CN112938213A - Intelligent environmental sanitation management method and system based on Internet of things and storage medium - Google Patents
Intelligent environmental sanitation management method and system based on Internet of things and storage medium Download PDFInfo
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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
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Abstract
The application relates to an intelligent environmental sanitation management method, system and storage medium based on the Internet of things, which relate to the field of environmental sanitation management and comprise the following steps: collecting garbage data of various types of garbage in a classified garbage can; acquiring volume information of various types of garbage in all classified garbage throwing buckets based on garbage data of various types of garbage in all classified garbage throwing buckets; if the volume of single type of garbage in the classified throwing garbage can exceeds a second preset value, the volumes of other types of garbage 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 throwing garbage can, a proper emergency garbage truck is screened out, and an emergency garbage disposal notice and the position information of the corresponding classified throwing garbage can are sent to the proper emergency garbage truck. This application has the effect of single type rubbish in the garbage bin is put in emergency treatment classification.
Description
Technical Field
The application relates to the field of environmental sanitation management, in particular to an intelligent environmental sanitation management method and system based on the Internet of things and a storage medium.
Background
At present, with the development of economy and the increasing of urban population, environmental sanitation problems become important problems faced by various big cities, daily arrangement of urban sanitation work and management statistics of various environmental sanitation facilities depend on manpower, so that the workload of managers is large, the traditional management mode and management method cannot meet the requirements of the current urban sanitation work, and along with the development of cities, garbage classification treatment plays an important role in reducing garbage treatment cost and reducing land resource consumption.
The patent of current publication No. CN106779332A and the patent name is an intelligent sanitation management system based on GPS, including first orientation module, the second orientation module, the third orientation module, the information input unit, the server, the early warning module, first communication module and second communication module, wherein first orientation module, the combination setting of second orientation module and third orientation module realizes sanitation vehicle in the sanitation area, the positional information real-time supervision of garbage bin and staff, first communication module and second communication module have realized that the server is to vehicle driver, sanitation staff's real-time command, and the progress of timely understanding sanitation work, be connected with the microphone on the server, realize that the administrator exchanges with sanitation vehicle driver, sanitation staff's information.
However, due to the popularization of garbage classification, the garbage can has a function of classified garbage throwing, cleaning of the garbage can requires sanitation workers to clean regularly, and the throwing amount of the single-class garbage partially arranged in the classified garbage throwing in the special area is large, for example, the throwing amount of harmful garbage in the classified garbage throwing in the garbage can near a factory is large or the throwing amount of living garbage in the classified garbage throwing in the garbage can near a living community is large, so that the garbage with the large throwing amount of the single-class garbage in the partial garbage can is likely to be in an overflow state when the workers come to clean, and therefore the market capacity is easily influenced.
In view of the above-mentioned related art, the inventor thinks that there is the defect that when the garbage is put into the garbage bin in a classified manner, the garbage with a large single input amount is difficult to clean in time.
Disclosure of Invention
In order to overcome the defect that single-type garbage with large input amount in a garbage can is difficult to clean in time when classified input is carried out, the application provides an intelligent environmental sanitation management method and system based on the Internet of things and a storage medium.
In a first aspect, the application provides an intelligent environmental sanitation management method based on the internet of things, which adopts the following technical scheme:
an intelligent environmental sanitation management method based on the Internet of things comprises the following steps:
collecting garbage data of various types of garbage in a classified garbage can;
acquiring volume information of various types of garbage in all classified garbage throwing buckets based on garbage data of various types of garbage in all classified garbage throwing buckets;
if the volume of each type of garbage in the classified throwing garbage can is larger than a first preset value, acquiring the position information of the corresponding classified throwing garbage can, and sending a garbage treatment notice and the position information of the corresponding classified throwing garbage can to a common garbage truck;
if the volume of single type of garbage in the classified throwing garbage can exceeds a second preset value, the volumes of other types of garbage 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 emergency garbage trucks and the position information of the corresponding classified throwing garbage can, a proper emergency garbage truck is selected, and an emergency garbage disposal notice and the position information of the corresponding classified throwing garbage can are sent to the proper emergency garbage truck.
Through adopting above-mentioned technical scheme, can in time acquire all volume of handling each type of rubbish in the categorised garbage bin of puting in, all be greater than first default when categorised each type of rubbish of puting in the garbage bin, then dispatch ordinary garbage truck and carry out normal refuse treatment, when categorised single type rubbish of puting in the garbage bin was too much, then based on the emergent garbage truck distribution condition of founding in advance and the corresponding categorised positional information who puts in the garbage bin, dispatch emergent garbage truck carries out the emergent refuse treatment of single type rubbish, thereby can be comparatively timely handle the great rubbish of single type input volume of categorised input in the garbage bin, avoid single type rubbish in the garbage bin to spill over and influence the market capacity.
