CN112938213B - Intelligent sanitation management method, system and storage medium based on Internet of things - Google Patents
Intelligent sanitation management method, system and storage medium based on Internet of things Download PDFInfo
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- CN112938213B CN112938213B CN202110141608.6A CN202110141608A CN112938213B CN 112938213 B CN112938213 B CN 112938213B CN 202110141608 A CN202110141608 A CN 202110141608A CN 112938213 B CN112938213 B CN 112938213B
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B65—CONVEYING; PACKING; STORING; HANDLING THIN OR FILAMENTARY MATERIAL
- B65F—GATHERING OR REMOVAL OF DOMESTIC OR LIKE REFUSE
- B65F1/00—Refuse receptacles; Accessories therefor
- B65F1/0033—Refuse receptacles; Accessories therefor specially adapted for segregated refuse collecting, e.g. receptacles with several compartments; Combination of receptacles
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B65—CONVEYING; PACKING; STORING; HANDLING THIN OR FILAMENTARY MATERIAL
- B65F—GATHERING OR REMOVAL OF DOMESTIC OR LIKE REFUSE
- B65F1/00—Refuse receptacles; Accessories therefor
- B65F1/14—Other constructional features; Accessories
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B65—CONVEYING; PACKING; STORING; HANDLING THIN OR FILAMENTARY MATERIAL
- B65F—GATHERING OR REMOVAL OF DOMESTIC OR LIKE REFUSE
- B65F1/00—Refuse receptacles; Accessories therefor
- B65F1/0033—Refuse receptacles; Accessories therefor specially adapted for segregated refuse collecting, e.g. receptacles with several compartments; Combination of receptacles
- B65F2001/008—Means for automatically selecting the receptacle in which refuse should be placed
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Abstract
The application relates to an intelligent sanitation management method, system and storage medium based on the Internet of things, which relate to the field of sanitation management and comprise the following steps: collecting garbage data of various garbage in the classified garbage can; acquiring volume information of various garbage in all classified garbage can based on garbage data of various garbage in all classified garbage can; if the volume of single garbage in the classified garbage can exceeds a second preset value and the volumes of other garbage types are smaller than the second preset value, the second preset value is higher than the first preset value, and based on the pre-constructed emergency garbage truck distribution condition and the position information of the corresponding classified garbage can, a proper emergency garbage truck is screened out, and an emergency garbage treatment notification and the position information of the corresponding classified garbage can are sent to the proper emergency garbage truck. The application has the effect of classifying and throwing single garbage in the garbage bin by emergency treatment.
Description
Technical Field
The application relates to the field of environmental sanitation management, in particular to an intelligent environmental sanitation management method, system and storage medium based on the Internet of things.
Background
At present, with the development of economy and the continuous increase of urban population, environmental sanitation problems have become important problems facing each large city, daily arrangement of urban volume sanitation work and management statistics of various environmental sanitation facilities depend on manpower, so that the workload of managers is very large, the traditional management mode and management method cannot meet the requirements of the current urban volume sanitation work, and with the development of cities, garbage classification treatment plays a significant role in reducing garbage treatment cost and reducing land resource consumption.
The utility model provides a current publication number CN106779332A and patent name are intelligent sanitation management system's based on GPS patent, including first positioning module, the second positioning module, the third positioning module, information input unit, a server, the early warning module, first communication module and second communication module, wherein the combination setting of first positioning module, second positioning module and third positioning module realizes sanitation vehicle in the sanitation district, garbage bin and staff's positional information real-time supervision, first communication module and second communication module have realized the server to the real-time command of vehicle driver, sanitation staff, and timely understanding sanitation work's progress, be connected with the microphone on the server, realize manager and sanitation vehicle driver, sanitation staff's information exchange.
However, due to popularization of garbage classification, the garbage can generally has a garbage classification throwing function, sanitation workers are required to clean the garbage can regularly, and single garbage throwing amount in the classified throwing garbage can partially arranged in a special area is large, such as large harmful garbage throwing amount in the classified throwing garbage can near a factory or large living garbage throwing amount in the classified throwing garbage can near a living community, so that garbage with large single throwing amount in the part garbage can is likely to be in an overflow state when the workers clean the garbage in advance, and urban capacity is easily affected.
Aiming at the related technology, the inventor considers that the defects that when the single garbage with larger throwing amount is thrown into the garbage can in a classified way, the garbage is difficult to clean in time exist.
Disclosure of Invention
In order to overcome the defect that when single garbage with large throwing amount is thrown into a garbage can in a classified manner, the garbage is difficult to clean in time, the application provides an intelligent sanitation management method, system and storage medium based on the Internet of things.
In a first aspect, the present application provides an intelligent environmental sanitation management method based on the internet of things, which adopts the following technical scheme: an intelligent sanitation management method based on the Internet of things comprises the following steps:
Collecting garbage data of various garbage in the classified garbage can;
acquiring volume information of various garbage in all classified garbage can based on garbage data of various garbage in all classified garbage can;
if the volumes of various kinds of garbage in the classified garbage can are larger than a first preset value, acquiring the position information of the corresponding classified garbage can, and sending a garbage treatment notice and the position information of the corresponding classified garbage can to a common garbage truck;
if the volume of single garbage in the classified garbage can exceeds a second preset value and the volumes of other garbage types are smaller than the second preset value, the second preset value is higher than the first preset value, the emergency garbage treatment notification and the position information of the classified garbage can are sent to the proper emergency garbage can based on the pre-constructed emergency garbage can distribution condition and the position information of the classified garbage can and the proper emergency garbage can.
