renovation, the “classification of the surveyed facility” and the risk index in the (k) to (n) columns are set with “different indicators”. If the risk index is defined, the (p) column to the (s) column are calculated by combining the “risk index set with different indicators” according to the “category of the facility to be surveyed”. This corresponds to obtaining (third risk index).

  FIG. 18 is an explanatory diagram showing a risk index data sheet 20 for each pest occurrence / invasion route in the field of food renovation. In the (a) column, ranks are set in descending order of risk index. In FIG. 18, the ranks from the first to the 50th are set in the descending order of the risk index in the column (a). In the (b) column, the pest species name is described. In the (c) column, the numerical value of the risk index is described. In the column (d), describe the characteristics of the path of occurrence / invasion of pests to the facility. As shown in column (e), the pest generation / intrusion route is, for example, “flight intrusion”, “claw / walking intrusion”, “import / attachment intrusion”, “internal drainage system”, “non-drainage” It is classified as “system internal generation”. In the (d) column of FIG. 18, a plurality of pest generation / intrusion routes for the facility are described. The (e) column describes the pest risk index in each occurrence / invasion route. The total value in column (e) for each occurrence / intrusion route is described in column (X).

  FIG. 19 is an explanatory diagram showing up to the top 10 pest species with a high risk index shown in FIG. 18 in a bar graph. When the numerical value of the data sheet 21 is displayed on the monitor, the top 10 pest species that enter the facility can be visually confirmed. If the bar graph is displayed in color, pest species with a higher risk index can be recognized more clearly. In this example, for example, the risk index 4 to 6 is set to level 1, the risk index 6 to 8 is set to level 2, and the risk index 8 to 12 is set to level 3. These risk index levels are displayed as horizontal lines, and each level can be displayed in color. In addition, a message that “a pest of the kind that has reached level 3 has a high possibility of occurrence / invasion” is displayed on the monitor screen to call attention. In addition, the numerical value of the risk index of the level 1 to the level 3 is an example, and the numerical value of the risk index of each level can be appropriately changed according to the situation.

  FIG. 20 is an explanatory diagram showing the risk index for each occurrence / intrusion route as a bar graph. When the numerical value of the data sheet 22 is displayed on the monitor, the pest species that invade the facility can be visually confirmed for each generation / invasion route. In this example, for example, the risk index 20 to 40 is set to level 1, the risk index 40 to 60 is set to level 2, the risk index 60 to 100 is set to level 3, and each level is displayed in a ranking. Yes. The horizontal lines at each level can be displayed in color. In this case, it is possible to visually grasp the danger level of the pest generation / invasion route more clearly. In addition, a message “Intrusion / occurrence that has reached level 3 needs to be taken urgently” is displayed on the monitor screen to call attention. Also in this example, similarly to the example of FIG. 19, the numerical values of the risk indexes of level 1 to level 3 can be appropriately selected.

  FIG. 21 is an explanatory diagram showing an example of the pest diagnosis data sheet 23. In FIG. 21, the building surrounding environment 23a corresponds to FIG. The building adjacent environment 23b corresponds to FIG. Furthermore, the environment classification 23c corresponds to FIG. 2, and the occupation ratio of each environment within 100 m from the outer wall of the building is displayed as a pie chart. Each environment is color-coded for easy viewing. In this example, it can be visually determined that the occupancy rate of the bare land and the flowing water area is high in the vicinity of the survey target facility.

  FIG. 22 is an explanatory diagram showing the names of pest classifications adopted in the embodiment of the present invention on the database and the risk index of occurrence / invasion thereof. When the data sheet 24 is displayed on the monitor screen, the bar graph is displayed in descending order of the risk index of each pest. A pest name is set in the X-axis direction, and a risk index is set in the Y-axis direction. The risk level is set as level 1 to level 3. Although only a part of the pest names in the X-axis direction are displayed, a number of pest names can be set as described with reference to FIG. In this example, it can be visually judged that the occurrence / invasion risk index of the pest name “housefly” is remarkably high.

  FIG. 23 is an explanatory diagram showing an example of a pest diagnosis data sheet 51 created based on the pest data stored in the database. In the column 51a, pest names are listed together with color photographs. In this example, “Niseke fly” is taken up. In the “classification and form” column 51b, characteristics such as the length and appearance of the pest are described. In the “life cycle” column 51c, the life cycle from the egg-laying to the adult of the pest is described. Such pest photos and features are created from a general picture book.