Optionally, the obtaining step of the volume information of various types of garbage in all classified garbage cans is 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, wherein the pre-constructed maximum capacity calculation formula of each type of garbage can is as follows: v1=S×h1In which V is1Is the maximum capacity of the garbage can, S is the preset garbage can bottom area, h1The height of the garbage can is preset;
the ultrasonic distance meter arranged at the top of the garbage can is started to vertically transmit ultrasonic waves to the bottom of the garbage can, and the time during ultrasonic transmission is T1The ultrasonic waves form reflected waves and turn back after contacting the garbage, and the time for receiving the reflected waves by the ultrasonic range finder is T2；
Time T based on ultrasonic detector when transmitting ultrasonic waves1With the time T of the ultrasonic wave receiving the reflected wave2The 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, wherein the pre-constructed volume calculation formula of the existing garbage in the garbage can is as follows:
in which V is2The volume of the existing garbage in the garbage can is C, the propagation speed of the ultrasonic waves in the air is C =340 m/s;
the method comprises the steps of marking all classified trash cans with different serial numbers, uploading all classified trash can serial numbers and current trash volume information of various types of trash in the corresponding classified trash cans to a preset first database, storing the serial numbers of all classified trash cans and the current trash volume information of various types of trash in the corresponding numbered cans by the first database, and acquiring the current trash volume information of various types of trash in the corresponding numbered cans by taking the classified trash can serial numbers as query objects from the first database.
Through adopting above-mentioned technical scheme, the maximum capacity of categorised garbage bin of puting in is measured out earlier, use ultrasonic ranging appearance again can measure the volume of categorised current each kind of rubbish of puting in the garbage bin, and with the serial number of categorised garbage bin of puting in and the current rubbish volume information of corresponding categorised various rubbish of puting in the garbage bin upload to first database in, compare in the interior rubbish volume of manual patrol checking garbage bin, not only can follow the current rubbish volume information of puting in the garbage bin of all categorised of the real-time transfer of first database and take out, and practice thrift the manpower more, data are also more accurate.
Optionally, the step of obtaining the distribution condition of the pre-constructed emergency garbage truck is as follows:
the method comprises the steps that all serial numbers of triggering emergency garbage disposal events, triggering time of the emergency garbage disposal events and position information of classified throwing garbage cans triggering the emergency disposal events are stored in a preset third database;
acquiring the triggering time of corresponding emergency garbage disposal and the position information of classified throwing garbage cans triggering the emergency disposal events as data analysis by taking the number triggering the emergency garbage disposal events as a query object from a third database;
and reasonably scheduling the emergency garbage truck based on the result of data analysis of the historical emergency garbage disposal times.
By adopting the technical scheme, based on the pre-constructed distribution condition of the emergency garbage trucks, the quantity of the emergency garbage trucks is reasonably arranged and dispatched through data analysis, so that the situation that excessive equipment and manpower are input in a garbage emergency treatment link can be avoided, and equipment resources and manpower resources are saved.
Optionally, the step of obtaining the triggering time of the corresponding emergency garbage disposal and the position information of the classified trash can triggering the emergency disposal event for data analysis is as follows:
calling the numbers of all the triggering emergency garbage disposal events of which the triggering time of the emergency garbage disposal in the third database is from the last Monday to the last Sunday, and counting the total number of all the emergency garbage disposal events completed from the last Monday to the last Sunday, so as to obtain the times of emergency garbage disposal in the last week and upload the times to the third database;
calculating the average daily emergency garbage disposal times of the last week by applying a pre-constructed calculation formula of the average daily emergency garbage disposal times of the last week, wherein the pre-constructed calculation formula of the average daily emergency garbage disposal times of the last week is as follows:
wherein lambda is the average number of times of emergency garbage disposal in the last week every day, and Y is the number of times of emergency garbage disposal in the last week;
the times of emergency garbage disposal in one week meet Poisson distribution, the probability of the times of emergency garbage disposal which averagely occurs in the next week every day is calculated by applying a pre-constructed probability density function formula of the times of emergency garbage disposal in one week every day, and the pre-constructed probability density function formula of the times of emergency garbage disposal in one week every day is specifically as follows:
wherein k is a positive integer, and P is the probability of emergency treatment of garbage k times per week on average;
substituting the lambda into a probability density function formula of the daily emergency treatment garbage frequency, sequentially substituting the k into the probability density function formula of the daily emergency treatment garbage frequency according to a 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 the k when the total value of P is more than 0.8 as the weekly average daily emergency treatment garbage frequency.
By adopting the technical scheme, because the emergency treatment garbage belongs to random events, the number of times of emergency treatment garbage in one week meets Poisson distribution, and according to a probability density function formula of the Poisson distribution and substituted into the number of times of emergency treatment garbage in the average day of the last week, the number of times of emergency treatment garbage which averagely occurs in the current week can be calculated and predicted, so that the number of emergency garbage trucks can be reasonably dispatched, and the equipment and manpower resources can be saved.
