KR20230054233A - Method and system of collecting wastes based on big data - Google Patents

Abstract

An objective of the present invention is to efficiently collect and manage waste from a plurality of workplaces. According to one embodiment of the present invention to achieve the objective of the present invention, a method of collecting waste based on big data comprises: a step of receiving waste collection information of at least one workplace from a collector terminal; a step of receiving food menu information and information on the number of people having meals from at least one workplace from a user terminal; a step of outputting a waste discharge amount for each food menu of each workplace by performing big data analysis, in which waste collection information, food menu information, and information on the number of people having meals for each workplace are accumulated from previous collection to current collection work, and predicting the amount of daily waste to be discharged for each workplace based on the waste discharge amount for each food menu of each workplace, food menu schedule plan information after the current collection work, and information on the number of people having meals; a step of generating a collection schedule composed of at least one workplace, of which storage amount of waste in a specific date is predicted to reach limited storage capacity, based on the predicted amount of daily waste to be discharged for each workplace; and a step of calculating a waste collection route for at least one workplace according to the collection schedule based on a departure location of a waste collection vehicle and a final destination thereof to output the same to the collector terminal.

Description

Waste collection method and system based on big data {METHOD AND SYSTEM OF COLLECTING WASTES BASED ON BIG DATA}

The present invention relates to a waste collection method and system based on big data, and more particularly, to a waste collection method based on big data that enables a manager to efficiently collect waste by business site based on waste discharge information of each business site. and systems.

Various wastes such as household waste, food waste, and recycling products are generated by region, district, business site, or housing type. Accordingly, each local government or business site requests a service company to collect and treat this waste. There is a situation.

Usually, a service company collects wastes in a designated area at a certain time, and performs the waste collection operation when recognizing that the wastes loaded in the business site are full on a regular basis or based on experience. On the other hand, in the case of food waste, waste collection is required more frequently than usual due to problems such as odor and maggots caused by decay in the hot and humid summer. In this case, the waste collection worker of the service company Regardless of the amount, waste is collected mechanically by operating a collection vehicle. That is, since the amount of food waste discharged by workplace and time period is different and the frequency of the collection operation is different, there is a problem in that information about this is absent from the waste collection operator.

In addition, when there are several business sites to collect waste, the waste collection worker collects waste by determining a route based on experience for the waste collection areas among the familiar business sites, but in this case, due to inefficient route setting Distance movement can cause unnecessary fuel consumption of the collection vehicle, and the greater the amount of waste loaded on the collection vehicle, the greater the fuel consumption. There was also a problem that had to be taken into account.

In addition, when there are two or more collection vehicles in a certain area, for efficient collection by business site, the total amount of waste to be collected, the loading limit of collectable waste for each vehicle, the distribution of waste to be collected by vehicle, and the business site to be passed through are set. There were difficulties, and as the wastes were collected without considering them, there was a problem in that more resources were inefficiently consumed to collect the actual wastes.

The present invention has been made to solve the above problems, and an object of the present invention is to analyze big data information on the amount of food waste for each business site and efficiently collect food waste for each business site based on the information.

A big data-based waste collection method according to an embodiment for realizing the above object of the present invention includes the steps of receiving waste collection information from at least one business site from a collector terminal, and from a user terminal from the at least one business site. Receiving food menu information and number of people serving food, analyzing accumulated big data on waste collection information collected by business site from previous collection work to this time, food menu information by business site, and information on number of people drinking water, Outputting the amount of waste discharged by each food menu, and predicting the amount of waste to be discharged by date for each business site based on the amount of waste discharged by food menu for each business site, the food menu schedule plan information after this collection operation, and the number of people drinking water; Generating a collection schedule consisting of at least one or more business sites in which the storage amount of waste on a specific date is predicted to reach a limit storage capacity based on the predicted daily waste emissions by business site, and the departure location and final destination of the waste collection vehicle and calculating a waste collection route for at least one or more workplaces according to the collection schedule and outputting the waste collection route to the collector terminal based on .

In one embodiment of the present invention, the calculation of the waste collection route may be further based on a predicted amount of waste for each business site to be collected and fuel consumption according to the loading amount of waste in the collection vehicle.

In one embodiment of the present invention, when the total amount of waste to be collected for at least one business site on the collection schedule exceeds the loading limit of the collection vehicle, a plurality of collection vehicles may be dispatched.

In one embodiment of the present invention, the plurality of collection vehicles are allocated a business site where the total amount of waste to be collected is within a loading limit range for each vehicle based on the departure location and final destination of each vehicle, and the waste A collection route can be calculated.

In one embodiment of the present invention, the limit storage capacity may be determined by the capacity and number of waste recovery bins possessed by each workplace.

In one embodiment of the present invention, the limit storage capacity is variable according to time, and is determined by the average amount of waste for each time period collected according to the application information for waste collection for each business site received from the at least one business site. can

In one embodiment of the present invention, the location information of the collection vehicle is grasped in real time based on a GPS signal, and whether or not the collection vehicle is moving according to the collection route calculated for each collection vehicle and the collection operation according to the collection schedule Whether this is being done can be monitored.

In one embodiment of the present invention, when the collection vehicle deviates from a collection route or a collection operation is not performed according to a collection schedule, a notification may be notified through the collector terminal.

In one embodiment of the present invention, at least one of waste discharge information by food menu for each business site and waste discharge information obtained by comparing and analyzing the amount of waste discharged compared to food menus of other business sites may be output to the user terminal for each business site.

In the big data-based waste collection system according to an embodiment for realizing the object of the present invention, a user terminal, a collector terminal connected to a collection vehicle for collecting waste, and communication with the user terminal and the collector terminal A connected central server, wherein the central server receives waste collection information from at least one business site from a collector terminal, and receives food menu information and number of people serving food from the at least one business site from a user terminal; By performing accumulated big data analysis on the waste collection information collected by business site from the previous collection work to the current collection job, food menu information by business site, and information on the number of people drinking water, the amount of waste discharged by food menu by business site is output, and the business site Waste information analysis unit that predicts the amount of waste to be discharged by business site by day based on the amount of waste by food menu, food menu schedule plan information after this collection operation, and number of people drinking water, based on the predicted waste emissions by business site by day a collection scheduling unit that generates a collection schedule consisting of at least one or more business sites in which the storage amount of waste on a specific date is predicted to reach the limit storage capacity; and the collection schedule based on the departure location and final destination of the waste collection vehicle. and a collection route calculation unit for calculating a waste collection route for at least one business site according to the above.

According to the present invention, it is possible to efficiently collect and manage wastes from a plurality of workplaces by analyzing big data information on the amount of food waste discharged from each workplace and setting a collection schedule and collection route for waste collection for each workplace.

In addition, if two or more collection vehicles are dispatched in a certain area due to the large amount of waste, the amount of waste to be collected by vehicle is allocated considering the total amount of waste to be collected and the loading limit of the waste that can be collected by each vehicle. , Based on this, it is possible to efficiently collect waste using limited resources by setting the business site to be passed by each vehicle.

In addition, information on the amount of waste discharged by business site is delivered to each user, the amount of waste discharged by period and the number of people drinking water are analyzed, and the expected amount of food material to be purchased is recommended to the user, thereby reducing food material consumption and food waste generation.