  In the “risk data” column 51d, specific risk data of the pest described in the column 51a is described. In this example, as a result of the pest diagnosis, the preferred breeding temperature of “Nisebetsu fly” is in the range of 22 ° C to 28 ° C. As an example of the place to be performed, various data such as a food residue etc. indoors, a contamination accident risk at a low level, and an indoor occurrence risk at a high level are described as risk data. In this way, the risk data 51d is output with the general characteristics of the pests published in the pictorial book. For this reason, it is possible to check the pest appearance to see what kind of pests are likely to occur and invade in the target facility. In addition, the “consideration of control measures” 51e describes each control measure when the pest occurs inside the building of the facility and when it occurs outside the building of the facility.

  24-30 is explanatory drawing which shows the process example of the pest control countermeasure system 3b of FIG. The check list 52 in FIGS. 24 and 25 improves the degree of fulfillment of the control measures by checking the confirmation items of the control measures for the pests in and around the building. This check list 52 is divided and displayed as 52a and 52b in FIGS.

  In FIG. 24, the (a) column of the check list 52a is the content of the control measures, the (b) column is remarks (supplement / reason), and the (c) column is the check column. In the (a) column, sub items (r), (s), (t), and (w) are further set. In the (r) column, “Securing / maintaining defense power of a building” is described. In the (s) column, “barrier function” is described. In the (t) column, “entrance / exterior structure / equipment and its maintenance, etc.” are described. In the (w) column, the contents of the control measures are described as explanatory text.

  In the example of FIG. 24, when the content of the control measures is, for example, “the distance between the doors in the front room is preferably 5 m or more.”, As a remark, “the doors prevent insects from easily moving to the next room. The distance between them is ensured. " In the check column of the (c) column, the items for which the countermeasures are taken are checked. In this example, for example, a check is made in the column of “Appropriate insect trapping / insecticing equipment is installed in the back room of the front room”.

  Although not shown in the figure, items such as “Ensuring airtightness” and “Preventing entry from drainage” are set in the (t) column corresponding to the “barrier function” item in the (s) column. can do. In the (s) field, items such as “attraction source control” can be set. Corresponding to the item “attraction source control” in the (s) column, items such as “light control” and “odor control” can be set in the (t) column.

  In the check list 52b of FIG. 25, items "monitoring" {(u) field} and "disinfecting" {(v) field} are set corresponding to the (r) field. In this example, for example, in “Monitoring”, “Light up is properly installed and flying insects are monitored” in column (w), “Lights are periodically replaced in column (b)”. "" Is checked. In addition, in the item “Disinfection”, a check is made in the column “w / Taping Pesticide and Insect” in the column (w), “Power supply / equipment must be installed” in the column (b). ing.

  26 to 30 are explanatory diagrams illustrating examples of a pest control list. This control measure list provides the user with a menu list for control measures inside and around the building for each pest occurrence / intrusion route. The control measure list 53 of FIG. 26 relates to a pest flight measure.

  In the column (a) of FIG. 26, a method for confirming the presence / absence of control measures is described. In this example, “hearing”, “internal viewing”, and “external viewing” are set. In the (b) column, items such as “not close” are described, and in the (c) column, the purpose of taking measures in the (e) column is described. In this example, “secure distance from habitat”, “airtightness”, etc. are set.

  In (d) column, classification is described. In this example, “potential”, “facility”, “operation”, and the like are set. In the (e) column, the contents of the countermeasure are described. For example, as countermeasures corresponding to “external visual” in column (a), “not enter” in column (b), “prevention of entrance / exit opening” in column (c), and “equipment” in column (d), ( In the column e), “install a front chamber at the doorway” and “make the door air tight” are described.

  The control measure list 54 in FIG. 27 relates to measures against insect pests and walking. In the (a) column, a method for confirming whether or not there is a control measure is described. In this example, “hearing”, “internal viewing”, and “external viewing” are set as in FIG. In the (b) column, items corresponding to the countermeasures in the (e) column, for example, “Do not approach”, “Do not put”, and the like are described. In the (c) column, the purpose of taking the measures in the (e) column is described. The purpose of this column (c) is set to “monitoring” in addition to “securing the distance from the habitat”, “airtightness” and the like as in FIG. The classification in the (d) column and the check contents in the (e) column are the same as those in FIG.

  FIG. 28 shows a pest control list 55 regarding pest entry / attachment countermeasures, FIG. 29 shows a pest drainage internal countermeasure list 56, and FIG. 30 shows a pest non-drainage internal countermeasure list 57. The fields (a) to (d) in FIGS. 28 to 30 are the same as the fields (a) to (d) shown in the pest control / walking countermeasure control list 54 in FIG. 27, respectively. is there. The contents of the check in the (e) column are partly the same as those in the (e) column of FIG. 27, but specific measures may be taken depending on the pest generation / intrusion route.