Through adopting above-mentioned technical scheme, can in time acquire the volume of all kinds of rubbish in the classification input garbage bin, all kinds of rubbish in the classification input garbage bin is greater than first default, then dispatch ordinary garbage truck and carry out normal garbage disposal, when single class rubbish in the classification input garbage bin is too much, then based on the emergent garbage truck distribution condition of building in advance and the position information of corresponding classification input garbage bin, dispatch emergent garbage truck carries out the emergent garbage disposal of single class rubbish, thereby can be comparatively timely the treatment classification input garbage that single class input in the garbage bin is great, avoid single class rubbish in the garbage bin to overflow and influence urban volume.
Optionally, the steps for acquiring the volume information of each kind of garbage in the classified garbage can are as follows:
the maximum capacity of each type of garbage can is calculated by applying a pre-constructed maximum capacity calculation formula of each type of garbage can, and the pre-constructed maximum capacity calculation formula of each type of garbage can is specifically as follows: v (V) 1 ＝S×h 1 Wherein V is 1 S is the preset garbage bin bottom area, h is the maximum capacity of the garbage bin 1 The height of the garbage can is preset;
starting an ultrasonic range finder arranged at the top of the garbage can to vertically emit ultrasonic waves to the bottom of the garbage can, wherein the time for ultrasonic wave emission is T 1 Ultrasonic touch and contact with the garbageForming reflected wave after garbage and turning back, wherein the time for receiving the reflected wave by the ultrasonic range finder is T 2 The method comprises the steps of carrying out a first treatment on the surface of the Time T based on ultrasonic wave detector when transmitting ultrasonic wave 1 Time T of receiving reflected wave by ultrasonic wave 2 The volume of the existing garbage in the garbage can is calculated by applying a pre-constructed volume calculation formula of the existing garbage in the garbage can, and the pre-constructed volume calculation formula of the existing garbage in the garbage can is specifically as follows:wherein V is 2 The existing garbage volume in the garbage can is that C is the propagation speed of ultrasonic waves in the air, and C=340 m/s;
and marking different numbers on all the classified garbage cans, uploading all the classified garbage can numbers and the existing garbage volume information of each type of garbage in the corresponding classified garbage can to a preset first database, wherein the first database is used for storing the classified garbage can number information and the existing garbage volume information of each type of garbage in the corresponding numbered can, and taking the classified garbage can number as a query object from the first database to acquire the existing garbage volume information of each type of garbage in the corresponding numbered can.
Through adopting above-mentioned technical scheme, the maximum capacity of classifying and throwing in the garbage bin is calculated first, and then use ultrasonic ranging appearance can measure the volume of classifying and throwing in the current various rubbish of garbage bin to in with classifying and throwing in the serial number of garbage bin and corresponding classifying and throwing in the current rubbish volume information uploading of various rubbish in the garbage bin to first database, compare in artifical inspection and look over the rubbish volume in the garbage bin, not only can retrieve in real time from first database and throw in the current rubbish volume information of garbage bin of all classifications, practice thrift the manpower more moreover, data are also more accurate.
Optionally, the pre-constructed emergency garbage truck distribution condition acquiring steps are as follows:
the method comprises the steps of putting the number of all triggering emergency garbage treatment events, the triggering time of the emergency garbage treatment events and the classification of the triggering emergency garbage treatment events into a third database of position information of garbage cans from preset storage;
taking the number triggering the emergency garbage disposal event as a query object from a third database, and acquiring the triggering time of corresponding emergency garbage disposal and the position information of the classified garbage can triggering the emergency garbage disposal event for data analysis;
and reasonably scheduling the emergency garbage truck based on the result of data analysis of the historical emergency garbage treatment times.
By adopting the technical scheme, based on the pre-constructed distribution condition of the emergency garbage truck, the quantity of the emergency garbage truck is reasonably scheduled and scheduled through data analysis, so that excessive equipment and manpower input in the garbage emergency treatment link can be avoided, and equipment resources and manpower resources are saved.
Optionally, the steps of acquiring the triggering time of the corresponding emergency garbage treatment and the position information of the classified garbage can triggering the emergency treatment event for data analysis are as follows:
the numbers of all the emergency garbage disposal triggering events with the triggering time of the emergency garbage disposal in the third database from the last week to the last week are called, the total number of all the emergency garbage disposal events completed from the last week to the last week is counted, and therefore the number of the emergency garbage disposal in the last week is obtained and uploaded to the third database;
the number of the daily emergency treatment garbage of the last week is calculated by using a pre-constructed calculation formula of the daily emergency treatment garbage of the last week, and the pre-constructed calculation formula of the daily emergency treatment garbage of the last week is specifically as follows:wherein lambda is the average number of times of emergency treatment of garbage every day in the last week, and Y is the number of times of emergency treatment of garbage in the last week;
The number of times of emergency treatment of garbage in one week meets poisson distribution, the probability of the number of times of emergency treatment of garbage in the next week, which occurs on average, is calculated by applying a pre-constructed probability density function formula of the number of times of emergency treatment of garbage in one week, and the pre-constructed probability density function formula of the number of times of emergency treatment of garbage in one week hasThe body is as follows:wherein k is a positive integer, and P is the probability of carrying out emergency treatment on garbage k times every day on average in a week;
substituting lambda into a probability density function formula of the number of times of daily emergency treatment of garbage, sequentially substituting k into the probability density function formula of the number of times of daily emergency treatment of garbage according to the sequence from small to large to calculate a P value, sequentially adding the obtained P values to obtain a total value of P, and obtaining k when the total value of P is greater than 0.8 as the number of times of daily emergency treatment of garbage when the average week.
By adopting the technical scheme, because the emergency garbage belongs to random events, the number of times of emergency garbage treatment in a week meets poisson distribution, the number of times of emergency garbage treatment in average every day in the week is substituted into a probability density function formula of poisson distribution, and the number of times of emergency garbage treatment in average every day in the week can be calculated and predicted, so that the number of emergency garbage trucks is reasonably scheduled, and equipment and human resources are saved.