1 is a configuration diagram for explaining a waste collection system according to an embodiment of the present invention.
FIG. 2 is a block diagram for explaining the configuration of the central server of FIG. 1 .
FIG. 3 is a block diagram illustrating a customer management unit of FIG. 1 .
Figure 4 is a block diagram for explaining the waste analysis management unit of FIG.
FIG. 5 is an exemplary diagram for explaining the collection path calculating unit shown in FIG. 2 .
6 is a flowchart schematically illustrating a big data-based waste collection method according to an embodiment of the present invention.

Since the present invention may have various changes and various forms, specific embodiments are illustrated in the drawings and described in detail in the text. However, it should be understood that this is not intended to limit the present invention to the specific disclosed form, and includes all modifications, equivalents, and substitutes included in the spirit and scope of the present invention.

Meanwhile, the meaning of terms described in this application should be understood as follows. Terms such as "first" and "second" are used to distinguish one component from another, and the scope of rights should not be limited by these terms. For example, a first element may be termed a second element, and similarly, a second element may be termed a first element.

Expressions in the singular number should be understood to include plural expressions unless the context clearly dictates otherwise, and terms such as “comprise” or “have” refer to an embodied feature, number, step, operation, component, part, or these. It should be understood that it is intended to indicate that a combination exists, and does not preclude the possibility of the presence or addition of one or more other features, numbers, steps, operations, components, parts, or combinations thereof.

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

Hereinafter, preferred embodiments of the present invention will be described in more detail with reference to the drawings.

1 is a configuration diagram for explaining a waste collection system according to an embodiment of the present invention. FIG. 2 is a block diagram for explaining the configuration of the central server of FIG. 1 . FIG. 3 is a block diagram illustrating a customer management unit of FIG. 1 . Figure 4 is a block diagram for explaining the waste analysis management unit of FIG.

1 to 4, the waste collection system 1000 of the present invention is a business owner or waste manager (hereinafter referred to as a "user") of a business that discharges food waste (hereinafter referred to as "waste"). ) owned by the user terminal (100; 100a to 100c), a manager of a service company that collects food waste and transports it to a waste collection point or waste disposal site, or a person who operates a waste collection vehicle and wants to collect waste within the waste collection system ( It communicates with the collector terminal 200 owned by (hereinafter, referred to as "the collector"), the user terminal 100 (100a to 100c), and the collector terminal 200 through a network, and accumulates waste for each business site. It includes a central server 300 that performs scheduling work for waste collection through big data analysis using data, calculates the dispatch of collection vehicles and the collection route of the collection vehicles, and transmits the results to the collector terminal 200.

The user terminal 100 is a computer or portable terminal owned by a user who wants to collect waste from a business owned or managed by the user through the waste collection system 1000, and the user can access the web, app ( Member registration can be performed by communicating with the central server 300 through the network 10 in the form of an Application) or a web app.

In addition, the user can select, through the user terminal 100, whether to collect the waste according to a waste collection method, for example, according to a collection schedule determined by the waste collection system, or through application at a desired time. In addition, the collection cost is calculated based on either the volume or weight of the collected waste, and the payment and payment details can be checked. However, in the case of an initial user who has signed up as a member of the waste collection system of the present invention, since there is no information on waste discharge in the waste collection system, it is fixed in a way that collection is performed through application at a desired time, and data to a certain extent is accumulated. After that, it is desirable to determine the waste collection method by the user's choice.

In addition, the user may be provided with waste information about the amount or weight of waste discharged each time waste is collected through the user terminal 100, and by inputting food menu information and number of people drinking water through the user terminal 100, waste It is possible to receive the estimated number of people to drink and the expected purchase amount of food materials for each food menu analyzed in the collection system, and an estimate of saving food materials and reducing waste generation accordingly.

The collector terminal 200 is a computer or portable terminal that is installed in a collection vehicle or owned by the collector, and the collector terminal 200 collects information through the network 10 in the form of a web, application, or web app. It is configured to communicatively connect to the central server (300). Hereinafter, for convenience, the collector terminal 200 will be described as a portable terminal owned by the collector, but it may be a collection vehicle itself that communicates directly with the central server 300, or it may be installed in the collection vehicle to determine whether or not the vehicle is abnormal, It may be a communication device capable of obtaining vehicle information such as fuel consumption measurement. The collection vehicle is assumed to collect waste collection containers for each workplace, but is not limited thereto.

The collector terminal 200 is configured to transmit and receive information to and from the central server 300 of the waste collection system 1000 while being attached to the vehicle. For example, the central server 300 calculates business site information, which is a scheduled waste collection target, assigned to a collection vehicle according to a collection schedule, and a collection route for efficient collection, and sends the information to the collector terminal 200. . The collector terminal 200 transmits the current location of the collection vehicle to the central server 300 based on the GPS signal, and records the amount of waste collected at the business site in units of volume or weight, and returns to the central server 300. configured to be sent to In addition, the fuel information of the vehicle used for the entire collection route or for each section is also transmitted to the central server 300 .

The information received from the collector terminal 200 is databased into information for each collection vehicle, waste information for each business site, and traffic information for each road on the collection route, and is stored and managed in the central server 300 .

In addition, in the case of a waste collection system in which the collector is paid according to performance, the collector may send performance information such as working hours, used fuel, and amount of work to the central server 300 through the collector terminal 200. There is, and you can be paid a daily wage or reward accordingly. That is, the reward received from the central server 300 may be displayed on the collector terminal 200 .

On the other hand, the portable terminal is, for example, a wireless communication device that ensures portability and mobility, and includes a smartphone, a personal communication system (PCS), a global system for mobile communication (GSM), a personal digital cellular (PDC), PHS (Personal Handyphone System), PDA (Personal Digital Assistant), IMT (International Mobile Telecommunication)-2000, CDMA (Code Division Multiple Access)-2000, W-CDMA (W-Code Division Multiple Access), Wibro (Wireless Broadband Internet ) may include all types of handheld-based wireless communication devices such as terminals. The computer includes, for example, a desktop, a laptop, a tablet PC, and the like equipped with a web browser.

In addition, the network 10 connecting the user terminal 100 and the collector terminal 200 and the central server 300 includes a local area network (LAN), a wide area network (WAN) ), Value Added Network (VAN), Personal Area Network (PAN), mobile radio communication network, Wibro (Wireless Broadband Internet), Mobile WiMAX, HSDPA (High Speed Downlink Packet Access) ) or all kinds of wired/wireless networks such as satellite communication networks.

The central server 300 is configured to communicate with the user terminal 100 and the collector terminal 200 through the network 10, and receives information received from the user terminal 100 and the collector terminal 200. The information is databased into waste information by business site, information by collection vehicle, traffic information by road on the collection route, and the like, and is stored and managed in the central server 300 . The databased information predicts the collection schedule for each business site’s waste emissions and collection date through big data analysis by the waste analysis and management department, which will be described later, and calculates a list of business sites that are subject to collection for effective waste collection, and dispatches vehicles accordingly And, when a plurality of vehicles are dispatched, a work load for each vehicle is allocated, and a collection route for the assigned workplace is calculated.

Hereinafter, the central server 300 according to the present embodiment will be described in detail with reference to FIGS. 2 to 4 .

2 to 4, the central server 300 includes an information receiving unit 310, a customer management unit 320, a collection vehicle management unit 330, a waste information analysis unit 340, a collection scheduling unit 350, It includes a collection path calculation unit 360, a collection information management unit 370, a payment processing unit 380 and an information output unit 390.

