KR20210084183A - Food waste management support apparatus and method - Google Patents

Abstract

The present invention relates to a food waste management support device and a method. The food waste management support device includes: a food waste analysis unit which collects analysis data on a current status of food waste in a specific area and determines the amount of food waste for each building; a collection difficulty calculation unit for each zone which divides the specific area into a plurality of zones according to a boundary of a legal dong by using legal zone information of the analysis data, and calculates food waste collection difficulty for each zone; and a recommended collection path determining unit which determines a recommended collection path for food waste collection in the specific area through network analysis based on the amount of food waste for each building and the food waste collection difficulty for each zone. The present invention supports the improvement of the efficiency of a food waste collection service.

Description

FOOD WASTE MANAGEMENT SUPPORT APPARATUS AND METHOD

The present invention relates to a food waste management support technology, and more particularly, food waste that can support the efficiency improvement of food waste collection service by calculating the amount of food waste by building and the difficulty of each zone regarding food waste collection through data analysis. It relates to a management support apparatus and method.

The RFID-based volume-rate system is a food waste volume-based system that recognizes an RFID tag on the equipment and discharges food waste, and the weight information of the dispenser and the discharged food waste is automatically transmitted to the central system to manage fees. This is an advanced food waste reduction policy and corresponds to a method that enables effective weight measurement and information management among three methods: RFID method, chip method, and envelope method. In addition, by establishing an information system, it has the advantage of enabling integrated management of food waste, such as collection of emission information, management of fee information, and management of national statistics.

There are three types of RFID-based volume-rate system: individual metering method, vehicle collection method, and portable reader method. Individual metering method is applied to apartment complexes, and vehicle collection method is applied to restaurants where a large amount of food waste is discharged. This method is applied to detached houses and small restaurants.

On the other hand, since food waste is generated everywhere in the building due to its nature, it is essential for the cleaning staff to be familiar with the area. In addition, when new personnel are put into unfamiliar areas, it is generally understood that it takes about two months to fully understand the collection routes, and the routes they need to know are managed in text, which is a cause of lowering work efficiency. .

Therefore, in order to improve the efficiency of the food waste collection service, there is a need to develop a technology that can utilize various information collected through the RFID-based volume-rate system.

Korean Patent Publication No. 10-2014-0028888 (2014.03.10)

An embodiment of the present invention provides an apparatus and method for supporting food waste management that can support the improvement of the efficiency of a food waste collection service by calculating the amount of food waste for each building and the difficulty of each area for food waste collection through data analysis. .

An embodiment of the present invention proposes a customized collection movement route by applying three improvements to a topic map that can know the aggregation of emissions by building type and legal dong, grading by dong for collection and transport, and three improvements to existing routes By doing so, it is intended to provide a food waste management support device and method that can improve the efficiency of the cleaning administration and improve the working environment of workers.

In the embodiments, the food waste management support apparatus collects analysis data on the current state of food waste in a specific area and determines the amount of food waste for each building by using the food waste emission analysis unit, the legal area information of the analysis data, to collect the analysis data. A specific area is divided into a plurality of areas according to the boundary of the statutory building, and a collection difficulty calculation unit for each area calculates the difficulty of collecting food waste by area, and a network analysis based on the amount of food waste for each building and the difficulty of collecting food waste for each area. and a recommended collection path determining unit for determining a recommended collection path for collecting food waste in the specific area through the method.

The food waste emission analysis unit purifies the analysis data to collect the collection amount, collection date, collection time and collection location of the food waste, a second step of matching the street name address building and the serial cadastral map of the analysis data A third step of allocating a collection place for each food waste to the building with the street name address to determine the amount of food waste for each building and a fourth step of generating a two-dimensional thematic map about the amount of food waste for each building can be performed. .

The collection difficulty calculation unit for each zone collects food waste for each zone by applying a weight to each of the plurality of zones according to the priority among the main variables defined by the collection point score, the amount of discharge, the road slope, the moving distance, and the road width. difficulty can be calculated.

According to the housing type of the specific area, the collection difficulty calculation unit for each zone gives the above priority in the order of collection points, emissions, road width, moving distance and road slope in case of single-family houses, and in case of apartment houses, collection points , the moving distance, the amount of discharge, the road width and the road slope may be given the above priority in the order.