Optionally, the steps of reasonable scheduling of the emergency garbage truck are as follows:
the numbers of all triggering emergency garbage disposal events with the triggering time of the emergency garbage disposal in the last week to the last sunday in the third database are called, and the position information of garbage cans is correspondingly classified and put in;
dividing the urban map into n areas, and respectively counting the total number of all emergency garbage treatment events in each area from the last week to the last week based on the position information of the classified throwing garbage bin triggering the emergency treatment events, so as to respectively obtain the times of emergency garbage treatment in each area from the last week;
the number of times of the last week of the emergency treatment of the garbage in the third database is called, and the number of times of the emergency treatment of the garbage in each area of the last week is divided by the number of times of the emergency treatment of the garbage in the last week in sequence, so that the duty ratio of the number of times of the emergency treatment of the garbage in each area of the last week to the number of times of the emergency treatment of the garbage in the last week is respectively obtained;
calculating the average number of times of daily emergency treatment of the garbage on the week, when the total value of P is larger than 0.8, based on a probability density function formula of the number of times of daily emergency treatment of the garbage, wherein the average number of scheduled emergency garbage trucks on the week is the same as the average number of times of daily emergency treatment of the garbage on the week;
The number of the emergency garbage trucks which are evenly scheduled every day in each area is obtained and distributed by multiplying the number of the emergency garbage trucks which are evenly scheduled every day in the week by the duty ratio of the number of the emergency garbage trucks which are evenly scheduled every day in each area in the week.
By adopting the technical scheme, the same number of emergency garbage trucks are distributed according to the number of the emergency garbage treatment times which are predicted to occur evenly in the current week, equipment and human resources can be saved while basic garbage emergency treatment is met, and then the different number of emergency garbage trucks are distributed to each area according to the ratio of the number of the emergency garbage treatment times in the total number of the emergency garbage treatment times in each area of the city, so that the utilization rate of the emergency garbage trucks is improved.
Optionally, the screening steps of a suitable emergency refuse vehicle are as follows:
the serial numbers of the classified garbage cans are used as query objects one by one from a preset first database, so that the existing garbage volume information of various kinds of garbage in each classified garbage can is queried, and classified garbage cans with the existing garbage volumes of single kinds exceeding a second preset value and the existing garbage volumes of other kinds being smaller than the second preset value are screened;
The method comprises the steps of taking an emergency garbage truck number as a query object one by one from a second database which is preset and stores the emergency garbage truck number and the residual capacity information of various garbage storage areas in corresponding emergency garbage trucks in real time, so that the residual capacity of various garbage storage areas in each emergency garbage truck is queried;
the emergency garbage truck which is used for sorting and putting single type garbage exceeding the second preset value in the garbage can and has the volume smaller than the residual capacity of the same type garbage storage area in the emergency garbage truck is selected as a proper emergency garbage truck.
Through adopting above-mentioned technical scheme, screening out need carry out the classification of emergent garbage treatment put in the garbage bin and this classification put in the present volume of the rubbish that needs to be handled in the garbage bin earlier, through the surplus capacity of this kind rubbish storage area in the present rubbish volume that needs to be handled and the emergent garbage truck of comparison to screening out the emergent garbage truck that is enough to hold the rubbish that needs to be handled, thereby being favorable to emergent garbage truck to carry out emergency treatment to rubbish.
Optionally, the step of screening the emergency garbage truck further comprises the step of screening the emergency garbage truck according to the existing garbage volume and the residual capacity in the emergency garbage truck:
If a plurality of emergency garbage trucks exist, the volume of garbage in the garbage can meeting the requirement of emergency treatment is smaller than the condition that the residual capacity of the same garbage storage area in the emergency garbage truck;
collecting the position information of all emergency garbage trucks meeting the conditions;
planning a running path from all emergency garbage trucks meeting the conditions to the classified garbage cans needing emergency treatment based on the position information of all emergency garbage trucks meeting the conditions and the position information of the classified garbage cans needing emergency treatment;
and obtaining the distances of all the traveling paths of the emergency garbage trucks meeting the conditions, comparing all the corresponding distances, and screening out the emergency garbage truck corresponding to the shortest distance as the proper emergency garbage truck.
Through adopting above-mentioned technical scheme, further consider if there are a plurality of emergent garbage trucks to accord with the volume of rubbish in the garbage bin of required emergency treatment and be less than the same kind rubbish storage area residual capacity in the emergent garbage truck, when above-mentioned circumstances appear, after screening out the emergent garbage truck that can hold the rubbish that needs emergency treatment, carry out the secondary screening from the emergent garbage truck that accords with the condition of screening again, travel to the distance of the travel path of throwing the garbage bin of the classification that needs emergency treatment through comparing all emergent garbage trucks that accord with the condition, thereby screen out the emergent garbage truck that the distance is shortest and carry out emergency garbage treatment, be favorable to the more quick processing to the rubbish that needs emergency treatment.
In a second aspect, the application provides an intelligent sanitation management system based on the internet of things, which adopts the following technical scheme: comprising a memory, a processor and a program stored on said memory and executable on said processor, which program, when loaded and executed by the processor, is capable of implementing an intelligent environmental sanitation management method based on the internet of things as claimed in any one of the preceding claims.
Through adopting above-mentioned technical scheme, through the accent of procedure, can in time acquire all processing classification and put in the volume of various rubbish in the garbage bin, all be greater than first default when the classification puts in various rubbish in the garbage bin, then dispatch ordinary garbage truck and carry out normal garbage disposal, when the classification puts in the single class rubbish in the garbage bin too much, then dispatch emergent garbage truck and carry out the emergent garbage disposal of single class rubbish, thereby can be comparatively timely processing classification put in the single class in the garbage bin put in the great rubbish of volume, avoid single class rubbish in the garbage bin to overflow and influence urban volume.