Optionally, the reasonable scheduling steps of the emergency garbage truck are as follows:
calling the numbers of all the triggering emergency garbage disposal events of which the triggering time of the emergency garbage disposal is from last Monday to last Sunday in the third database and the position information of the corresponding classified garbage throwing buckets;
dividing the city map into n areas, and respectively counting the total number of all emergency garbage disposal events in each area from the last Monday to the last Sunday based on the position information of the classified garbage cans triggering the emergency disposal events, so as to respectively obtain the emergency garbage disposal times of each area in the last week;
calling the number of times of emergency garbage disposal of the last week in the third database, and sequentially dividing the number of times of emergency garbage disposal of each region of the last week by the number of times of emergency garbage disposal of the last week, thereby respectively obtaining the proportion of the number of times of emergency garbage disposal of each region of the last week to the number of times of emergency garbage disposal of the last week;
calculating the number of times of emergency garbage disposal per day in the current week when the total value of P is greater than 0.8 based on a probability density function formula of the number of times of emergency garbage disposal per day, wherein the number of emergency garbage trucks which are averagely scheduled per day in the current week is the same as the number of times of emergency garbage disposal per day in the current week;
the quantity of the emergency garbage trucks which are averagely scheduled every day in the week is multiplied by the proportion of the times of the emergency garbage disposal of each area in the last week to the times of the emergency garbage disposal of each area in the last week, so that the quantity of the emergency garbage trucks which are averagely scheduled every day in each area is obtained and distributed.
By adopting the technical scheme, the emergency garbage trucks with the same quantity are distributed according to the average emergency garbage disposal times in the week, so that the emergency garbage trucks can save equipment and human resources while meeting the basic garbage emergency disposal, and the emergency garbage trucks with different quantities are distributed to each region according to the proportion of the emergency garbage disposal times in the total times in each region of a city every day, thereby being beneficial to improving the utilization rate of the emergency garbage trucks.
Optionally, the screening steps of the suitable emergency garbage truck are as follows:
the classified throwing garbage cans are sequentially numbered as query objects from a preset first database, so that the existing garbage volume information of various types of garbage in each classified throwing garbage can is queried, and the classified throwing garbage cans with the existing garbage volume of single type of garbage exceeding a second preset value and the existing garbage volumes of other types of garbage being smaller than the second preset value are screened out;
the method comprises the steps that the emergency garbage truck numbers are used as query objects one by one from a preset second database which stores the emergency garbage truck numbers and the information of the residual capacity 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 selects the single type of garbage exceeding the second preset value in the classified throwing garbage can and has the garbage volume smaller than the residual capacity of the same type of garbage storage area in the emergency garbage truck is taken as a proper emergency garbage truck.
Through adopting above-mentioned technical scheme, select earlier that the classification that needs emergent refuse handling puts in the garbage bin and this classification puts in the current volume of the rubbish that needs handled in the garbage bin, deposit the surplus capacity in district through comparing the current rubbish volume that needs handle and this kind of rubbish in the emergency garbage truck to select enough emergent garbage truck that holds the rubbish that needs handle, thereby be favorable to emergent garbage truck to carry out emergency handling to rubbish.
Optionally, the step of screening the emergency garbage truck further comprises the step of screening the emergency garbage truck according to the volume of the existing garbage and the residual capacity in the emergency garbage truck:
if a plurality of emergency garbage trucks meet the condition that the volume of the garbage in the garbage can needing emergency treatment is smaller than the residual capacity of the garbage storage areas of the same type in the emergency garbage trucks;
collecting the position information of all emergency garbage trucks meeting the conditions;
planning a driving path from all the emergency garbage trucks meeting the conditions to the classified garbage can needing emergency treatment based on the position information of all the emergency garbage trucks meeting the conditions and the position information of the classified garbage can needing emergency treatment;
and acquiring the distances of all the emergency garbage trucks meeting the conditions, comparing all the corresponding distances, and screening the emergency garbage truck corresponding to the shortest distance as a proper emergency garbage truck.
Through adopting above-mentioned technical scheme, further consider if there is the volume of rubbish in the garbage bin that a plurality of emergent garbage trucks accord with required emergency treatment to be less than the surplus capacity of same kind rubbish storage area in the emergent garbage truck, when above-mentioned condition appears, select to hold the emergent garbage truck back that needs emergency treatment rubbish, carry out the secondary screening again in the emergent garbage truck of the qualification of agreeing with of selecting, go to the distance of the route of traveling of the categorised input garbage bin of needs emergency treatment through comparing all emergent garbage trucks that accord with the condition, thereby select the emergent garbage truck that the distance is shortest and carry out emergent refuse treatment, be favorable to the more quick processing of 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 the memory and executable on the processor, the program being capable of being loaded and executed by the processor to implement a method for intelligent internet of things based sanitation management as claimed in any one of the preceding claims.