The information receiver 310 is configured to receive information from the user terminal 100 and the collector terminal 200 through the network 10 . For example, the information receiver 310 is configured to communicate with the user terminal 100 and the collector terminal 200 to receive customer information including basic information through membership registration.

In addition, the information receiving unit 310 is configured to receive workplace information managed by the user, for example, food menu information, information on the number of people drinking water, etc. from the user terminal 100, and to receive a waste collection request. do. In addition, it is configured to receive collected waste information, collection vehicle location information, consumed fuel information, and the like for each business site from the collector terminal 200 .

The customer management unit 320 registers and manages a user of at least one or more workplaces who wants to use the waste collection service in the waste collection system 1000 and at least one or more collectors who perform waste collection as customers. For example, the customer management unit 320 may include a user management module 321 that stores and manages registration information of a user and a collector management module 323 that stores and manages registration information of a collector.

The user management module 321 stores and manages user information including basic information such as the user's company name, manager name, contact information, and e-mail address input from the user terminal 100, and when the user signs up as a member, A user identification code is assigned to each user, matched with the entered user information, and stored and managed in the customer DB. The user information may include, in addition to the basic information, information on the amount of waste collected by the collection information management unit 370 to be described later, a cost calculated based on a pre-contracted standard for the amount of collected waste, and payment information therefor. there is. Alternatively, each information may be stored and managed in a collection information DB and a payment information DB, respectively.

The collector management module 323 includes the collector's company name, name, owned vehicle information, loading limit for each vehicle, number of vehicles information, address, management area information, contact information, and mail of the collector input from the collector terminal 200. Collector information including basic information such as address is stored and managed. When a collector signs up as a member, an identification code is assigned to each recipient, matched with the entered information for each recipient, and stored and managed in the customer DB. Information managed for each collection vehicle by the collection vehicle manager to be described later is matched and stored with the collector information, and through analysis of the information, characteristic information of the collector may be further stored and managed.

Also, the collector management module 323 may store and manage performance information on waste collection for each collector, and store and manage compensation based on performance as reward information. Corresponding reward information may be amount information, and separate account number information may be further added for reward compensation processing.

In addition, one embodiment of the present invention has been described as an example in which the customer management unit 320 stores and manages users and collectors in a customer DB, but is not limited thereto, and may be managed through separate DBs. In addition, this embodiment has been described as an example of managing information in different modules by distinguishing users and collectors, but is not limited thereto. For example, the customer management unit 320 may register, integrate, and manage customers regardless of classification. In this case, when the user and the collector access the central server 300 and log in, the customer management unit 320 checks whether or not the accessing person is a customer. Depending on whether or not the user is a collector, interfaces displayed on the user terminal 100 and the collector terminal 200 may be switched to receive a corresponding service.

The collection vehicle management unit 330 controls the collection vehicle operated by the collector through the collector terminal 200, collects waste information for each business site received from the collector terminal 200, and various operations related to the operation of the collection vehicle. It is configured to receive and manage information. The various types of information are stored and managed by assigning a vehicle identification code to each collected vehicle and matching with the collected person information.

For example, the collection vehicle management unit 330 determines the location information of the collection vehicle in real time based on a GPS signal, determines whether the collection vehicle is moving according to the collection route calculated for each vehicle, and performs the task according to a predetermined schedule. You can check if it is working or not. If the collection vehicle deviates from the collection route or the work is not performed according to a predetermined schedule, a notification may be notified to the collector through the information output unit described below to the collector's terminal. In addition, the collection vehicle management unit 330 may extract and manage working hours based on the location holding time for each business site based on the GPS signal.

The collection vehicle management unit 330 is configured to dispatch a collection vehicle to collect wastes according to the collection schedule when a collection schedule for a business site to be collected is created in a collection scheduling unit described below. The dispatch is based on the location of the waiting location of the collection vehicle and the location of the waste collection point or disposal site where the waste to be collected is unloaded. In addition, for equal allocation, the number of times of dispatch during a certain period of time or the amount of work for each business site may be considered, and the number of available collection personnel at the time of collection may be considered.

In addition, if there is an area managed by each service company, or if there is a contractual relationship with a specific service company for each business site, the specific service company is notified to dispatch vehicles to the specific area or specific business site according to the collection schedule. In contrast, when a business site does not designate a separate service company by region or according to contractual relationships, a suitable collection vehicle is dispatched according to the collection schedule generated by the collection vehicle management unit 330 .

In addition, the collection vehicle management unit 330 receives vehicle data for each collection vehicle, receives and manages the current amount of fuel and the amount of fuel consumed for total waste collection and section-by-section according to the collection route, and also records driving. and based on big data analysis thereof, an operation guide for minimum fuel consumption may be notified to the collection vehicle, and the minimum amount of fuel required to collect wastes according to the collection route may be notified to the collector terminal 200. can

For example, big data analysis may be performed by providing at least one of a 3D analysis graph including accelerator pedal, rpm, and fuel consumption from a collection vehicle, and a 2D analysis graph including engine speed and mileage. . The 3D analysis graph assigns each coordinate axis to the accelerator pedal, rpm, and fuel consumption, and shows 3D bars according to the matching of the three-axis coordinate values, and the 2D analysis graph assigns each coordinate axis to the engine speed and travel amount, A 2D dot may be displayed according to matching of 2-axis coordinate values.

As another embodiment of the 2D analysis graph, the vehicle speed according to the type of collection vehicle may be displayed as a 2D bar according to a two-axis table by assigning coordinate axes to vehicle speed and ratio, as in the example of vehicle speed driving characteristic analysis. . In addition, the engine speed and fuel amount may be assigned to respective coordinate axes to the engine speed and the traveling amount, and 2D dots may be displayed according to the matching of the two-axis coordinate values, thereby indicating the driving habit of the collector.

For example, driving data of each collection vehicle and driving data of other collection vehicles subscribed to the waste collection system may be compared and analyzed, and based on the result, information on the driving habits of the collector of a specific collection vehicle may be provided. For example, if the driving data of other collection vehicles is stored in large quantities in the DB and the driving data of a specific collection vehicle is entered into the waste collection system, the waste collection system will drive other collection vehicles close to the driving data of the specific collection vehicle in the DB. It is possible to predict the driving habits of other collection vehicles analyzed by searching the data and using the driving data of other collection vehicles as the driving habits of the specific collection vehicle collector.

In addition, the collection vehicle management unit 330 manages control information such as vehicle management, data management, driving data analysis, vehicle movement path, location confirmation, etc., and performs waste information analysis for each vehicle performance information for the waste collection record, which will be described later. It can be provided to unit 340. For example, when a lot of waste is loaded into a vehicle, the overall weight of the collection vehicle increases, so the performance of the collection vehicle inevitably deteriorates. A collection route calculation unit to be described below may calculate a collection route for collecting waste for each vehicle based on the amount of fuel consumed according to the route.

In addition, the collection vehicle management unit 330 acquires collection vehicle information, displays an engine oil exchange message to the collector through consumables management and maintenance linked services of the vehicle, and a message notification, and opens a repair shop guide search window. It can also float and guide the collection vehicle to the nearest repair shop. In this embodiment, it has been described that the analysis information related to the collection vehicle operation is performed by the collection vehicle management unit 330 as an example, but is not limited thereto. For example, a separate module or the description below may be performed in the big data analysis unit 343 of the waste information analysis unit 340.