As a pre-processing step of the network analysis, the recommended collection path determining unit is a first step of refining the road name address basic map to generate links between nodes constituting the road network, according to the slope of each link of the road network. A network data set can be constructed by performing the second step of assigning weights and the third step of giving each link an average travel time for food waste collection.

The recommended collection route determining unit applies a limited capacity of a collection vehicle in charge of collecting the food waste, collection time, and length of collection route as conditions through VRP (Vehicle Route Problem) analysis based on the network dataset, and applies the conditions to the specific area It is possible to derive an optimal collection path from among a plurality of collection paths for food waste collection.

The recommended collection route determining unit derives the average loading amount, average collection time, and average number of trips of collection vehicles for collection routes currently in operation as improvement conditions, and satisfies at least two of the improvement conditions among the plurality of collection routes A collection path may be determined as the recommended collection path.

Among the embodiments, the food waste management support method includes determining the amount of food waste for each building by collecting the food waste generation status for a specific area, and calculating the difficulty of collecting food waste for each area based on the topographic data on the specific area and determining a collection path for food waste collection in the specific area through network analysis based on the amount of food waste for each building and the difficulty of collecting food waste for each area.

The disclosed technology may have the following effects. However, this does not mean that a specific embodiment should include all of the following effects or only the following effects, so the scope of the disclosed technology should not be construed as being limited thereby.

The apparatus and method for supporting food waste management according to an embodiment of the present invention can support the improvement of the efficiency of the food waste collection service by calculating the amount of food waste for each building and the difficulty of each zone regarding food waste collection through data analysis.

Food waste management support apparatus and method according to an embodiment of the present invention is a subject map that can know the aggregate of emission by building type and legal dong, grading of difficulty for collection and transport by dong, three improvements to existing routes It is possible to improve the efficiency of the cleaning administration and improve the working environment of workers by suggesting a customized collection route by applying the

1 is a block diagram illustrating an apparatus for supporting food waste management according to the present invention.
FIG. 2 is a flowchart illustrating a food waste management support process in the food waste management support apparatus shown in FIG. 1 .
3 is a conceptual diagram illustrating a method for determining a new collection path for food waste management support according to the present invention.
4 to 6 are diagrams illustrating main variables used for calculating the collection difficulty for each zone.
7 is a diagram showing the priority among the main variables affecting the collection difficulty for each zone.
8 is a diagram illustrating an embodiment of grading by zone with respect to the difficulty of collecting food waste according to the present invention.

Since the description of the present invention is merely an embodiment for structural or functional description, the scope of the present invention should not be construed as being limited by the embodiment described in the text. That is, since the embodiment may have various changes and may have various forms, it should be understood that the scope of the present invention includes equivalents capable of realizing the technical idea. In addition, since the object or effect presented in the present invention does not mean that a specific embodiment should include all of them or only such effects, it should not be understood that the scope of the present invention is limited thereby.

On the other hand, the meaning of the terms described in the present application should be understood as follows.

Terms such as “first” and “second” are for distinguishing one component from another, and the scope of rights should not be limited by these terms. For example, a first component may be termed a second component, and similarly, a second component may also be termed a first component.

When a component is referred to as being “connected to” another component, it should be understood that the component may be directly connected to the other component, but other components may exist in between. On the other hand, when it is mentioned that a certain element is "directly connected" to another element, it should be understood that the other element does not exist in the middle. Meanwhile, other expressions describing the relationship between elements, that is, “between” and “immediately between” or “neighboring to” and “directly adjacent to”, etc., should be interpreted similarly.

The singular expression is to be understood to include the plural expression unless the context clearly dictates otherwise, and terms such as "comprises" or "have" refer to the embodied feature, number, step, action, component, part or these It is intended to indicate that a combination exists, and it should be understood that it does not preclude the possibility of the existence or addition of one or more other features or numbers, steps, operations, components, parts, or combinations thereof.

Identifiers (eg, a, b, c, etc.) in each step are used for convenience of description, and the identification code does not describe the order of each step, and each step clearly indicates a specific order in context. Unless otherwise specified, it may occur in a different order from the specified order. That is, each step may occur in the same order as specified, may be performed substantially simultaneously, or may be performed in the reverse order.