Through adopting above-mentioned technical scheme, through the calling of procedure, can in time acquire all volume of handling each type of rubbish in the categorised garbage bin of puting in, all be greater than first default when categorised each type of rubbish of puting in the garbage bin, then dispatch ordinary garbage truck and carry out normal refuse treatment, when categorised single type rubbish of puting in the garbage bin was too much, then dispatch emergent garbage truck carries out the emergent refuse treatment of single type rubbish, thereby can be comparatively timely handle the great rubbish of single type input volume of categorised input in the garbage bin, avoid the interior single type rubbish of garbage bin to spill over and influence the city.
In a third aspect, the present application provides a computer storage medium, which adopts the following technical solutions:
a program which can be loaded and executed by a processor to implement a method for intelligent internet of things based sanitation management as claimed in any one of the preceding claims.
Through adopting above-mentioned technical scheme, through the calling of procedure, can in time acquire all volume of handling each type of rubbish in the categorised garbage bin of puting in, all be greater than first default when categorised each type of rubbish of puting in the garbage bin, then dispatch ordinary garbage truck and carry out normal refuse treatment, when categorised single type rubbish of puting in the garbage bin was too much, then dispatch emergent garbage truck carries out the emergent refuse treatment of single type rubbish, thereby can be comparatively timely handle the great rubbish of single type input volume of categorised input in the garbage bin, avoid the interior single type rubbish of garbage bin to spill over and influence the city.
In summary, the present application includes at least one of the following beneficial technical effects:
1. when the single-type garbage in the garbage can is thrown in a classified mode, the emergency garbage truck can be dispatched to conduct emergency garbage disposal of the single-type garbage, therefore, the garbage with large single-type throwing amount in the garbage can be thrown in a classified mode in a timely mode, and the phenomenon that the single-type garbage in the garbage can overflows to affect the city capacity is avoided.
2. Based on the pre-constructed distribution condition of the emergency garbage trucks, the quantity of the emergency garbage trucks is reasonably arranged and dispatched through data analysis, so that the situation that excessive equipment and manpower are input in a garbage emergency treatment link can be avoided, and equipment resources and manpower resources are saved.
Drawings
Fig. 1 is a schematic overall flow chart of an intelligent environmental sanitation management method based on the internet of things in the embodiment of the present application.
Fig. 2 is a schematic flow chart of the S200 substep of fig. 1.
Fig. 3 is a schematic flow chart of the pre-constructed emergency garbage truck distribution acquisition step mentioned in the sub-step S400 of fig. 1.
Fig. 4 is a schematic flow chart of the S4B0 sub-step of fig. 3.
Fig. 5 is a schematic flow diagram of the S4C0 sub-step of fig. 3.
Fig. 6 is a schematic flow diagram of a suitable emergency garbage truck screening step as set forth in sub-step S400 of fig. 1.
Fig. 7 is a schematic flow diagram of a screening step for a suitable emergency trash vehicle of fig. 6 after the S4c0 substep.
Detailed Description
The present application is described in further detail below with reference to figures 1-7.
Referring to fig. 1, the method for managing intelligent sanitation based on internet of things disclosed in the present application includes steps S100 to S400.
In step S100, garbage data of various types of garbage placed in the garbage can by classification is collected.
Specifically, the collected garbage data mentioned in step S100 is mainly captured and collected by a monitoring camera disposed at the classified trash can, and the various types of garbage mentioned in step S100 include recoverable garbage, harmful garbage, kitchen garbage, and other garbage.
In step S200, volume information of various types of garbage in all classified trash cans is obtained based on garbage data of various types of garbage in all classified trash cans.
Referring to fig. 2, the steps of obtaining the volume information of each type of garbage in all classified trash cans in step S200 can be divided into steps S210 to S240.
In step S210, the maximum capacity of each type of trash can is calculated by applying the pre-constructed maximum capacity calculation formula of each type of trash can, which is specifically as follows: v1=S×h1In which V is1Is the maximum capacity of the garbage can, S is the preset garbage can bottom area, h1Is the preset height of the garbage can.
For example, assuming that one of the trash cans obtains a bottom area of 0.5 square meter, i.e. an S value of 0.5, by manual measurement, the trash can obtains a height of 2 meters, i.e. h, of the same trash can by manual measurement1The value is 2, so the maximum capacity of the garbage can be according to V1=S×h1And calculating to obtain the product, specifically 1 cubic meter.