The waste information analysis unit 340 analyzes the accumulated big data on the waste collection information collected by business site from the previous collection operation to the current collection operation, the food menu information by business site, and the number of people drinking water, and the food menu by business site. It is configured to output the amount of waste discharged by each place of business, and predict the amount of waste to be discharged by date by place of business based on the amount of waste discharged by food menu by place of business, food menu schedule plan information after this collection operation, and information on the number of people drinking water. The waste information analysis unit 340 includes an information collection unit 341, a big data analysis unit 343 and a waste amount prediction unit 345.

The information collection unit 341 receives from the user terminal 100 and collects food menu information for each business site managed by the customer management unit 320, information on the number of people drinking water, and application information for waste collection through the user terminal, , is received from the collector terminal 200, and information on the volume or weight of collected wastes for each business site managed by the collection information management unit described later and time spent in the collection operation are collected. Also, the information collection unit 341 may collect waste collection work and information generated during the process from a user terminal or a collector terminal.

The collected information can be automatically stored in an integrated database, waste information for each business site can be distinguished from information on all collected wastes, and backup can be maintained with NAS, a mass storage device for recovery in the event of a failure.

The big data analysis unit 343 analyzes waste information collected for each business site based on the data collected by the information collection unit 341 . Food waste is accumulated and stored after each meal time in a waste collection bin provided at the workplace, but since waste cannot be collected at every time, it is impossible to accurately predict the amount of food menu and amount of waste compared to the number of people drinking water. Therefore, the big data analysis unit of the present invention, based on the amount of waste collected for each period from the previous collection day to the next collection day, considers the food menu and the number of people drinking during the period, food menu and number of people drinking for each business site The purpose is to predict the amount of waste that will be discharged. Usually, the food menu for each business site is repeated, and the number of people drinking water tends to be maintained at a certain number without significant change. Therefore, the big data analysis unit 343 calculates the difference in the amount of waste collected for each period, tracks the cause through overlapping food menus and number of people eating and difference food menu information and information on the number of people drinking for each period, and finally It is configured to calculate the average waste discharge by food menu for each business site. In addition, the average amount of waste discharge per day may be output, and in this case, the average amount of waste per day may be corrected within an error range using the amount of waste per food menu.

Meanwhile, waste information for each business site analyzed is transmitted to each user, and food material saving and waste generation can be improved by recommending an expected amount of food material to be purchased to the user. In addition, by providing the amount of waste discharged for each food menu, the user can base the corresponding information when making a food menu schedule plan. Accordingly, the amount of waste generation can be greatly improved. In addition, the amount of waste discharged compared to the food menu of other workplaces subscribed to the waste collection system is compared and analyzed, and waste discharge information of a specific workplace may be provided based on the result. Accordingly, the user can receive help in improving the ingredients or quality of the food menu.

In addition, the big data analysis unit 343 compares and analyzes the amount of waste actually collected based on the amount of waste predicted by the waste amount prediction unit 345 to be described later, calculates an error in predicting the amount of waste, and analyzes the cause. is configured to For example, when a specific food menu is newly added, or when the number of people serving is greatly increased, the predictable cause is analyzed thereby, or the amount of waste collected is predicted even though the food menu or the number of people serving is the same as before. If the amount is out of the error range, the result is notified to the user, information on the improved matter is obtained, and whether it is a temporary phenomenon or whether it is reflected in future analysis is determined. For example, if it is a result of a user changing food material reorganization to save food material, it should be reflected in future analysis.

The big data analysis unit 343 may include a collection/storage and processor responsible for data processing, and may perform high-speed processing by utilizing a big data platform. Information can be analyzed by storing information in distributed storage from the database and performing data recognition and pre-processing functions for high-speed processing and big data processing function, which is a query generation function for information extraction. The big data analysis unit 343 may include a monitoring module, provide a dash mode for integrated operation management, and configure a screen by classifying collected information in real time. For example, the big data analyzer 343 may monitor in real time the amount of waste collected for each business site received from the terminal of the collector of the collection vehicle.

In addition, the big data analysis unit 343 may include a detailed module for each task, and information generated during the waste collection operation and the process, for example, waste collection operation time, number of available collection vehicles, and waste collection vehicle Fuel consumption according to load capacity, number of waste collection bins per business site, capacity of waste collection bins, information on working hours, information on additional work hours when waste collection bins are dispersed in large businesses, information on collection routes It is possible to analyze hourly traffic information and fuel consumption information according to movement on a specific route. The big data analysis unit 343 analyzes the collection route of the selected business site based on the information based on the premise of minimum fuel consumption.

For example, big data analysis may be performed in a manner of providing at least one of a 3D analysis graph including efficient collection route information and a 2D analysis graph while simulating a collection order for each business site from a collection vehicle. The 3D analysis graph assigns each information to a coordinate axis, shows 3D bars according to the matching of coordinate values on the 3 axes, and the 2D analysis graph also assigns the coordinate axis to each information, and displays 2D dots according to the matching of the coordinate values on the 2 axes. can be shown.

Accordingly, the big data analysis unit 343 sets a collection schedule for collection work, allocates vehicles according to the collection schedule, allocates the amount of waste to be collected for each dispatched vehicle, and wastes, based on simulation and various accumulated data. It is configured to calculate an optimal value for path setting for collection. The big data analysis unit 343 may perform in-memory-based distributed/parallel processing (configuration of multiple servers serving the role of master and slave) by utilizing the RADUCE technique.

The waste amount prediction unit 345 calculates the average amount of waste for each business establishment and each food menu calculated by the big data analysis unit 343, and determines the food menu schedule plan information and expected number of people to eat by business establishments input from the user. Estimate the amount of waste to be discharged per day.

Specifically, the waste amount prediction unit 345 determines the waste discharged by the business site by the collection vehicle. When collected, the amount of discharged waste is reset, and if there is a difference between the collected amount and the predicted amount and the error range, the corresponding information is transmitted to the big data analysis unit 343 for cause analysis. do. In addition, in order to create a schedule for the next collection day, the amount of waste discharge per business site is predicted.

That is, the waste collection system 1000 according to the present embodiment analyzes big data information on the amount of food waste collected for each business site and predicts the amount of waste to be discharged for each business site, thereby efficiently removing waste from a plurality of business sites. can be collected and managed.

The collection scheduling unit 350 is configured to set a waste collection schedule for each business site based on the data analysis result of the big data analysis unit 343 . For example, the collection scheduling unit 350 sets the next collection date from the previous collection date based on the predicted daily waste discharge amount for each workplace. When a specific service company has jurisdiction over multiple workplaces within a certain area, the size of each workplace, the amount of waste discharged by each workplace, the limit storage capacity of waste for each workplace, and the working hours are inevitably different.

For example, when the daily waste discharge of a specific business site is significantly higher than that of other business sites, when waste collection is carried out at the time when the waste limit storage capacity of a specific business site is reached, when considering the loading limit of collectable waste in a collection vehicle, Wastes from other businesses other than the specific business site will not be collected. Accordingly, a collection schedule is created so that the total amount of waste for each business site to be collected is within the loading limit of the collection vehicle, taking into consideration the daily waste discharge from other business sites. That is, the collection scheduling unit 350 generates a collection schedule composed of at least one business site predicted to reach a limit storage capacity of waste on a specific day based on the predicted waste discharge amount by business site and by day. Here, the limit storage capacity is determined by multiplying the capacity and number of waste recovery bins possessed by each workplace, or may be determined as the remaining capacity after subtracting a certain level of free space (capacity) for each recovery bin.