In a third aspect, the present application provides a computer storage medium, which adopts the following technical scheme:
a program comprising instructions capable of implementing an intelligent sanitation management method based on the internet of things as claimed in any one of the preceding claims when loaded and executed by a processor.
Through adopting above-mentioned technical scheme, through the accent of procedure, can in time acquire all processing classification and put in the volume of various rubbish in the garbage bin, all be greater than first default when the classification puts in various rubbish in the garbage bin, then dispatch ordinary garbage truck and carry out normal garbage disposal, when the classification puts in the single class rubbish in the garbage bin too much, then dispatch emergent garbage truck and carry out the emergent garbage disposal of single class rubbish, thereby can be comparatively timely processing classification put in the single class in the garbage bin put in the great rubbish of volume, avoid single class rubbish in the garbage bin to overflow and influence urban volume.
In summary, the present application includes at least one of the following beneficial technical effects:
1. when the single garbage in the classified garbage can is excessively put, the emergency garbage truck can be scheduled to carry out emergency garbage treatment on the single garbage, so that the garbage with larger single garbage put amount in the classified garbage can be treated timely, and the influence on urban volume caused by overflow of the single garbage in the garbage can is avoided.
2. Based on the pre-constructed distribution condition of the emergency garbage trucks, the quantity of the emergency garbage trucks is reasonably scheduled and scheduled through data analysis, so that excessive equipment and manpower input in the garbage emergency treatment link can be avoided, and equipment resources and manpower resources are saved.
Drawings
Fig. 1 is an overall flow diagram of an intelligent sanitation management method based on the internet of things in an embodiment of the application.
Fig. 2 is a schematic flow chart of the sub-step S200 in fig. 1.
Fig. 3 is a schematic flow chart of steps S4a0 to S4c 0.
Fig. 4 is a flow chart of steps S4d0 to S4g 0.
Fig. 5 is a flow chart of steps S4A0 to S4C 0.
Fig. 6 is a flow chart of steps S4B1 to S4B 4.
Fig. 7 is a flow chart of steps S4C1 to S4C 5.
Detailed Description
The present application is described in further detail below in conjunction with figures 1-7.
Referring to fig. 1, an intelligent sanitation management method based on the internet of things disclosed in the present application includes steps S100 to S400.
In step S100, garbage data for classifying and throwing various kinds of garbage in the garbage can is collected.
Specifically, the collected garbage data mentioned in step S100 is mainly captured by a monitoring camera disposed at the classified garbage can, and various garbage mentioned in step S100 includes recyclable garbage, harmful garbage, kitchen garbage and other garbage.
In step S200, volume information of each kind of garbage in the garbage can is acquired based on the garbage data of each kind of garbage in the garbage can.
Referring to fig. 2, the steps of acquiring volume information of various kinds of garbage in all the classified delivery garbage referred to in step S200 may be divided into steps S210 to S240.
In step S210, the maximum capacity of each type of trash can is calculated by applying a pre-constructed maximum capacity calculation formula of each type of trash can, and the pre-constructed maximum capacity calculation formula of each type of trash can is specifically as follows: v (V) 1 ＝S×h 1 Wherein V is 1 S is the preset garbage bin bottom area, h is the maximum capacity of the garbage bin 1 The height of the garbage can is preset.
For example, assume that one of the trash cans obtains a certain trash can bottom area of 0.5 square meters, i.e., S value of 0.5, by means of manual measurement, and the same trash can height of 2 meters, i.e., h, by means of manual measurement 1 The value is 2, so the maximum capacity of the garbage can be according to V 1 ＝S×h 1 And calculating to obtain the product, specifically 1 cubic meter.
In step S220, an ultrasonic range finder disposed at the top of the garbage can is started to vertically emit ultrasonic waves to the bottom of the garbage can, and the time for the ultrasonic wave emission is T 1 After the ultrasonic waves touch the garbage, reflected waves are formed and turned back, and the time for the ultrasonic range finder to receive the reflected waves is T 2 。
Specifically, the ultrasonic distance meter mentioned in step S220 is installed at the middle position of the inner top of the dustbin, and the aiming device on the ultrasonic distance meter is vertically downward, so that the ultrasonic distance meter is adopted for measurement in the embodiment because the ultrasonic has the advantages of good directionality, concentrated energy, smaller attenuation and stronger reflecting capability in the transmission process.
In step S230, the time T when the ultrasonic wave is emitted based on the ultrasonic detector 1 Time T of receiving reflected wave by ultrasonic wave 2 The volume of the existing garbage in the garbage can is calculated by applying a pre-constructed volume calculation formula of the existing garbage in the garbage can, and the pre-constructed volume calculation formula of the existing garbage in the garbage can is specifically as follows:wherein V is 2 C is ultrasonic wave in air, which is the existing garbage volume in the garbage canC=340 m/s.
For example, assume that one of the garbage cans obtains a bottom area of 0.5 square meter, i.e., an S value of 0.5, by means of manual measurement, and calculates a maximum capacity of 1 cubic meter, i.e., V, of the garbage can by applying a maximum capacity calculation formula of various kinds of garbage cans 1 0.12, it is assumed that the aiming point device of the ultrasonic detector in the garbage can emits ultrasonic waves toward the garbage in the garbage can at 12 minutes 0 seconds, namely T 1 Is 12 hours and 0 minutes and 0 seconds, and the receiving device of the ultrasonic detector in the garbage can receives reflected waves formed after ultrasonic waves touch garbage when the ultrasonic waves are 12 minutes and 002 seconds, namely T 2 Is 12 hours 0 min 002 seconds, so the volume of the existing garbage in the garbage can be according toThe calculation is carried out to obtain 0.592 cubic meter.