The present invention can be embodied as computer-readable codes on a computer-readable recording medium, and the computer-readable recording medium includes all types of recording devices in which data readable by a computer system is stored. . Examples of the computer-readable recording medium include ROM, RAM, CD-ROM, magnetic tape, floppy disk, optical data storage device, and the like. In addition, the computer-readable recording medium may be distributed in a network-connected computer system, so that the computer-readable code may be stored and executed in a distributed manner.

All terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention belongs, unless otherwise defined. Terms defined in general used in the dictionary should be interpreted as being consistent with the meaning in the context of the related art, and cannot be interpreted as having an ideal or excessively formal meaning unless explicitly defined in the present application.

The food waste management support apparatus 100 may be implemented as a server corresponding to a computer or program capable of supporting food waste management by analyzing the amount of food waste in a specific area, calculating the collection difficulty for each area, and determining a recommended collection route. . The food waste management support apparatus 100 may be wirelessly connected to various user terminals through Bluetooth, WiFi, a communication network, etc., and may exchange data with the user terminals through the network. In this case, the user terminal may correspond to a personal terminal used by a food waste collector or manager.

In an embodiment, the food waste management support apparatus 100 may store data necessary for determining the amount of food waste by building, calculating the collection difficulty for each area, and determining the recommended collection route in conjunction with the database. The food waste management support apparatus 100 may be implemented by including a database therein. In addition, the food waste management support apparatus 100 may be implemented by including a processor, a memory, a user input/output unit, and a network input/output unit, and a detailed description thereof will be omitted.

The database may correspond to a storage device for storing various types of information required in a process of determining a collection path for food waste collection in a specific area. For example, the database may store analysis data collected from various administrative agencies and public institutions, and the like, and may store statistical information of the collected data and status information derived through spatial analysis. In addition, the database may be composed of a plurality of database modules to store and manage each piece of information, and each database module may be connected to a network to form one database group.

1 is a block diagram illustrating an apparatus for supporting food waste management according to the present invention.

Referring to FIG. 1 , the food waste management support apparatus 100 may include a food waste emission analysis unit 110 , a collection difficulty calculation unit 130 for each area, a recommended collection route determination unit 150 , and a control unit 170 . can

The food waste emission analysis unit 110 may determine the amount of food waste for each building by collecting analysis data on the current state of food waste generation in a specific area. In the case of food waste, it is common to discharge food waste in a specific place for each building and collect it at once at the place. Therefore, the food waste analysis unit 110 determines the optimal route for food waste collection by building based on the collected analysis data. The amount of food waste can be derived.

On the other hand, the analysis data collected by the food waste emission analysis unit 110 is data on the food waste generation status, and may include food waste metering data, information on a collection company, and public data.

Food waste weighing data can be automatically collected by transmitting the data to the central server when RFID tagging through the RFID-type collection device. Food waste weighing data may be composed of five tables. More specifically, the food waste weighing data may have field names of 'GUBUN', 'CAR_NO', 'SG_DATE', 'QTY', and 'ADDRESS'.

In the case of 'GUBUN', gong may mean an apartment house, so may mean a small restaurant, and dan may mean a detached house. 'CAR_NO' is the number of the collection vehicle and can be used to classify each company. 'SG_DATE' is a collection date and can be used when analyzing patterns by day of the week. 'QTY' is the amount of food waste that can be estimated for each building based on the address. 'ADDRESS' may correspond to the address where the food waste was discharged.

The collection company information may correspond to information on a collection company in charge of collecting food waste in a specific area, and the collection company may be designated for each housing type. In addition, public data may correspond to data or information created or managed by public institutions, and may include legal area information, serial cadastral map, road name address DB, DEM (Digital Elevation Model, slope), and RFID/communal house weight information. and the like.

The legal area information is information indicating the boundary area of the legal building and may correspond to spatial data expressed in the SHP format of the Bessel ellipsoid and the planar rectangular coordinate system. The continuous cadastral map is drawing information created in a continuous form by connecting the boundary points on the cadastral map and the forest map, and may correspond to reference drawing information that cannot be used as survey data, and is expressed in the SHP format of the Bessel ellipsoid and the planar rectangular coordinate system. It may correspond to spatial data.