  For example, in the control measure list 55 of FIG. 28, “internal view” in the column (a), “not enter” in the column (b), “cleaning relation” in the column (c), “architecture” in the column (d). The check content in the corresponding column (e) describes “divide into contaminated area and clean work area”. In addition, in the control measure list 56 of FIG. 29, it corresponds to “internal visual inspection” in the column (a), “not enter” in the column (b), “other” in the column (c), and “architecture” in the column (d). The check content in the (e) column to be set is “Install trap and drain fitting with lid”. Further, in the control countermeasure list 57 of FIG. 30, “internal visual inspection” in the column (a), “not generated” in the column (b), “air conditioning” in the column (c), “equipment” in the column (d) are supported. The check content in the (e) column is set to “prevent steam and heat from staying indoors”.

  FIG. 31 is an explanatory diagram showing an example of the data sheet 58 indicating the unachieved level of pest control measures. The data sheet 58 displays, as a percentage, a bar graph as to whether or not measures for each pest generation / intrusion route are taken from the check results of the check list 52 of FIGS. In addition, the level of countermeasures is displayed as a bar graph for countermeasures in terms of hardware and management in addition to the pest generation / intrusion route. In this example, a caution level is set when the unachieved level of countermeasures is 40% to 70% on the Y axis. In addition, when the unachieved level of countermeasures is 70% to 100%, a level that requires immediate countermeasures is set. In this way, by displaying the unachieved levels in ranks, it is possible to call the attention of related parties. In this example, the numerical value of the level can be set as appropriate as in the examples of FIGS.

  In the above description, the facility to be investigated in the pest information processing system of the present invention may be ingested by pests such as pests or pathogens that are borne by pests, orally from the skin. It was supposed to be an article manufacturing factory and an article manufacturing factory that could be eroded by the pests and impair the quality of the articles themselves, even if the pests do not directly affect the human body. However, in the embodiment of the present invention, the facility to be investigated is not limited to the above-described article manufacturing factory. For example, foodstuff centers such as private companies and schools that handle large amounts of foods, markets, backyards for food processing in large stores such as department stores and supermarkets, and food warehouses for distributors can also be included in the surveyed facilities.

  As described above, the features of the pest information processing system according to the embodiment of the present invention are summarized as follows: (1) This pest information processing system can build a building with a high defense against the harm of pests. It is a support system for planning and designing. The pest information processing system includes a “control diagnosis system” for diagnosing the degree of risk caused by pests, and a countermeasure database “control measure system” for preventing damage caused by pests.

  (2) One-to-one risk index for various pests for each input item such as surveyed facilities, for example, factory handling items, factory surroundings, outdoor facilities / environment, attached facilities / environment, etc. I'm allowed. Then, the risk index of each pest in the factory is calculated by taking into account a numerical value obtained by multiplying the risk index of the pest for each input item by a weighting factor. At this time, the handling items have a greater influence than the surrounding environment of the factory, and therefore, the contrivances such as increasing the coefficient of the handling items are made. Here, since there are several types of generation / invasion routes for each pest, the rate of occurrence / invasion from each route is quantified for each pest. For example, in the case of stink bugs, the flying is 60% and the walking is 40%, and a specific risk index for occurrence / intrusion is indicated by a numerical value.

  (3) The risk of each pest calculated in (2) above is multiplied by the ratio of each occurrence / invasion route, and the risk is tabulated for each occurrence / invasion route. From the output unit, the top of the pest risk calculated in (2), for example, the top 10 are shown in a bar graph. Furthermore, the risk for each occurrence / intrusion route tabulated in (3) is shown as a bar graph. For this reason, it becomes easy to judge the occurrence and invasion of pests visually. As described above, in the embodiment of the present invention, the risk of invasion and contamination of pests is calculated and output instead of the incidence of pests. Therefore, there is an advantage that it is easy to take specific control measures for pests.

  As described above, according to the present invention, a pest control information processing system and a pest control information processing method capable of taking effective control measures in accordance with a specific example of a target facility are obtained. .