In step S240, the garbage cans are marked with different numbers, and the numbers of the garbage cans and the existing garbage volume information of each kind of garbage in the corresponding garbage cans are uploaded to a preset first database, wherein the first database is used for storing the number information of the garbage cans and the existing garbage volume information of each kind of garbage in the corresponding garbage cans, and the number of the garbage cans is taken as a query object from the first database to obtain the existing garbage volume information of each kind of garbage in the corresponding garbage cans.
Specifically, the marks mentioned in step S240 are numbered differently, and the sorting garbage cans are numbered sequentially from small to large according to the natural integer.
In step S300, if the volumes of the various types of garbage in the classified garbage can are larger than the first preset value, the position information of the corresponding classified garbage can is obtained, and the garbage treatment notification and the position information of the corresponding classified garbage can are sent to the common garbage truck.
Specifically, the position information of the classified garbage can is obtained in step S300, and is obtained by installing a positioning device on the classified garbage can and then using the beidou satellite navigation system, and the first preset value in step S300 is preset to be 50% of the maximum capacity of the garbage can.
In step S400, if the volume of single garbage in the classified garbage can exceeds the second preset value and the volumes of other garbage types are smaller than the second preset value, the second preset value is higher than the first preset value, based on the pre-constructed distribution condition of the emergency garbage truck, and the position information of the corresponding classified garbage can, and the proper emergency garbage truck is screened out, and the emergency garbage treatment notification and the position information of the corresponding classified garbage can are sent to the proper emergency garbage truck.
Specifically, the second preset value mentioned in step S400 is preset to 75% of the maximum capacity of the trash can.
Referring to fig. 5, the acquisition steps of the pre-constructed emergency garbage truck distribution mentioned in step S400 may be divided into steps S4A0 to S4C0.
In step S4A0, the position information of the garbage can is put into a third database from the preset number, the triggering time and the classification of all the triggering emergency garbage treatment events.
Specifically, when the triggering time of the emergency garbage disposal event mentioned in step S4A0 is triggered by the garbage disposal event, the current system time is invoked to obtain.
In step S4B0, the number triggering the emergency garbage disposal event is taken as the query object from the third database, and the triggering time of the corresponding emergency garbage disposal and the position information of the classified garbage can triggering the emergency garbage disposal event are obtained for data analysis.
Referring to fig. 6, the steps mentioned in step S4B0 for acquiring the triggering time of the corresponding emergency garbage, and the location information of the classified delivering garbage for triggering the emergency garbage event for data analysis may be divided into steps S4B1 to S4B4.
In step S4B1, the numbers of all the emergency garbage disposal triggering events with the triggering time of the emergency garbage disposal in the third database from monday to sunday are called, and the total number of all the emergency garbage disposal events completed from monday to sunday is counted, so that the number of the emergency garbage disposal in the last week is obtained and uploaded to the third database.
Specifically, the statistics mentioned in step S4B1 are added statistics based on the number of the numbers of all triggering emergency garbage disposal events whose triggering time of the emergency garbage disposal is on the last monday to the last sunday.
In step S4B2, the number of times of daily emergency treatment of the last week average is calculated by applying a pre-constructed calculation formula of the number of times of daily emergency treatment of the last week average, and the pre-constructed calculation formula of the number of times of daily emergency treatment of the last week average is specifically as follows: Where λ is the average number of times of emergency treatment of the refuse per day in the last week and Y is the number of times of emergency treatment of the refuse per week.
For example, assuming that the number of all trigger emergency garbage disposal events based on the trigger time of the emergency garbage disposal is on the last week to the last week counts the number of last week emergency garbage disposal as 70, i.e., Y is 70, the number of last week average daily emergency garbage disposal may be as followsThe calculation is carried out for 10 times.
In step S4B3, the number of times of emergency treatment of the garbage in one week satisfies poisson distribution, and the probability of the number of times of emergency treatment of the garbage in the next week is calculated by applying a pre-constructed probability density function formula of the number of times of emergency treatment of the garbage in one week, wherein the pre-constructed probability density function formula of the number of times of emergency treatment of the garbage in one week is specifically as follows:where k is a positive integer and P is the average daily probability of emergency disposal of the refuse k times a week.
Specifically, the poisson distribution mentioned in step S4B3 is characterized by the average occurrence number of random events in unit time (or unit area), so that the number of times of emergency treatment on garbage in a week satisfies the poisson distribution, and the probability of average emergency treatment on garbage k times per day in a week can be calculated by using a probability density function formula of the poisson distribution.
In step S4B4, λ is substituted into a probability density function formula of the number of times of daily emergency treatment of garbage, and k is sequentially substituted into the probability density function formula of the number of times of daily emergency treatment of garbage according to the order from small to large to calculate a P value, and the obtained P values are sequentially added to obtain a total P value, where k is the number of times of daily emergency treatment of garbage when the total P value is greater than 0.8.
Specifically, the greater the total value of P, the higher the likelihood that k, which gives the total value of P, is the number of times the refuse is subjected to emergency treatment every day on a weekly average, so that the greater the total value of P is 0.8, the greater the k is the number of times the refuse is subjected to emergency treatment every day on a weekly average, for example, assuming that the number of times the refuse is subjected to emergency treatment every day on a weekly average is 10, i.e., λ is 10, and thus k is substituted in order from small to largeCalculating, when k is 1 +.>The total value of P at this time is 0.0005; when k is 2 +.>The total value of P at this time is P (1) +p (2) =0.0028; when k is 12The total value of P at this time is P (1) +p (2) +p (12) =0.7916; when k is 13The total P was P (1) +p (2) +.+ P (13) = 0.8645 > 0.8 at this time, so the probability of 13 times of emergency treatment of the waste on average per week was 86.45%.