That is, the collection scheduling unit 350 creates a collection schedule by selecting a business site to be collected before the waste limit storage capacity for each business site is reached. For example, the collection scheduling unit 350 may display and manage a graph in which a list of workplaces within a certain area is listed on the x-axis and a predicted daily amount of waste discharge is accumulated on the y-axis. The above graph shows the cumulative amount of waste discharge by business site, and at this time, the collection vehicle has a loading limit of 1 ton that can collect about 20 waste collection containers based on a waste collection container having a capacity of 50L. If there is, select workplaces that have discharged accumulated waste predicted in the range of 1 ton.

For example, when the cumulative amount of waste from the first business site predicted on a specific date is 0.3 ton, the waste from the third business site is 0.4 ton, and the waste from the fourth business site is 0.3 ton, set a specific date as the collection date; The 1st, 3rd, and 4th business sites within the range of 1 ton are selected as the business sites to be collected. Of course, at this time, it is required that at least one or more of the selected business sites have reached the waste limit storage capacity within a predetermined range. For example, even though the first, third, and fourth business sites all have a limit capacity of 1 ton, if waste collection is performed frequently, the efficiency in terms of manpower costs for the collection work decreases, and the number of collection vehicles is increased. Because it has to be driven, fuel consumption is inevitable. Therefore, based on the limit storage capacity of each business site, the business site to be collected is selected based on the business site within a certain range. For example, in the previous example, if the first business site and the third business site are in a state close to the limit storage capacity, the collection target is selected first, and the location information, working time, and fuel to be consumed are based on the first business site and the third business site. In consideration of the information, etc., a fifth business site may be selected to fill the loading limit of the collection vehicle.

For example, set up a collection schedule based on a specific business site that has reached its capacity limit, but does not reach its capacity, but is adjacent to or discharged from that specific business site, when collecting waste, loading of collection vehicles A collection schedule can be created by adding workplaces within the limit range. In this case, the specific business site that is the standard may be a business site with a threshold capacity of waste discharge of a predetermined standard or more, or a business site that is far away from other business sites.

In addition, waste collection does not presuppose that wastes accumulated in all workplaces are made on the same date, that is, reset on the same date. Moreover, it is not assumed that it is the same cycle. That is, in the case of a business site with a small amount of waste compared to the limit storage capacity, the collection cycle may be relatively long, and in the case of a business site with a large amount of waste compared to the limit storage capacity, the collection period may be short.

On the other hand, the limit storage capacity may vary depending on the time. Usually, it is determined by the capacity and number of waste recovery bins for each business site, but in the case of summer when corruption is severe, it can be set to a low range regardless of the capacity and number of waste recovery bins. In addition, the limit storage capacity may be managed differently for each business site even if the same capacity and number of waste recovery bins are maintained. For example, the limit storage capacity may be set based on application information for waste collection received through a user terminal in an initial stage of subscribing to a waste collection system for each business site. For example, if the capacity of the waste collection container is 50L, and the average amount of waste collected according to the application information for waste collection according to the period is 40L, 40L is set as the limit storage capacity to manage the business site. can That is, the limit storage capacity may be determined by the average amount of waste collected at each time according to application information for waste collection for each business site.

In addition, the collection scheduling unit 350. When the total amount of waste to be collected for at least one or more business sites on the collection schedule exceeds the loading limit of the collection vehicle, a plurality of collection vehicles are dispatched. Specifically, when the number of businesses subject to waste collection exceeds a certain level, or when the amount of waste to be collected exceeds the loading limit of the collection vehicle, or when the total travel time and collection work time exceeds the set daily routine, the collection vehicle It is possible to designate more than 2 units of the dispatcher. That is, the collection scheduling unit 350 may set a collection schedule for waste collection in consideration of the number of available collection vehicles based on the big data analysis result. Specifically, when the number of available collection vehicles is small compared to the amount of waste to be collected, the collection cycle may be shortened, and when the number of available collection vehicles is large compared to the amount of waste to be collected, the collection cycle may be adjusted to be long.

The collection route calculation unit 360 is configured to calculate a collection route for the collection vehicle to collect wastes in consideration of the departure location and final destination of the collection vehicle when a business site to be collected is selected. At this time, the collection path calculation unit 360 calculates the amount of waste to be collected for each business site predicted by the big data analysis unit 343, the amount of fuel consumption according to the weight of the loaded waste, and the amount of fuel consumption according to the moving distance. Based on the information-based data analysis result, it is configured to calculate an optimal collection route. On the other hand, the final destination includes a waste disposal site where the waste is treated or a collection point where a certain amount of waste is piled up before being transported to the waste disposal site.

On the other hand, the collection point and the waste disposal site may be operated by a company designated within a jurisdiction that collects waste, or may be a specific company contracted with a collection vehicle. Alternatively, it may be a company registered in the platform, which is the waste collection system of the present invention. In this case, as a collection point or waste disposal site, you can participate in the platform by entering the cost unit price according to the weight of waste storage or treatment, and as a collector, consider fuel consumption and storage and treatment cost unit price according to the amount of movement to the collection point or waste disposal site You can choose a collection point or waste disposal site of your choice. Alternatively, in the waste collection system of the present invention, through big data analysis including information input therefrom, business site allocation and collection routes for each collection vehicle may be calculated.

In addition, the collection route calculation unit 360 allocates a business site to be collected in consideration of the loading limit for each vehicle, the departure location for each vehicle, and the final destination, when a business site for collection is selected and the number of vehicles for collection is two or more. , it is configured to calculate a collection route for collecting waste for each vehicle. In other words, the sum of waste emissions predicted for each business site to be collected by vehicle is allocated within the range of the loading limit for each vehicle. In this regard, it will be described with reference to FIG. 5 .

FIG. 5 is an exemplary diagram for explaining the collection path calculating unit shown in FIG. 2 .

Referring to FIG. 5 , workplaces and collection routes assigned to each vehicle are shown. It is premised that the sum of the estimated waste emissions at the business site assigned to each vehicle is within the range of the loading limit for each vehicle, and the loading limit may be different for each collection vehicle. For example, in the case of the first collection vehicle, a first business site, a third business site, and a fourth business site may be allocated, and in the case of a second collection vehicle, a second business site and a fifth business site may be allocated. In this case, a third collection vehicle may be further dispatched. At this time, the optimal collection route is calculated based on the data analysis results based on the estimated amount of waste to be collected for each business site, fuel consumption according to the weight of the loaded waste, and fuel consumption according to the distance traveled. do. That is, in the case of the first collection vehicle, the waste collection proceeds in the order of the first business site, the third business site, and the fourth business site, and in the case of the second collection vehicle, the waste collection proceeds in the order of the second business site and the fifth business site. is set

In addition, the collection route may include collection time-line information including collection operation time for each business site and travel time information to each business site. For example, based on FIG. 5 , the length of each box for each workplace represents working time, and the distance between boxes for each workplace represents travel time. The collection work time for each business site is based on the data analysis result based on the amount of waste collected for each business site and the collection work time information analyzed by the big data analysis unit 343, compared to the predicted amount of waste to be collected. The collection work time can be calculated and displayed, and the travel time to each business site can be calculated according to the travel route between business sites at a specific time according to the result of analyzing the hourly traffic situation.