In step S220, the garbage can arranged at the top of the garbage can is startedThe ultrasonic distance meter vertically transmits ultrasonic waves to the bottom of the garbage can, and the time when the ultrasonic waves are transmitted is T1The ultrasonic waves form reflected waves and turn back after contacting the garbage, and the time for receiving the reflected waves by the ultrasonic range finder is T2。
Specifically, the ultrasonic range finder mentioned in step S220 is installed at the middle position of the top in the trash can, and the aiming point device on the ultrasonic range finder faces vertically downward, so that the ultrasonic range finder is adopted for measurement in the embodiment because the ultrasonic has the advantages of good directionality, concentrated energy, small attenuation in the transmission process and strong reflection capability in the transmission process.
In step S230, the ultrasonic detector emits ultrasonic waves based on the time T1With the time T of the ultrasonic wave receiving the reflected wave2The 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, wherein the pre-constructed volume calculation formula of the existing garbage in the garbage can is as follows:
in which V is2C is the propagation speed of the ultrasonic waves in the air, and C =340 m/s.
For example, suppose that one of the trash cans is measured manually to obtain that the bottom area of one trash can is 0.5 square meter, i.e. the S value is 0.5, and the maximum volume of the trash can is calculated to be 1 cubic meter, i.e. V, by applying the maximum volume calculation formula of each type of trash can10.12, the ultrasonic detector in the garbage can is assumed to transmit ultrasonic waves towards the garbage in the garbage can at 12 hours, 0 minutes and 0 seconds, namely T112 hours, 0 minute and 0 second, and the receiving device of the ultrasonic detector in the garbage can receives reflected waves, namely T waves formed after the ultrasonic waves touch the garbage at 12 hours, 0 minute and 002 seconds212 hours, 0 minute and 002 seconds, so that the volume of the existing garbage in the garbage can be adjusted according to the volume
And calculating to obtain the specific value of 0.592 cubic meter.
In step S240, all classified trash cans are marked with different numbers, and the numbers of all classified trash cans and the current trash volume information of various types of trash in the corresponding classified trash cans are uploaded to a preset first database, where the first database is used to store the numbers of all classified trash cans and the current trash volume information of various types of trash in the corresponding numbered cans, and the numbers of classified trash cans are used as query objects from the first database to obtain the current trash volume information of various types of trash in the corresponding numbered cans.
Specifically, the labeling in step S240 is different in number, and the sorting and throwing garbage cans are numbered in sequence according to the sequence of natural integers from small to large.
In step S300, if the volume of each type of garbage in the classified trash can is greater than the first preset value, the position information of the corresponding classified trash can is obtained, and a garbage disposal notification and the position information of the corresponding classified trash can are sent to the general garbage truck.
Specifically, the position information of the classified trash can in the step S300 is acquired by installing a positioning device on the classified trash can and then using a Beidou satellite navigation system, and the first preset value in the step S300 is preset to 50% of the maximum capacity of the trash can.
In step S400, if the volume of the single type of garbage in the classified dumping garbage bin exceeds a second preset value and the volumes of other types of garbage are smaller than the second preset value, and the second preset value is higher than the first preset value, based on the pre-established distribution condition of the emergency garbage truck and the position information of the corresponding classified dumping garbage bin, a suitable emergency garbage truck is selected, and an emergency garbage disposal notification and the position information of the corresponding classified dumping garbage bin are sent to the suitable emergency garbage truck.
Specifically, the second preset value mentioned in step S400 is preset to be 75% of the maximum capacity of the trash can.
Referring to fig. 3, the step of acquiring the pre-constructed emergency garbage truck distribution mentioned in step S400 can be divided into steps S4a0 to S4C 0.
In step S4a0, all numbers triggering emergency garbage disposal events, triggering times of the emergency garbage disposal events, and location information of classified delivery garbage cans triggering the emergency disposal events are stored in a preset third database.
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 called to obtain the triggering time.
In step S4B0, the number triggering the emergency garbage disposal event is used as the query object from the third database, and the triggering time of the corresponding emergency garbage disposal and the location information of the classified trash can triggering the emergency disposal event are obtained for data analysis.
Referring to fig. 4, the steps of obtaining the triggering time of the corresponding emergency garbage disposal and the location information of the classified putting garbage can triggering the emergency disposal event for data analysis in step S4B0 can be divided into steps S4B1 to S4B 4.
In step S4B1, numbers of all the triggered emergency garbage disposal events in the third database whose triggering times for emergency garbage disposal are from the last monday to the last sunday are called, and the total number of all the emergency garbage disposal events completed from the last monday to the last sunday is counted, so as to obtain the number of times of emergency garbage disposal in the last week and upload the number of times to the third database.
Specifically, the statistics mentioned in step S4B1 are added based on the numbers of all the numbers of the emergency spam events triggered from the last monday to the last sunday of the emergency spam.