In step S4C0, the emergency garbage truck is reasonably scheduled based on the result of the data analysis of the historical emergency treatment garbage times.
Referring to fig. 7, the rational scheduling steps of the emergency garbage truck mentioned in step S4C0 may be divided into steps S4C1 to S4C5.
In step S4C1, the numbers of all the triggering emergency garbage disposal events with the triggering time of the emergency garbage disposal in the third database from monday to sunday and the position information of the corresponding classified garbage cans are called.
In step S4C2, the urban map is divided into n areas, and the total number of all the emergency garbage disposal events in each area from the last week to the last week is counted based on the position information of the classified garbage can triggering the emergency disposal events, so as to obtain the number of times of emergency garbage disposal in each area from the last week.
Specifically, the urban map is divided into n areas as mentioned in step S4C2, and the area division is performed based on administrative areas divided in the urban overall plan.
In step S4C3, the number of times of last week emergency treatment of the garbage in the third database is called, and the number of times of last week emergency treatment of each piece of area is divided by the number of times of last week emergency treatment of the garbage in turn, so as to obtain the duty ratio of the number of times of last week emergency treatment of the garbage in each piece of area respectively.
For example, assuming that the urban map is divided into 2 areas, namely an area a and an area B, i.e. n is 2, if the number of times of the last week of the refuse emergency treatment is 50, wherein the number of times of the refuse emergency treatment in the area a is 20 and the number of times of the refuse emergency treatment in the area B is 30, the ratio of the number of times of the refuse emergency treatment in the area a to the number of times of the last week of the refuse emergency treatment isThe proportion of the number of times of emergency treatment of the garbage in the area B to the number of times of emergency treatment of the garbage in the periphery is
In step S4C4, the number of times of daily emergency treatment of the refuse is averaged over the week when the total value of P obtained is larger than 0.8, based on the probability density function formula of the number of times of daily emergency treatment of the refuse, and the number of emergency refuse vehicles which are averaged over the week and are scheduled on the average is the same as the number of times of daily emergency treatment of the refuse.
For example, assuming that the average number of times of emergency treatment of garbage per week is 10 times, i.e., λ is 10, the P total value is P (1) +p (2) +.+p (13) = 0.8645 > 0.8 when k is 13, calculated according to a probability density function formula of the number of times of emergency treatment of garbage per week, and thus the number of emergency garbage trucks scheduled per week is 13.
In step S4C5, the number of emergency garbage trucks that are scheduled each day in each area is obtained and allocated by multiplying the number of emergency garbage trucks that are scheduled each day in the week by the duty ratio of the number of emergency garbage trucks that are scheduled each day in each area in the week.
For example, assuming that the number of emergency garbage trucks scheduled daily in the week is 100, the urban map is divided into 2 areas, namely an area a and an area B, the number of emergency garbage trucks in the area a is 40% of the number of emergency garbage trucks in the week, the number of emergency garbage trucks in the area B is 60% of the number of emergency garbage trucks in the week, the number of emergency garbage trucks scheduled daily in the area a is 100×40%, specifically 40, and the number of emergency garbage trucks scheduled daily in the area a is 100×60%, specifically 60.
Referring to fig. 3 and 4, the screening step of the suitable emergency garbage truck mentioned in step S400 may be divided into steps S4a0 to S4g0.
In step S4a0, the number of the classified garbage can is used as a query object from a preset first database one by one, so that the existing garbage volume information of each kind of garbage in each classified garbage can is queried, and the classified garbage cans with the existing garbage volumes of single kind of garbage exceeding a second preset value and the existing garbage volumes of other kinds being smaller than the second preset value are screened.
Specifically, the screening mentioned in step S4a0 refers to screening by comparing the existing garbage volumes of various kinds of garbage in the garbage can with the second preset value of the garbage can, for example, assuming that the maximum capacity of each kind of garbage can in one of the classified garbage cans is 1 cubic meter, the second preset value of the classified garbage can is 0.75 cubic meter, if kitchen garbage in the garbage can is 0.76 cubic meter, harmful garbage in the garbage can is 0.33 cubic meter, recoverable garbage is 0.74 cubic meter, and other garbage is 0.58 cubic meter, the garbage can meets the condition.
In step S4b0, the emergency garbage truck numbers are used as query objects one by one from a second database which is preset and stores the emergency garbage truck numbers and the residual capacity information of the various garbage storage areas in the corresponding emergency garbage trucks in real time, so that the residual capacities of the various garbage storage areas in each emergency garbage truck are queried.
Specifically, the residual capacity information of various kinds of garbage storage areas in the emergency garbage truck mentioned in step S4b0 is obtained by a sensor installed in the emergency garbage truck.
In step S4c0, an emergency garbage truck with the existing garbage volume of the single type of garbage exceeding the second preset value in the classified garbage can smaller than the residual capacity of the same type of garbage storage area in the emergency garbage truck is selected as a proper emergency garbage truck.
In step S4d0, if there are a plurality of emergency refuse trucks, the volume of the refuse in the refuse receptacle conforming to the required emergency treatment is smaller than the remaining capacity of the same kind of refuse storage area in the emergency refuse truck.
In step S4e0, position information of all emergency refuse trucks meeting the conditions is collected.
Specifically, the position information of the emergency garbage truck is collected in step S4e0, and the position information is obtained by installing a positioning device on the emergency garbage truck and then using the Beidou satellite navigation system.
In step S4f0, a travel path from the emergency garbage truck meeting the conditions to the classified garbage can requiring emergency treatment is planned based on the position information of the emergency garbage truck meeting the conditions and the position information of the classified garbage can requiring emergency treatment.
Specifically, the planned driving path mentioned in step S4f0 is firstly obtained the position information of the emergency garbage truck and the position information of the classified garbage can for emergency treatment, and then the path planning is performed by a path analysis algorithm engine based on a compression layering algorithm.