The manager of the waste collection system of the present invention can monitor the location of the collection vehicle and the progress of the schedule through the example chart shown in FIG. 5, and the waste collection system works separately from the GPS location information of the collection vehicle. Progress can be received in real time and information can be analyzed. That is, the waste collection system 1000 of the present invention, when the amount of waste is large and two or more collection vehicles are dispatched, considering the total amount of waste to be collected and the loading limit of collectable waste for each collection vehicle, each vehicle By allocating the waste to be collected and setting the business site to be passed by vehicle based on this, it is possible to efficiently collect the waste using limited resources.

The collection information management unit 370 is configured to accumulate, store, and manage information on the date waste was collected for each business site and information on the collected waste. Accordingly, based on the corresponding information, the collection cost may be calculated based on either the volume or weight of the collected waste, and the cost may be claimed. In addition, based on the information, a report analyzing trends in waste emissions by business site is provided to the user.

When the collection information management unit 370 receives a payment success signal from the payment agency server through payment processing in the payment processing unit 380, which will be described later, the collected waste is paid by receiving the signal and matching it with the business place where the payment was made. It is configured to act to store and manage information.

The payment processing unit 380 is configured to process a user's payment for waste collected for each business site managed by the collection information management unit 370 . That is, the payment processing unit 380 outputs a purchase payment window supporting the user's payment to the user terminal, and when payment is made by the user, it proceeds with processing. For example, the user may select and pay only part of the determined collected waste.

In addition, the payment processing unit 380 is configured to communicate with a server of a payment agency when a user requests payment. The payment agency server may be, for example, a server of a credit card company, a mobile phone phone bill, or the like, or a server of a separately affiliated communication company. Through the payment processing unit 380, the user can pay for the collected waste on a cost basis contracted for each business site, for example, in a weight unit or volume unit, or can make a regular payment for a set period. .

For example, when there is an authentication or payment request from the user terminal 100 in cooperation with a payment agency, the payment processing unit 380, through a client program and API linked with the server of the payment agency, Authentication or payment information is transmitted to the server of the payment agency, and authentication and payment procedures are performed on the server of the payment agency. Authentication or payment information such as waste information, payment amount, and payment time is stored. The payment processing unit 380 receives the authentication and payment success signals and stores the same information in a customer DB or a separate payment information DB.

The information output unit 390 is configured to output information to the user terminal 100 and the collector terminal 200 through the network 10 . For example, the information output unit 390 transmits information on the amount of waste for each business site to each user, analyzes the amount of waste for each period and the number of people drinking water, and provides recommended information on the amount of expected food material purchase to the user through the user terminal 100. ) can be provided.

Also, the information output unit 390 may output waste collection performance information for each collector and reward information based on the performance to the collector terminal 200 . In addition, the information output unit 390 outputs corresponding payment information to the user terminal 100 when payment is made by the user, and when a reward for each collector is paid, the information about this is sent to the collector terminal 200. ) can be output.

That is, the waste collection system 1000 according to the present embodiment delivers information on the amount of waste discharged by each business site to each user, analyzes the amount of waste discharged by period and the number of people drinking water, and recommends the expected amount of food material purchase to the user, thereby saving food materials and There is an effect of improving the amount of food waste generated.

6 is a flowchart schematically illustrating a big data-based waste collection method according to an embodiment of the present invention.

1 to 6, the big data-based waste collection method according to the present invention includes the steps of receiving waste collection information for each business site (S100); Receiving food menu information and meal number information (S200); Predicting the amount of waste to be discharged by business site based on big data analysis (S300); Creating a collection schedule for each business site (S400); A step S500 of generating a collection route for at least one or more workplaces according to a collection schedule is included.

In the step of receiving waste collection information for each business site (S100), the collection vehicle operated by the collector is controlled through the collector terminal 200, and the collected waste information and collection vehicle for each business site received from the collector terminal 200 are received. It is configured to receive various driving information related to the driving of the vehicle.

For example, it is possible to determine the location information of collection vehicles in real time based on GPS signals, and to control whether the collection vehicles are moving according to the collection routes calculated for each vehicle and whether work is being performed according to a predetermined schedule. there is. If the collection vehicle deviates from the collection route or the work is not performed according to a predetermined schedule, a notification may be notified to the collector through the information output unit described below to the collector's terminal. In addition, based on the location holding time for each business site based on the GPS signal, it is possible to extract and manage the working time.

In addition, information on the volume or weight of wastes collected for each business site and the time required for the collection operation are collected from the collector terminal 200 . In addition, waste collection work and information generated during the process may be received from a user terminal or a collector terminal.

In the step of receiving the food menu information and the number of people serving food (S200), business information managed by the user from the user terminal 100, for example, food menu information, information about the number of people eating, etc. is received, and waste is collected. It is configured to receive an application for.

Based on the amount of waste collected for each period from the previous collection day to the next collection day, the purpose is to predict the amount of waste discharged compared to the food menu and number of people drinking for each business site, considering the food menu and number of people drinking during the period to be Usually, the food menu for each business site is repeated, and the number of people drinking water tends to be maintained at a certain number without significant change. That is, food menu information corresponding to the amount of waste collected for big data analysis and information on the number of people to eat are received, and food menu schedule planning information and expected number of people to eat are input from the user to predict the amount of waste to be discharged for each business site. receive

In addition, the user can select, through the user terminal 100, whether to collect the waste according to a waste collection method, for example, according to a collection schedule determined by the waste collection system, or through application at a desired time. there is. However, in the case of an initial user who has signed up as a member of the waste collection system of the present invention, since there is no information on waste discharge in the waste collection system, it is fixed in a way that collection is performed through application at a desired time, and data to a certain extent is accumulated. After that, it is desirable to determine the waste collection method by the user's choice.

In the step of estimating the amount of waste to be discharged by business site based on big data analysis (S300), food menu information for each business site received from the user terminal 100, information on the number of people drinking water, and each business site received from the collector terminal 200 Based on the collected waste information, big data analysis is performed, and accordingly, the average amount of waste discharge per food menu for each workplace and the amount of waste discharge per day are output, and food menu schedule planning information input from the user terminal 100, Based on the predicted number of people drinking water, it is configured to predict the amount of waste to be discharged for each business site.

First, food menu information for each business site received from the user terminal 100 and managed by the customer management unit 320, information on the number of people drinking water, and waste collection application information are collected through the user terminal and managed by the collection information management unit. Collect information on the volume or weight of waste collected by business site and the time spent in the collection operation. In addition, waste collection work and information generated during the process may be collected from a user terminal or a collector terminal.

The collected information can be automatically stored in an integrated database, waste information for each business site can be distinguished from information on all collected wastes, and backup can be maintained with NAS, a mass storage device for recovery in the event of a failure.

In the big data analysis step, collected waste information for each business site is analyzed based on the collected data. Food waste is accumulated and stored after each meal time in a waste collection bin provided at the workplace, but since waste cannot be collected at every time, it is impossible to accurately predict the amount of food menu and amount of waste compared to the number of people drinking water. Therefore, the big data analysis unit of the present invention, based on the amount of waste collected for each period from the previous collection day to the next collection day, considers the food menu and the number of people drinking during the period, food menu and number of people drinking for each business site The purpose is to predict the amount of waste that will be discharged. Usually, the food menu for each business site is repeated, and the number of people drinking water tends to be maintained at a certain number without significant change. Therefore, in the big data analysis step, the difference in the amount of waste collected for each period is calculated, the cause is tracked through overlapping food menus and the number of people eating and the difference between food menu information and number of people eating, and finally food for each business site. It is configured to calculate the average waste discharge by menu.