In step S4B2, the pre-constructed formula for calculating the average number of emergency garbage disposal times per day in the last week is used to calculate the average number of emergency garbage disposal times per day in the last week, and the pre-constructed formula for calculating the average number of emergency garbage disposal times per day in the last week is specifically as follows:
wherein, lambda is the average number of times of emergency garbage disposal in the last week every day, and Y is the number of times of emergency garbage disposal in the last week.
For example, it is assumed that the number of emergency garbage disposal events in the last week is counted as 70 times, that is, Y is 70 times, based on the number of all the emergency garbage disposal triggering events from the last Monday to the last Sunday, so the average number of emergency garbage disposal events per day in the last week can be calculated according to the number
And calculating and obtaining, specifically 10 times.
In step S4B3, the number of times of emergency garbage disposal within one week satisfies poisson distribution, and a pre-constructed probability density function formula of the number of times of emergency garbage disposal for each day of one week is applied to calculate the probability of the number of times of emergency garbage disposal that occurs averagely for each day of the next week, where the pre-constructed probability density function formula of the number of times of emergency garbage disposal for each day of one week is specifically as follows:
and k is a positive integer, and P is the probability of emergency treatment of garbage k times per week.
Specifically, the poisson distribution mentioned in step S4B3 is characterized in that the average occurrence frequency of random events in unit time (or unit area) is such that the emergency garbage disposal frequency in one week satisfies the poisson distribution, and the probability of emergency garbage disposal k times per week can be calculated by using the probability density function formula of poisson distribution.
In step S4B4, λ is substituted into the probability density function formula of the number of times of emergency disposal of garbage per day, k is substituted into the probability density function formula of the number of times of emergency disposal of garbage per day in sequence from small to large to calculate a P value, and the obtained P values are added in sequence to obtain a total value of P, where k is the number of times of emergency disposal of garbage per day when the total value of P is greater than 0.8.
Specifically, the larger the total value of P is, the higher the probability that k is the number of emergency garbage disposal times per day in the average week is, so that the larger the probability that k is the number of emergency garbage disposal times per day in the average week is when the total value of P is greater than 0.8, for example, the average number of emergency garbage disposal times per day in the last week is assumedThe number is 10, i.e., λ is 10, so that k is substituted in order from small to large
Calculation, when k is 1
When the total value of P is 0.0005; when k is 2
When the total value of P is
(ii) a When k is 12
When the total value of P is
(ii) a When k is 13
When P is a total value
Therefore, the average number of emergency garbage disposals per day in the week is 86.45%.
In step S4C0, the emergency garbage truck is dispatched reasonably based on the results of the data analysis of the historical emergency garbage disposal times.
Referring to fig. 5, the reasonable dispatching steps of the emergency garbage truck mentioned in step S4C0 can be divided into steps S4C1 to S4C 5.
In step S4C1, the numbers of all the triggered emergency garbage disposal events with the triggering time of emergency garbage disposal being from the last monday to the last sunday in the third database and the location information of the corresponding classified trash can are called.
In step S4C2, the city map is divided into n areas, and the total number of all emergency garbage disposal events in each area from the previous monday to the previous sunday is counted based on the location information of the classified trash can triggering the emergency disposal event, so as to obtain the number of emergency garbage disposal times of each area in the previous week.
Specifically, in step S4C2, the city map is divided into n areas, and the areas are divided based on the administrative districts divided in the city general plan.
In step S4C3, the number of times of emergency garbage disposal in the last week in the third database is retrieved, and the number of times of emergency garbage disposal in each area in the last week is sequentially divided by the number of times of emergency garbage disposal in the last week, thereby obtaining the percentage of the number of times of emergency garbage disposal in each area in the last week.
For example, assuming that the city map is divided into 2 areas, namely area a and area B, that is, n is 2, if the number of emergency garbage disposal in the last week is 50, wherein the number of emergency garbage disposal in area a is 20, and the number of emergency garbage disposal in area B is 30, the ratio of the number of emergency garbage disposal in area a to the number of emergency garbage disposal in the last week is equal to
The proportion of the emergency garbage disposal frequency of the area B to the emergency garbage disposal frequency of the last week is
。
In step S4C4, calculating the average daily emergency garbage disposal number of the current week when the total value of P is more than 0.8 based on the probability density function formula of the daily emergency garbage disposal number, wherein the number of the emergency garbage trucks which are averagely dispatched per week is the same as the average daily emergency garbage disposal number of the current week.
For example, assuming that the average number of emergency garbage disposal times per day in the last week is 10, i.e. λ is 10, the total value of P is 13 when k is calculated according to the probability density function formula of the number of emergency garbage disposal times per day in the week
Therefore, the number of the emergency garbage trucks which are dispatched on average every day in the week is 13.
In step S4C5, the number of the emergency garbage trucks dispatched equally per day in the same week is multiplied by the percentage of the number of times of emergency garbage disposal in each area of the last week in the last week, so as to obtain and allocate the number of the emergency garbage trucks dispatched equally per day in each area.