In addition, the road name address DB is an electronic map that provides 11 types of data, such as administrative district boundaries (province, city, county, eup-myeon-dong, Beop-myeon-dong), building/building group, road section/shock road/base section, entrance/base section may be applicable. Meanwhile, the food waste management support apparatus 100 may use the PNU of target data composed of building polygons as a PK (Primary Key) value to match the amount of food waste for each building object. On the other hand, road data can be used for calculation of food waste collection difficulty and VRP analysis.

DEM can be constructed by sampling digital topographic data, and can be classified as DEM or TIN according to the approach.

In one embodiment, the food waste emission analysis unit 110 purifies the analysis data to collect the collection amount, collection date, collection time, and collection location of the food waste in the first step, the road name address building and the serial cadastral map of the analysis data. The second step of matching, the third step of determining the amount of food waste by building by allocating the collection place for each food waste to the building with the street name address, and the fourth step of creating a two-dimensional thematic map for the amount of food waste by building can do.

More specifically, the food waste emission analyzer 110 may obtain food waste collection information by refining the food waste metering amount data among the analyzed data. In addition, the food waste emission analysis unit 110 may perform a spatial join between the building of the road name address DB among public data and the continuous cadastral map for matching between the refined food waste metering amount and the building of the road name address basic map. have.

In addition, the food waste emission analysis unit 110 can spatially coordinate the collection place for each food through geocoding, and assign the food waste emission amount to all buildings existing in a specific area by assigning it to a road name address building. value can be assigned.

In addition, the food waste emission analysis unit 110 can derive the total emission by building type as well as the total emission by legal dong through the thematic map of the food waste emission by building, and establishes the base data for calculating the collection difficulty by area can do. The food waste emission analysis unit 110 may analyze the food waste pattern for each day of the week and for each season through the thematic map on the amount of food waste for each building.

On the other hand, the subject map is a map that emphasizes a specific subject, and may be displayed using a certain color or symbol based on the general map. For example, the subject map may include statistical maps such as land use maps, geological maps, and soil maps, urban planning maps, regional plans, and national land development plans. Thematic map is a map produced for a specific purpose and can be used to express a special geographical distribution by using structural characteristics such as time, direction relationship, change of location form, and orientation. Therefore, the food waste emission subject map can display the result of matching the food waste emission amount with the attribute value for a building based on the building information of the road name address basic map using a differentiated color.

The collection difficulty calculation unit 130 for each area divides a specific area into a plurality of areas according to the boundary of the legal dong by using the legal area information of the analysis data, and calculates the food waste collection difficulty for each area. In order to derive an optimal collection path for each area, the collection difficulty calculation unit 130 may perform analysis on a partial area obtained by dividing the whole rather than the entire specific area. The collection difficulty calculation unit 130 for each zone may use the legal dong boundary as a division criterion, and as a result, may calculate the food waste collection difficulty for each of the plurality of zones divided according to the legal dong boundary.

In one embodiment, the collection difficulty calculation unit 130 for each zone applies a weight according to the priority among the main variables defined by the collection point number, the discharge amount, the road slope, the moving distance, and the road width for each of the plurality of zones Thus, it is possible to calculate the difficulty of collecting food waste for each area. That is, the difficulty of collecting food waste can increase as the amount of food waste in the work area increases and the number of collection points increases, and the steeper the road slope, the higher the level of road gradient because food waste must be transported to the collection container and vehicle by human labor. In addition, the longer the moving distance, the narrower the road width when moving may affect the collection operation.

4 to 6 are diagrams illustrating main variables used for calculating the collection difficulty for each zone. More specifically, Fig. 4 shows the amount of food waste discharged (discharge amount), Fig. 5 shows the collection points, Fig. 6 (a) shows the road gradient, Fig. 6 (b) shows the moving distance, Figure (c) is a diagram showing the width of the road.

4 to 6 , the collection difficulty calculation unit 130 for each zone derives the spatial distribution regarding the collection point score, the discharge amount, the road slope, the moving distance, and the road width for each of the plurality of zones based on the analysis data can do. In an embodiment, the collection difficulty calculation unit 130 for each zone may grade each zone by using the spatial distribution of the main variables.