Meanwhile, waste information for each business site analyzed is transmitted to each user, and food material saving and waste generation can be improved by recommending an expected amount of food material to be purchased to the user. In addition, by providing the amount of waste discharged for each food menu, the user can base the corresponding information when making a food menu schedule plan. Accordingly, the amount of waste generation can be greatly improved. In addition, the amount of waste discharged compared to the food menu of other workplaces subscribed to the waste collection system is compared and analyzed, and waste discharge information of a specific workplace may be provided based on the result. Accordingly, the user can receive help in improving the ingredients or quality of the food menu.

In addition, the big data analysis step is configured to compare and analyze the amount of waste actually collected based on the predicted amount of waste, calculate an error in predicting the amount of waste, and analyze the cause. For example, when a specific food menu is newly added, or when the number of people serving is greatly increased, the predictable cause is analyzed thereby, or the amount of waste collected is predicted even though the food menu or the number of people serving is the same as before. If the amount is out of the error range, the result is notified to the user, information on the improved matter is obtained, and whether it is a temporary phenomenon or whether it is reflected in future analysis is determined. For example, if it is a result of a user changing food material reorganization to save food material, it should be reflected in future analysis.

The big data analysis step may include a collection/storage and processor responsible for data processing, and high-speed processing may be performed using a big data platform. Information can be analyzed by storing information in distributed storage from the database and performing data recognition and pre-processing functions for high-speed processing and big data processing function, which is a query generation function for information extraction. The big data analysis unit 343 may include a monitoring module, provide a dash mode for integrated operation management, and configure a screen by classifying collected information in real time. For example, the big data analyzer 343 may monitor in real time the amount of waste collected for each business site received from the terminal of the collector of the collection vehicle.

In addition, the big data analysis step may include a detailed module for each task, and information generated during the waste collection operation and the process, for example, the waste collection operation time, the number of available collection vehicles, and the amount of waste in the collection vehicle fuel consumption, number of waste collection bins by business site, capacity of waste collection bins, information on working hours, in the case of large workplaces, additional work time information when waste collection bins are dispersed, hourly traffic in setting collection routes Information, fuel consumption information according to movement of a specific route, etc. can be analyzed. That is, based on the above information, it is possible to analyze the collection route of the selected business site on the premise of minimum fuel consumption.

For example, big data analysis may be performed in a manner of providing at least one of a 3D analysis graph including efficient collection route information and a 2D analysis graph while simulating a collection order for each business site from a collection vehicle. The 3D analysis graph assigns each information to a coordinate axis, shows 3D bars according to the matching of coordinate values on the 3 axes, and the 2D analysis graph also assigns the coordinate axis to each information, and displays 2D dots according to the matching of the coordinate values on the 2 axes. can be shown.

Accordingly, in the big data analysis step, based on simulation and various accumulated data, a collection schedule for collection work is set, vehicles are dispatched according to the collection schedule, waste amount to be collected for each dispatched vehicle is allocated, and waste collection is performed. It is configured to calculate an optimal value for route setting and the like.

Based on this, in the big data analysis step, the amount of waste to be discharged for each business site is predicted from food menu schedule planning information and expected number of people to eat food input from the user, based on the calculated average waste amount for each food menu for each business site.

Specifically, the waste discharged by business site is collected by a collection vehicle. When it is collected, the amount of waste discharged is reset, and if there is a difference between the amount collected and the predicted amount and beyond the error range, the information becomes the basis for analysis again for the cause analysis, and the result is update In addition, in order to create a schedule for the next collection day, the amount of waste discharge per business site is predicted.

In the step of generating the collection schedule for each business site (S400), the waste collection schedule for each business site is set based on the predicted amount of waste to be discharged by business site and date based on the data analysis result in the big data analysis step. That is, the next collection date is set from the previous collection date based on the predicted daily waste emissions by business site. When a specific service company has jurisdiction over multiple workplaces within a certain area, the size of each workplace, the amount of waste discharged by each workplace, the limit storage capacity of waste for each workplace, and the working hours are inevitably different. For example, when the daily waste discharge of a specific business site is significantly higher than that of other business sites, when waste collection is carried out at the time when the waste limit storage capacity of a specific business site is reached, when considering the loading limit of collectable waste in a collection vehicle, Wastes from other businesses other than the specific business site will not be collected. Accordingly, a collection schedule is created so that the total amount of waste for each business site to be collected is within the loading limit of the collection vehicle, taking into consideration the daily waste discharge from other business sites. That is, a collection schedule consisting of at least one business site predicted to reach the limit storage capacity of waste on a specific date is generated based on the predicted waste discharge amount for each business site and each day.

That is, in the step of creating a collection schedule, a collection schedule is created by selecting a business site to be collected prior to reaching the limit storage capacity of wastes for each business site. For example, a graph in which a list of workplaces within a certain area is listed on the x-axis and predicted daily waste emissions are accumulated on the y-axis can be displayed and managed. The above graph shows the cumulative amount of waste discharge by business site, and at this time, the collection vehicle has a loading limit of 1 ton that can collect about 20 waste collection containers based on a waste collection container having a capacity of 50L. If there is, select workplaces that have discharged accumulated waste predicted in the range of 1 ton.

For example, when the cumulative amount of waste from the first business site predicted on a specific date is 0.3 ton, the waste from the third business site is 0.4 ton, and the waste from the fourth business site is 0.3 ton, set a specific date as the collection date; The 1st, 3rd, and 4th business sites within the range of 1 ton are selected as the business sites to be collected. Of course, at this time, it is required that at least one or more of the selected business sites have reached the waste limit storage capacity within a predetermined range. For example, even though the first, third, and fourth business sites all have a limit capacity of 1 ton, if waste collection is performed frequently, the efficiency in terms of manpower costs for the collection work decreases, and the number of collection vehicles is increased. Because it has to be driven, fuel consumption is inevitable. Therefore, based on the limit storage capacity of each business site, the business site to be collected is selected based on the business site within a certain range. For example, in the previous example, if the first business site and the third business site are in a state close to the limit storage capacity, the collection target is selected first, and the location information, working time, and fuel to be consumed are based on the first business site and the third business site. In consideration of the information, etc., a fifth business site may be selected to fill the loading limit of the collection vehicle.

For example, set up a collection schedule based on a specific business site that has reached its capacity limit, but does not reach its capacity, but is adjacent to or discharged from that specific business site, when collecting waste, loading of collection vehicles A collection schedule can be created by adding workplaces within the limit range. In this case, the specific business site that is the standard may be a business site with a threshold capacity of waste discharge of a predetermined standard or more, or a business site that is far away from other business sites.

In addition, waste collection does not presuppose that wastes accumulated in all workplaces are made on the same date, that is, reset on the same date. Moreover, it is not assumed that it is the same period. That is, in the case of a business site with a small amount of waste compared to the limit storage capacity, the collection cycle may be relatively long, and in the case of a business site with a large amount of waste compared to the limit storage capacity, the collection period may be short.