For example, assuming that the number of emergency garbage vehicles scheduled on average every day in the week is 100, the city map is divided into 2 areas, which are an area a and an area B, respectively, the percentage of the number of emergency garbage disposal times in the area a in the last week is 40%, and the percentage of the number of emergency garbage disposal times in the area B in the last week is 60%, then the number of emergency garbage vehicles scheduled on average every day in the area a in the week is 100 × 40%, specifically 40, and the number of emergency garbage vehicles scheduled on average every day in the area a in the week is 100 × 60%, specifically 60.
Referring to fig. 6 and 7, the screening step of the suitable emergency garbage truck mentioned in step S400 can be divided into steps S4a0 to S4g 0.
In step S4a0, the classified trash can numbers are sequentially selected from the preset first database as query objects, so as to query the existing trash volume information of each type of trash in each classified trash can, and select the classified trash cans in which the existing trash volume of the single type of trash exceeds the second preset value and the existing trash volumes of other types of trash are smaller than the second preset value.
Specifically, the screening mentioned in step S4a0 is performed by comparing the existing garbage volume of each type of garbage in the garbage can with the second preset value of the garbage can, for example, assuming that the maximum capacity of each type of garbage can in one of the classified garbage cans is 1 cubic meter, so the second preset value of the classified garbage can is 0.75 cubic meter, and if the kitchen garbage in the garbage can is 0.76 cubic meter, the harmful garbage in the garbage can is 0.33 cubic meter, the recyclable garbage is 0.74 cubic meter, and the other garbage is 0.58 cubic meter, the garbage can meets the condition.
In step S4b0, the emergency garbage truck numbers are sequentially used as query objects from a preset second database in which the emergency garbage truck numbers and the remaining capacity information of the various garbage storage areas in the corresponding emergency garbage trucks are stored in real time, so as to query the remaining capacity of the various garbage storage areas in each emergency garbage truck.
Specifically, the information about the remaining capacity of various 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, the emergency garbage truck with the volume of the single type of garbage exceeding the second preset value in the classified garbage can smaller than the remaining capacity of the same type of garbage storage area in the emergency garbage truck is selected as the suitable emergency garbage truck.
In step S4d0, if there are multiple emergency garbage trucks, the volume of garbage in the garbage can meeting the emergency treatment requirement is smaller than the remaining capacity of the garbage storage area of the same type in the emergency garbage truck.
In step S4e0, the position information of all eligible emergency garbage trucks is collected.
Specifically, the step S4e0 is to collect the position information of the emergency garbage truck, install a positioning device on the emergency garbage truck, and then use the beidou satellite navigation system to obtain the position information of the emergency garbage truck.
In step S4f0, based on the position information of all eligible emergency garbage trucks and the position information of the classified trash can to be put in for emergency treatment, a driving path from all eligible emergency garbage trucks to the classified trash can to be put in for emergency treatment is planned.
Specifically, the planning of the driving path mentioned in step S4f0 includes obtaining position information of the emergency garbage truck and position information of the classified trash can to be put in for emergency treatment, and then planning the path through a path analysis algorithm engine based on a compressed hierarchical algorithm.
In step S4g0, the distances of all the eligible emergency garbage trucks along the driving route are obtained, all the corresponding distances are compared, and the corresponding emergency garbage truck with the shortest distance is screened out as the appropriate emergency garbage truck.
Specifically, the step S4g0 includes obtaining the distance of the travel path, dividing the path planned by the path analysis algorithm engine into a plurality of linear paths based on the beidou satellite navigation system, calculating the distance of the plurality of linear paths according to the length of the plurality of linear paths and a scale, and adding the distances of the plurality of linear paths to obtain the total distance of the travel path.
An embodiment of the present invention provides a computer-readable storage medium, which includes a program capable of being loaded and executed by a processor to implement any one of the methods shown in fig. 1-7.
The computer-readable storage medium includes, for example: various media capable of storing program codes, such as a usb disk, a removable hard disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), a magnetic disk, or an optical disk.
Based on the same inventive concept, an embodiment of the present invention provides an intelligent environmental sanitation management system based on the internet of things, which includes a memory and a processor, wherein the memory stores a program that can be executed on the processor to implement any one of the methods shown in fig. 1 to 7.
It will be clear to those skilled in the art that, for convenience and simplicity of description, the foregoing division of the functional modules is merely used as an example, and in practical applications, the above function distribution may be performed by different functional modules according to needs, that is, the internal structure of the device is divided into different functional modules to perform all or part of the above described functions. For the specific working processes of the system, the apparatus and the unit described above, reference may be made to the corresponding processes in the foregoing method embodiments, and details are not described here again.