In another embodiment, the collection difficulty calculation unit 130 for each zone may derive the difficulty of collecting food waste for each zone as a result of spatially joining the spatial distributions of the main variables. For example, the collection difficulty calculation unit 130 for each zone may combine the food waste emission amount, the number of collection points, and the moving distance with the legal dong data through a summation calculation, and the road slope and the road width may be combined through an average calculation. Based on these values, the collection difficulty calculation unit 130 for each zone performs grading on the assumption that the larger the table value and the smaller the road width, the higher the collection difficulty. can

8 is a diagram illustrating an embodiment of grading by zone with respect to the difficulty of collecting food waste according to the present invention. Referring to FIG. 8 , the difficulty of collecting food waste for each zone is graded by the collection difficulty calculation unit 130 for each zone, and a graphically visualized result can be confirmed.

Figure 8 (a) shows the grading result when the housing type is a detached house or a small restaurant, and Figure 8 (b) shows the grading result when the housing type is an apartment house. As a result, even in the same area, the priority level of the major variables affecting the difficulty of collecting food waste is different depending on the type of housing, and thus the grade of the level of difficulty in collecting may also be different.

Meanwhile, as for the food waste collection method, a total of three types may be used: an individual metering method, a vehicle collection method, and a portable reader method. For example, the individual metering method may be applied to apartment complexes, etc., the vehicle collection method may be applied to a restaurant where a large amount of food waste is discharged, and the portable reader method may be applied to a detached house or a small restaurant.

In one embodiment, the collection difficulty calculation unit 130 for each area gives priority in the order of collection points, emissions, road width, moving distance and road slope in the case of a detached house, according to the housing type of a specific area, and the common In the case of housing, priority can be given in the order of collection points, travel distance, emissions, road width and road slope. Since different methods may be applied to the food waste collection depending on the housing type, the collection difficulty calculation unit 130 for each area may differentially determine the collection difficulty according to the housing type.

More specifically, in the case of a detached house, the collection point and food waste emission may have a greater effect on the collection difficulty than the moving distance or road slope, and in the case of an apartment house, the collection point and the moving distance are higher than the road width or road slope. It may have a greater impact on the difficulty of collection. The collection difficulty calculation unit 130 for each zone differentially assigns weights according to priorities to each of the major variables, so that the ratio reflected in the calculation of the collection difficulty for each zone can be adjusted according to the local environment or collection conditions.

For example, FIG. 7 is a diagram illustrating priorities among major variables affecting the collection difficulty for each zone. Figure 7 (a) shows the priority for each major variable when the housing type is a detached house or a small restaurant, and Figure 7 (b) shows the priority for each major variable when the housing type is an apartment house. have. That is, since food waste collection methods are different depending on the housing type, main variables affecting the towel difficulty may be different, and as a result, a difference in collection difficulty may occur.

The recommended collection path determining unit 150 may determine a recommended collection path for food waste collection in a specific area through network analysis based on the amount of food waste for each building and the difficulty of collecting food waste for each area. That is, the recommended collection route determining unit 150 can arrange more collection vehicles or collection personnel in areas where the amount of food waste by building is greater and the difficulty in collecting food waste by area is higher, and can increase the number of collections or increase the number of collections. By reducing the collection cycle, the efficiency of food waste collection can be increased. Accordingly, the recommended collection route determining unit 150 may derive an optimal collection route by reflecting the collection vehicle, the collection manpower, the number of collection times, and the collection period.

In one embodiment, the recommended collection path determining unit 150 is a pre-processing step of network analysis, a first step of refining a road name address basic map to create a link between nodes constituting the road network; A network dataset can be constructed by performing the second step of giving each link a weight according to the inclination and the third step of giving each link an average moving time for food waste collection. That is, the recommended collection route determining unit 150 may build a road network based on the road of the road name address basic map.

More specifically, the recommended collection path determining unit 150 may generate links between nodes so as to correspond to each road of the basic road name address in the first step. A road network is a network, where nodes may correspond to intersections of roads, and links may correspond to roads. A link can be automatically identified by a segment identifier when configuring a network, and in the case of a road network, it may include an attribute table including information such as road name, distance, and speed limit.