It is a block diagram which shows the whole structure of embodiment of this invention. It is explanatory drawing which shows embodiment of this invention. It is explanatory drawing which shows embodiment of this invention. It is explanatory drawing which shows embodiment of this invention. It is a characteristic view which shows embodiment of this invention. It is explanatory drawing which shows embodiment of this invention. It is explanatory drawing which shows embodiment of this invention. It is explanatory drawing which shows embodiment of this invention. It is explanatory drawing which shows embodiment of this invention. It is explanatory drawing which shows embodiment of this invention. It is explanatory drawing which shows embodiment of this invention. It is explanatory drawing which shows embodiment of this invention. It is explanatory drawing which shows embodiment of this invention. It is explanatory drawing which shows embodiment of this invention. It is a characteristic view which shows embodiment of this invention. It is explanatory drawing which shows embodiment of this invention. It is explanatory drawing which shows embodiment of this invention. It is explanatory drawing which shows embodiment of this invention. It is explanatory drawing which shows embodiment of this invention. It is explanatory drawing which shows embodiment of this invention. It is explanatory drawing which shows embodiment of this invention. It is explanatory drawing which shows embodiment of this invention. It is explanatory drawing which shows embodiment of this invention. It is explanatory drawing which shows embodiment of this invention. It is explanatory drawing which shows embodiment of this invention. It is explanatory drawing which shows embodiment of this invention. It is explanatory drawing which shows embodiment of this invention. It is explanatory drawing which shows embodiment of this invention. It is explanatory drawing which shows embodiment of this invention. It is explanatory drawing which shows embodiment of this invention. It is explanatory drawing which shows embodiment of this invention.

Explanation of symbols

  DESCRIPTION OF SYMBOLS 1 ... Pest control information processing system, 2 ... Input part, 3 ... Operation processing part, 3a ... Pest control diagnosis system (1st process part), 3b ... Pest control Countermeasure system (second processing unit), 4 ... storage unit, 5 ... output unit

Claims (7)

First storage means for storing pest control diagnostic information relating to the name and characteristics of the pest as a database;
A first processing means for creating control pest control information of the pests in a facility to be investigated;
Output means for outputting control diagnostic information of the pest created by the first processing means ,
The first processing means includes
Information on the goods handled in the surveyed facility and the environment inside and outside the site and building are collected from the items checked in advance in the data sheet,
According to the classification of the facility to be surveyed, calculate the risk of pest occurrence / invasion numerically by calculation combining risk indices set with different indicators,
Risk of occurrence / invasion of pests created based on information in the database stored in the first storage means and information on handling articles in the surveyed facility and various environments inside and outside the site and building A pest control information processing system, characterized in that the pest control diagnosis information, which is information represented by a numerical value obtained by multiplying an index by a weighting factor, is created. The risk index of the occurrence and invasion of pests created based on the handling articles in the surveyed facility and the information on the environment inside and outside the site and building are the risk index (A) of “Ambient environment” and “ Risk index (B) for “facility around building”, risk index (C) for “building environment”, and risk index (D) for “item classification”
A numerical value (A × a) obtained by multiplying the risk index (A) by the weighting factor (a), a numerical value (B × b) obtained by multiplying the risk index (B) by the weighting factor (b), and the risk index (C ) Multiplied by a weighting factor (c) (C × c) and a risk index (D) multiplied by a weighting factor (d) (D × d). The pest control information processing system according to claim 1, wherein control diagnosis information is calculated. A weighting factor (a) for the risk index (A) of the “surrounding environment”, and
A weighting factor (b) for the risk index (B) of the “facility around the building”, and
A weighting factor (c) for the risk index (C) of the “building environment”; and
3. The pest control information processing system according to claim 2, wherein the weighting coefficient (d) for the risk index (D) of the “item classification” is set according to the name of the pest. The types of “flight intrusion”, “徘徊 / walk intrusion”, “import / attachment intrusion”, “drainage internal generation”, and “non-drainage internal generation” are defined as generation / intrusion routes according to the name of the pest. The pest control information processing system according to any one of claims 1 to 3, wherein each ratio is set. Claim handling article in facilities of the surveyed food to be ingested orally, in addition to pharmaceuticals, cosmetics ingested into the body through the skin, and the container, packaging material, characterized in that it comprises a printed material The pest control information processing system according to any one of claims 1 to 4 . The information on the environment inside and outside the site and building in the surveyed facility includes the external natural environment within a certain range from the facility, the water environment around the building, the presence or absence of a waste disposal site, the drainage and heat removal mechanism attached to the building The pest control information processing system according to any one of claims 1 to 5, wherein the information includes presence or absence. Information to be processed by the first processing means;
A second storage means for storing each data of handled articles, on-site and off-site environments, and building environments;
A list of pests with a high risk of occurrence / invasion at the facility under investigation, and a third storage means for storing the pest occurrence / invasion form / level risk level by route;
The pest control information processing according to any one of claims 1 to 6, further comprising: a pest data sheet, a control measure diagnosis checklist, and a fourth storage means for storing the control measure list. system.

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