In step S4g0, the distances of all the emergency garbage truck traveling paths meeting the conditions are obtained, all the corresponding distances are compared, and the emergency garbage truck corresponding to the shortest distance is selected as the proper emergency garbage truck.
Specifically, the distance of the travel path is obtained in step S4g0, the path planned by the path analysis algorithm engine is divided into a plurality of sections of straight paths based on the beidou satellite navigation system, the distances of the plurality of sections of straight paths are calculated according to the lengths and the scales of the plurality of sections of straight paths, and then the distances of the plurality of sections of straight paths are added, so that the total distance of the travel path is obtained.
Embodiments of the present invention provide a computer readable storage medium comprising a program capable of implementing a method as any of fig. 1-7 when loaded and executed by a processor.
The computer-readable storage medium includes, for example: a U-disk, a removable hard disk, a Read-Only Memory (ROM), a random access Memory (Random Access Memory, RAM), a magnetic disk, or an optical disk, or other various media capable of storing program codes.
Based on the same inventive concept, the embodiment of the invention provides an intelligent environmental sanitation management system based on the Internet of things, which comprises a memory and a processor, wherein a program capable of realizing any one of the methods shown in fig. 1 to 7 is stored in the memory.
It will be apparent to those skilled in the art that, for convenience and brevity of description, only the above-described division of the functional modules is illustrated, and in practical application, the above-described functional allocation may be performed by different functional modules according to needs, i.e. the internal structure of the apparatus is divided into different functional modules to perform all or part of the functions described above. The specific working processes of the above-described systems, devices and units may refer to the corresponding processes in the foregoing method embodiments, which are not described herein.
In the several embodiments provided in this application, it should be understood that the disclosed systems, apparatuses, and methods may be implemented in other ways. For example, the apparatus embodiments described above are merely illustrative, e.g., the division of modules or units is merely a logical functional division, and there may be additional divisions when actually implemented, e.g., multiple units or components may be combined or integrated into another system, or some features may be omitted or not performed. Alternatively, the coupling or direct coupling or communication connection shown or discussed with each other may be an indirect coupling or communication connection via some interfaces, devices or units, which may be in electrical, mechanical or other form.
The units described as separate units may or may not be physically separate, and units shown as units may or may not be physical units, may be located in one place, or may be distributed over a plurality of network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.
In addition, each functional unit in each embodiment of the present application may be integrated in one processing unit, or each unit may exist alone physically, or two or more units may be integrated in one unit. The integrated units may be implemented in hardware or in software functional units.
The integrated units, if implemented in the form of software functional units and sold or used as stand-alone products, may be stored in a computer readable storage medium. Based on such understanding, the technical solution of the present application may be embodied in essence or a part contributing to the prior art or all or part of the technical solution, in the form of a software product stored in a storage medium, including several instructions to cause a computer device (which may be a personal computer, a server, or a network device, etc.) or a processor (processor) to perform all or part of the steps of the methods described in the embodiments of the present application. And the aforementioned storage medium includes: various media capable of storing program codes, such as a U disk, a mobile hard disk, a read-only memory, a random access memory, a magnetic disk or an optical disk.
The embodiments of the present invention are all preferred embodiments of the present invention, and are not intended to limit the scope of the present invention in this way, therefore: all equivalent changes in structure, shape and principle of the invention should be covered in the scope of protection of the invention.
Claims (5)
1. An intelligent sanitation management method based on the Internet of things is characterized by comprising the following steps:
collecting garbage data of various garbage in the classified garbage can;
acquiring volume information of various garbage in all classified garbage can based on garbage data of various garbage in all classified garbage can;
if the volumes of various kinds of garbage in the classified garbage can are larger than a first preset value, acquiring the position information of the corresponding classified garbage can, and sending a garbage treatment notice and the position information of the corresponding classified garbage can to a common garbage truck;
if the volume of single garbage in the classified garbage can exceeds a second preset value and the volumes of other garbage types are smaller than the second preset value, the second preset value is higher than the first preset value, based on the pre-constructed emergency garbage truck distribution condition and the position information of the corresponding classified garbage can, a proper emergency garbage truck is screened out, and an emergency garbage treatment notification and the position information of the corresponding classified garbage can are sent to the proper emergency garbage truck;
The method comprises the following steps of:
taking the number of the triggering emergency garbage treatment event as a query object from a third database which is preset and stores all the numbers of the triggering emergency garbage treatment event, the triggering time of the emergency garbage treatment event and the position information of the classified delivery garbage bin of the triggering emergency garbage treatment event, calling the numbers of all the triggering emergency garbage treatment events of which the triggering time of the emergency garbage treatment is from the last week to the last week in the third database, counting the total number of all the emergency garbage treatment events completed from the last week to the last week, and obtaining the number of the last week emergency garbage treatment and uploading the number to the third database;
the number of the daily emergency treatment garbage of the last week is calculated by using a pre-constructed calculation formula of the daily emergency treatment garbage of the last week, and the pre-constructed calculation formula of the daily emergency treatment garbage of the last week is specifically as follows:wherein lambda is the average number of times of emergency treatment of garbage every day in the last week, and Y is the number of times of emergency treatment of garbage in the last week;
the number of times of emergency treatment of garbage in one week meets poisson distribution, the probability of the number of times of emergency treatment of garbage in the next week, which occurs on average, is calculated by applying a pre-constructed probability density function formula of the number of times of emergency treatment of garbage in one week, and the pre-constructed probability density function formula of the number of times of emergency treatment of garbage in one week is specifically as follows: Wherein k is a positive integer, and P is the probability of carrying out emergency treatment on garbage k times every day on average in a week;