On the other hand, the limit storage capacity may vary depending on the time. Usually, it is determined by the capacity and number of waste recovery bins for each business site, but in the case of summer when corruption is severe, it can be set to a low range regardless of the capacity and number of waste recovery bins. In addition, the limit storage capacity may be managed differently for each business site even if the same capacity and number of waste recovery bins are maintained. For example, the limit storage capacity may be set based on application information for waste collection received through a user terminal in an initial stage of subscribing to a waste collection system for each business site. For example, if the capacity of the waste collection container is 50L, and the average amount of waste collected according to the application information for waste collection according to the period is 40L, 40L is set as the limit storage capacity to manage the business site. can

In addition, in the step of generating the collection schedule, when the total amount of waste to be collected for at least one business site on the collection schedule exceeds the loading limit of the collection vehicle, a plurality of collection vehicles are dispatched. Specifically, when the number of businesses subject to waste collection exceeds a certain level, or when the amount of waste to be collected exceeds the loading limit of the collection vehicle, or when the total travel time and collection work time exceeds the set daily routine, the collection vehicle It is possible to designate more than 2 units of the dispatcher. That is, the collection scheduling unit 350 may set a collection schedule for waste collection in consideration of the number of available collection vehicles based on the big data analysis result. Specifically, when the number of available collection vehicles is small compared to the amount of waste to be collected, the collection cycle may be shortened, and when the number of available collection vehicles is large compared to the amount of waste to be collected, the collection cycle may be adjusted to be long.

In the step of creating a collection route for at least one business site according to the collection schedule (S500), if a business site to be collected is selected, a collection route for the collection vehicle to collect wastes is determined in consideration of the departure location and final destination of the collection vehicle. configured to produce At this time, based on the results of data analysis based on the amount of waste to be collected for each business site predicted by the big data analysis unit 343, the amount of fuel consumption according to the weight of the loaded waste, and the amount of fuel consumption according to the distance traveled , configured to calculate the optimal collection route. On the other hand, the final destination includes a waste disposal site where the waste is treated or a collection point where a certain amount of waste is piled up before being transported to the waste disposal site.

On the other hand, the collection point and the waste disposal site may be operated by a company designated within a jurisdiction that collects waste, or may be a specific company contracted with a collection vehicle. Alternatively, it may be a company registered in the platform, which is the waste collection system of the present invention. In this case, as a collection point or waste disposal site, you can participate in the platform by entering the cost unit price according to the weight of waste storage or treatment, and as a collector, consider fuel consumption and storage and treatment cost unit price according to the amount of movement to the collection point or waste disposal site You can choose a collection point or waste disposal site of your choice. Alternatively, in the waste collection system of the present invention, through big data analysis including information input therefrom, business site allocation and collection routes for each collection vehicle may be calculated.

In addition, in the step of creating a collection route for at least one or more business sites according to the collection schedule (S500), the business site to be collected is selected, and if there are two or more collection vehicles, the loading limit for each vehicle, the departure location for each vehicle, and the final It is configured to allocate a business site for collection in consideration of a destination, and to calculate a collection route for collecting waste for each vehicle. In other words, the sum of waste emissions predicted for each business site to be collected by vehicle is allocated within the range of the loading limit for each vehicle.

According to the present invention, it is possible to efficiently collect and manage wastes from a plurality of workplaces by analyzing big data information on the amount of food waste discharged from each workplace and setting a collection schedule and collection route for waste collection for each workplace.

In addition, if two or more collection vehicles are dispatched in a certain area due to the large amount of waste, the amount of waste to be collected by vehicle is allocated considering the total amount of waste to be collected and the loading limit of the waste that can be collected by each vehicle. , Based on this, it is possible to efficiently collect waste using limited resources by setting the business site to be passed by each vehicle.

The big data-based waste collection method according to an embodiment described with reference to FIG. 6 may be implemented in the form of a recording medium including instructions executable by a computer, such as an application or program module executed by a computer. . Computer readable media can be any available media that can be accessed by a computer and includes both volatile and nonvolatile media, removable and non-removable media. Also, computer readable media may include all computer storage media. Computer storage media includes both volatile and nonvolatile, removable and non-removable media implemented in any method or technology for storage of information such as computer readable instructions, data structures, program modules or other data.

The above-described big data-based waste collection method according to an embodiment of the present invention may be executed by an application basically installed in the terminal (this may include a program included in a platform or operating system basically loaded in the terminal). and may be executed by an application (that is, a program) directly installed in the master terminal by a user through an application providing server such as an application store server, an application or a web server related to the corresponding service. In this sense, the big data-based waste collection method according to the present invention according to one embodiment of the present invention described above is implemented as an application (ie, a program) that is basically installed in the terminal or directly installed by the user, and It can be recorded on a computer-readable recording medium.

The above description of the present invention is for illustrative purposes, and those skilled in the art can understand that it can be easily modified into other specific forms without changing the technical spirit or essential features of the present invention. will be. Therefore, the embodiments described above should be understood as illustrative in all respects and not limiting. For example, each component described as a single type may be implemented in a distributed manner, and similarly, components described as distributed may be implemented in a combined form.

1000: waste collection system
100: user terminal
200: collector terminal
300: central server
310: information receiver
320: customer management department
330: collection vehicle management department
340: waste information analysis unit
350: collection scheduling unit
360: collection route calculation unit
370: collection information management department
380: payment processing unit
390: information output unit

Claims (9)

In the big data-based waste collection method,
Receiving waste collection information from at least one business site from a collector terminal;
Receiving food menu information and information on the number of people who eat food from the at least one business place from a user terminal for each business place;
By performing accumulated big data analysis on the waste collection information collected by business site from the previous collection work to the current collection job, food menu information by business site, and information on the number of people drinking water, the amount of waste discharged by food menu by business site is output, and the business site Predicting the amount of waste to be discharged by business site and date based on the amount of waste by food menu, food menu schedule planning information after this collection operation, and information on the number of people drinking;
Collecting waste from a business site in which the storage amount of waste on a specific date is predicted to reach a limit storage capacity, based on the predicted waste discharge amount by day for each business site; and
A waste collection method comprising outputting at least one of waste discharge information by food menu for each business site and waste discharge information obtained by comparing and analyzing the amount of waste discharged compared to food menus of other business sites to a user terminal for each business site. According to claim 1,
The step of collecting waste from the workplace,
generating a collection schedule consisting of at least one or more business sites predicted to reach a limit storage capacity of the waste storage on the specific date; and
and calculating a waste collection route for at least one business site according to the collection schedule based on a departure location and a final destination of the waste collection vehicle and outputting the result to the collector terminal. According to claim 2,
The waste collection method according to claim 1 , wherein the calculation of the waste collection route is further based on a predicted amount of waste for each business site to be collected and fuel consumption according to a waste loading amount of a collection vehicle. According to claim 2,
Wherein a plurality of collection vehicles are dispatched when the total amount of waste to be collected for at least one business site on the collection schedule exceeds a loading limit of the collection vehicle. According to claim 4,
In the plurality of collection vehicles, based on the departure location and final destination of each vehicle, the total amount of waste to be collected is allocated to a business site to be collected within the range of the loading limit for each vehicle, and a waste collection route is calculated for each vehicle. Characterized in that Waste collection method. According to claim 1,
The waste collection method, characterized in that the limit storage capacity is determined by the capacity and number of waste recovery bins possessed by each business site. According to claim 1,
The limit storage capacity is variable according to time, and is determined by an average amount of waste for each time period collected according to the application information for waste collection for each business site received from the at least one business site. According to claim 2,
Location information of the collection vehicle is grasped in real time based on a GPS signal, and whether or not the collection vehicle is moving according to the collection route calculated for each collection vehicle and whether or not collection work is being performed according to the collection schedule is controlled. characterized waste collection methods. According to claim 8,
The waste collection method of claim 1 , wherein a notification is notified through the collector terminal when the collection vehicle deviates from the collection route or the collection operation is not performed according to the collection schedule.

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