In addition, the recommended collection path determining unit 150 may assign a weight to each link of the road network according to the inclination. Each link may include an attribute table, and items constituting the attribute table may include a gradient and a weight. The recommended collection path determining unit 150 may assign a gradient and a weight to the attribute table of each link based on the DEM of the analyzed data.

In addition, the recommended collection path determining unit 150 may give each link an average travel time for food waste collection. That is, the recommended collection path determining unit 150 may allocate the average travel time to the attribute table of each link. As a result, the recommended collection path determining unit 150 may perform a preparatory operation for network analysis through road network construction.

In an embodiment, the recommended collection route determining unit 150 performs VRP (Vehicle Route Problem) analysis based on the network data set to condition the limited capacity, collection time, and length of the collection path of the collection vehicle in charge of collecting food waste. It is possible to derive the optimal collection path from among a plurality of collection paths for food waste collection in a specific area.

Here, VRP (Vehicle Route Problem) analysis is a network analysis and may correspond to an analysis method of finding an optimal route according to conditions for multiple vehicles visiting a series of locations. The recommended collection route determining unit 150 may apply the limited capacity of the collection vehicle, collection time, and length of the collection route as conditions for VRP (Vehicle Route Problem) analysis, and a plurality of collections for food waste collection in a specific area. By using the routes as candidates, the optimal collection route can be determined among them.

In an embodiment, the recommended collection route determining unit 150 derives the average loading amount, average collection time, and average number of trips of the collection vehicles for the currently operated collection routes as improvement conditions, and improves conditions among the plurality of collection routes A collection route that satisfies at least two of the following may be determined as a recommended collection route. The recommended collection route determining unit 150 may use the current actual collection routes derived based on the analysis data collected from the actual collection vehicle for a specific period as a reference condition.

That is, the recommended collection route determining unit 150 determines the average loading amount of food waste collected by the collection vehicle along the currently operated collection route, the average collection time required to collect all the food waste along the collection route, and the food waste discharge rate. In accordance with this, a recommended collection route can be determined from among the collection routes that have a higher average load capacity, shorter average collection time, or fewer average trips, using the average number of trips required for collection as a condition for improvement.

The control unit 170 controls the overall operation of the food waste management support apparatus 100 , and a control flow between the food waste emission analysis unit 110 , the collection difficulty calculating unit 130 by area, and the recommended collection path determining unit 150 . Or you can manage the data flow.

FIG. 2 is a flowchart illustrating a food waste management support process in the food waste management support apparatus shown in FIG. 1 .

Referring to FIG. 2 , the food waste management support apparatus 100 collects analysis data on the food waste generation status in a specific area through the food waste emission analysis unit 110 to determine the amount of food waste for each building (step S210).

The food waste management support apparatus 100 divides a specific area into a plurality of areas according to the boundary of the legal dong using the legal area information of the analysis data through the collection difficulty calculation unit 130 for each area, and determines the difficulty of collecting food waste by area. can be calculated (step S230).

The food waste management support apparatus 100 determines a recommended collection path for food waste collection in a specific area through network analysis based on the food waste emission by building and the food waste collection difficulty by area through the recommended collection path determining unit 150 . It can be determined (step S250).

3 is a conceptual diagram illustrating a method for determining a new collection path for food waste management support according to the present invention.

Referring to FIG. 3 , the food waste management support apparatus 100 may construct a new route map for food waste collection in a specific area. The food waste management support apparatus 100 can largely independently perform an analysis on a building and an analysis on a road, and can derive the amount of food waste for each building through the analysis on the building, and through the analysis on the road It is possible to calculate the collection difficulty for each area.

More specifically, the apparatus 100 for supporting food waste management may obtain information about a vehicle, a date, an amount of weight, and an address by refining the amount of food waste. The food waste management support apparatus 100 may match a road name address building and a continuous cadastral map, and may generate a subject map by matching the weight of each building.

In addition, the food waste management support apparatus 100 can extract the movement distance for each legal dong from the road name address road, and can extract the road slope and road width for each legal dong from the numerical topographic map, and based on these data, grading can be done.

Finally, the food waste management support apparatus 100 may construct a road network reflecting road factors and perform VRP network analysis by reflecting the classification for each legal dong.