substituting lambda into a probability density function formula of the number of times of daily emergency treatment of garbage, sequentially substituting k into the probability density function formula of the number of times of daily emergency treatment of garbage according to the sequence from small to large to calculate a P value, sequentially adding the obtained P values to obtain a total value of P, and obtaining that k is the number of times of daily emergency treatment of garbage when the total value of P is greater than 0.8;
the numbers of all triggering emergency garbage disposal events with the triggering time of the emergency garbage disposal in the last week to the last sunday in the third database are called, and the position information of garbage cans is correspondingly classified and put in;
dividing the urban map into n areas, and respectively counting the total number of all emergency garbage treatment events in each area from the last week to the last week based on the position information of the classified throwing garbage bin triggering the emergency treatment events, so as to respectively obtain the times of emergency garbage treatment in each area from the last week;
the number of times of the last week of the emergency treatment of the garbage in the third database is called, and the number of times of the emergency treatment of the garbage in each area of the last week is divided by the number of times of the emergency treatment of the garbage in the last week in sequence, so that the duty ratio of the number of times of the emergency treatment of the garbage in each area of the last week to the number of times of the emergency treatment of the garbage in the last week is respectively obtained;
Calculating the average number of times of daily emergency treatment of the garbage on the week, when the total value of P is larger than 0.8, based on a probability density function formula of the number of times of daily emergency treatment of the garbage, wherein the average number of scheduled emergency garbage trucks on the week is the same as the average number of times of daily emergency treatment of the garbage on the week;
the number of the emergency garbage trucks which are evenly scheduled every day in the week is multiplied by the duty ratio of the number of the emergency garbage trucks which are evenly scheduled every day in the week to the number of the emergency garbage trucks which are evenly scheduled every day in the week, so that the number of the emergency garbage trucks which are evenly scheduled every day in each area is obtained and distributed;
the volume information of various garbage in the classified garbage can is obtained by the following steps:
the maximum capacity of each type of garbage can is calculated by applying a pre-constructed maximum capacity calculation formula of each type of garbage can, and the pre-constructed maximum capacity calculation formula of each type of garbage can is specifically as follows: v (V) 1 ＝S×h 1 Wherein V is 1 S is the preset garbage bin bottom area, h is the maximum capacity of the garbage bin 1 The height of the garbage can is preset;
starting an ultrasonic range finder arranged at the top of the garbage can to vertically emit ultrasonic waves to the bottom of the garbage can, wherein the time for ultrasonic wave emission is T 1 After the ultrasonic waves touch the garbage, reflected waves are formed and turned back, and the time for the ultrasonic range finder to receive the reflected waves is T 2 ；
Time T based on ultrasonic wave detector when transmitting ultrasonic wave 1 Time T of receiving reflected wave by ultrasonic wave 2 Calculating by using a pre-constructed volume calculation formula of the existing garbage in the garbage canThe volume of the existing garbage in the garbage can is discharged, and a pre-constructed volume calculation formula of the existing garbage in the garbage can is specifically as follows:wherein V is 2 The existing garbage volume in the garbage can is that C is the propagation speed of ultrasonic waves in the air, and C=340 m/s;
and marking different numbers on all the classified garbage cans, uploading all the classified garbage can numbers and the existing garbage volume information of each type of garbage in the corresponding classified garbage can to a preset first database, wherein the first database is used for storing the classified garbage can number information and the existing garbage volume information of each type of garbage in the corresponding numbered can, and taking the classified garbage can number as a query object from the first database to acquire the existing garbage volume information of each type of garbage in the corresponding numbered can.
2. The intelligent sanitation management method based on the internet of things according to claim 1, wherein the screening steps of the suitable emergency garbage truck are as follows:
the serial numbers of the classified garbage cans are used as query objects one by one from a preset first database, so that the existing garbage volume information of various kinds of garbage in each classified garbage can is queried, and classified garbage cans with the existing garbage volumes of single kinds exceeding a second preset value and the existing garbage volumes of other kinds being smaller than the second preset value are screened;
The method comprises the steps of taking an emergency garbage truck number as a query object one by one from a second database which is preset and stores the emergency garbage truck number and the residual capacity information of various garbage storage areas in corresponding emergency garbage trucks in real time, so that the residual capacity of various garbage storage areas in each emergency garbage truck is queried;
the emergency garbage truck which is used for sorting and putting single type garbage exceeding the second preset value in the garbage can and has the volume smaller than the residual capacity of the same type garbage storage area in the emergency garbage truck is selected as a proper emergency garbage truck.
3. The internet of things-based intelligent sanitation management method of claim 2, wherein the step of screening the emergency garbage truck further comprises the step of screening the emergency garbage truck according to the existing garbage volume and the remaining capacity in the emergency garbage truck:
if a plurality of emergency garbage trucks exist, the volume of garbage in the garbage can meeting the requirement of emergency treatment is smaller than the condition that the residual capacity of the same garbage storage area in the emergency garbage truck;
collecting the position information of all emergency garbage trucks meeting the conditions;
planning a running path from all emergency garbage trucks meeting the conditions to the classified garbage cans needing emergency treatment based on the position information of all emergency garbage trucks meeting the conditions and the position information of the classified garbage cans needing emergency treatment;
And obtaining the distances of all the traveling paths of the emergency garbage trucks meeting the conditions, comparing all the corresponding distances, and screening out the emergency garbage truck corresponding to the shortest distance as the proper emergency garbage truck.
4. An wisdom sanitation management system based on thing networking, its characterized in that: comprising a memory, a processor and a program stored on the memory and executable on the processor, which program, when loaded and executed by the processor, is capable of implementing an intelligent sanitation management method based on the internet of things as claimed in any one of claims 1 to 3.
5. A computer storage medium, characterized by: a program comprising instructions capable of implementing an intelligent sanitation management method based on the internet of things according to any one of claims 1 to 3 when loaded and executed by a processor.
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