In this case, the collection difficulty for each area may be expressed as a numerical value, and the food waste management support apparatus 100 may rank based on the numerical value. The food waste management support apparatus 100 may determine a recommended collection path for food waste collection through VRP network analysis based on the amount of food waste for each building and the collection difficulty for each area.

In addition, the food waste management support apparatus 100 may calculate the cost of a consignment company in charge of collecting and transporting food waste based on the difficulty of collection for each area. Currently, the process of calculating the appropriate manpower and vehicle after the field survey for collection and transportation and the cost estimation for each collection system is being carried out. However, as described above, the difficulty calculation index for each administrative district derived through the food waste management support device 100 is calculated. If it is used, it can be expected to not only calculate the service cost according to the characteristics of the region but also improve the working environment of the cleaning administration.

In addition, the food waste management support apparatus 100 can provide basic data for enhancing work equality between collection companies by calculating the difficulty of each task by grading by index, and supplementing problems such as overlapping routes through efficient collection route management can do.

Although the above has been described with reference to preferred embodiments of the present invention, those skilled in the art can variously modify and change the present invention within the scope without departing from the spirit and scope of the present invention as set forth in the claims below. You will understand that it can be done.

100: food waste management support device
110: food waste emission analysis unit
130: collection difficulty calculation unit for each area
150: recommended collection route determining unit
170: control unit

Claims (8)

a food waste analysis unit that collects analysis data on the current status of food waste in a specific area and determines the amount of food waste for each building;
a collection difficulty calculation unit for each zone for dividing the specific area into a plurality of zones according to the boundary of the legal dong by using the legal zone information of the analysis data and calculating the food waste collection difficulty for each zone; and
and a recommended collection path determining unit configured to determine a recommended collection path for food waste collection in the specific area through network analysis based on the amount of food waste for each building and the difficulty of collecting food waste for each area.
According to claim 1, wherein the food waste analysis unit
The first step of purifying the analysis data to collect the amount of food waste, collection date, collection time and collection location, the second step of matching the road name address building and the serial cadastral map of the analysis data, a collection place for each food waste Food waste management support, characterized in that a third step of determining the amount of food waste for each building by allocating to the building with the street name address and a fourth step of generating a two-dimensional thematic map for the amount of food waste for each building are performed Device.
According to claim 1, wherein the collection difficulty calculation unit for each area
For each of the plurality of zones, a weight is applied according to the priority among major variables defined by the number of collection points, the amount of discharge, the road slope, the moving distance, and the road width to calculate the difficulty of collecting food waste for each zone. Food waste management support device.
The method of claim 3, wherein the collection difficulty calculation unit for each area
According to the housing type in the specific area, in the case of single-family houses, the above priority is given in the order of collection points, emissions, road width, moving distance and road slope, and in the case of apartment houses, collection points, moving distances, emissions, roads Food waste management support apparatus, characterized in that the priority is given in the order of width and road inclination.
The method of claim 1, wherein the recommended collection path determining unit
As a pre-processing step of the network analysis, a first step of refining a road name address basic map to generate links between nodes constituting a road network, a second step of assigning a weight to each link of the road network according to a slope and a third step of assigning an average travel time for food waste collection to each link to establish a network data set.
The method of claim 5, wherein the recommended collection path determining unit
Based on the network data set, through VRP (Vehicle Route Problem) analysis, the limited capacity, collection time, and length of the collection path of the collection vehicle responsible for collecting the food waste are applied as conditions for food waste collection in the specific area. Food waste management support apparatus, characterized in that deriving an optimal collection path from among a plurality of collection paths.
The method of claim 6, wherein the recommended collection path determining unit
Deriving the average load capacity, average collection time, and average number of operations of collection vehicles for collection routes currently in operation as improvement conditions;
and determining, among the plurality of collection paths, a collection path that satisfies at least two of the improvement conditions as the recommended collection path.
In the method performed in the food waste management support device,
determining the amount of food waste for each building by collecting the current status of food waste in a specific area;
calculating the difficulty of collecting food waste for each area based on the topographic data on the specific area; and
and determining a collection path for food waste collection in the specific area through network analysis based on the amount of food waste for each building and the difficulty of collecting food waste for each area.

Images