In the several embodiments provided in the present application, it should be understood that the disclosed system, apparatus and method may be implemented in other manners. For example, the above-described apparatus embodiments are merely illustrative, and for example, a module or a unit may be divided into only one logical function, and may be implemented in other ways, for example, a plurality of units or components may be combined or integrated into another system, or some features may be omitted, or not executed. In addition, the shown or discussed mutual coupling or direct coupling or communication connection may be an indirect coupling or communication connection through some interfaces, devices or units, and may be in an electrical, mechanical or other form.
Units described as separate parts may or may not be physically separate, and parts displayed as units may or may not be physical units, may be located in one place, or may be distributed on a plurality of network units. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of the embodiment.
In addition, functional units in the embodiments of the present application may be integrated into one processing unit, or each unit may exist alone physically, or two or more units are integrated into one unit. The integrated unit can be realized in a form of hardware, and can also be realized in a form of a software functional unit.
The integrated unit, if implemented in the form of a software functional unit and sold or used as a stand-alone product, may be stored in a computer readable storage medium. Based on such understanding, the technical solution of the present application may be substantially implemented or contributed by the prior art, or all or part of the technical solution may be embodied in a software product, which is stored in a storage medium and includes instructions for causing a computer device (which may be a personal computer, a server, a network device, or the like) or a processor (processor) to execute all or part of the steps of the method according to the embodiments of the present application. And the aforementioned storage medium includes: u disk, removable hard disk, read only memory, random access memory, magnetic or optical disk, etc. for storing program codes.
The embodiments of the present invention are preferred embodiments of the present invention, and the scope of the present invention is not limited by these embodiments, so: all equivalent changes made according to the structure, shape and principle of the invention are covered by the protection scope of the invention.
Claims (9)
1. An intelligent environmental sanitation management method based on the Internet of things is characterized by comprising the following steps:
collecting garbage data of various types of garbage in a classified garbage can;
acquiring volume information of various types of garbage in all classified garbage throwing buckets based on garbage data of various types of garbage in all classified garbage throwing buckets;
if the volume of each type of garbage in the classified throwing garbage can is larger than a first preset value, acquiring the position information of the corresponding classified throwing garbage can, and sending a garbage treatment notice and the position information of the corresponding classified throwing garbage can to a common garbage truck;
if the volume of single type of garbage in the classified throwing garbage can exceeds a second preset value, the volumes of other types of garbage 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 emergency garbage trucks and the position information of the corresponding classified throwing garbage can, a proper emergency garbage truck is selected, and an emergency garbage disposal notice and the position information of the corresponding classified throwing garbage can are sent to the proper emergency garbage truck.
2. The intelligent environmental sanitation management method based on the internet of things as claimed in claim 1, wherein the steps of obtaining the volume information of various types of garbage in all classified garbage cans 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, wherein the pre-constructed maximum capacity calculation formula of each type of garbage can is as follows: v1=S×h1In which V is1Is the maximum capacity of the garbage can, S is the preset garbage can bottom area, h1The height of the garbage can is preset;
the ultrasonic distance meter arranged at the top of the garbage can is started to vertically transmit ultrasonic waves to the bottom of the garbage can, and the time during ultrasonic transmission is T1The ultrasonic waves form reflected waves and turn back after contacting the garbage,the time for receiving the reflected wave by the ultrasonic range finder is T2；
Time T based on ultrasonic detector when transmitting ultrasonic waves1With the time T of the ultrasonic wave receiving the reflected wave2The 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, wherein the pre-constructed volume calculation formula of the existing garbage in the garbage can is as follows:
in which V is2The volume of the existing garbage in the garbage can is C, the propagation speed of the ultrasonic waves in the air is C =340 m/s;
the method comprises the steps of marking all classified trash cans with different serial numbers, uploading all classified trash can serial numbers and current trash volume information of various types of trash in the corresponding classified trash cans to a preset first database, storing the serial numbers of all classified trash cans and the current trash volume information of various types of trash in the corresponding numbered cans by the first database, and acquiring the current trash volume information of various types of trash in the corresponding numbered cans by taking the classified trash can serial numbers as query objects from the first database.
3. The intelligent environmental sanitation management method based on the internet of things as claimed in claim 1, wherein the pre-constructed emergency garbage truck distribution situation is obtained by the following steps:
the method comprises the steps that all serial numbers of triggering emergency garbage disposal events, triggering time of the emergency garbage disposal events and position information of classified throwing garbage cans triggering the emergency disposal events are stored in a preset third database;
acquiring the triggering time of corresponding emergency garbage disposal and the position information of classified throwing garbage cans triggering the emergency disposal events as data analysis by taking the number triggering the emergency garbage disposal events as a query object from a third database;
and reasonably scheduling the emergency garbage truck based on the result of data analysis of the historical emergency garbage disposal times.
4. The method for intelligent environmental sanitation management based on the internet of things as claimed in claim 3, wherein the steps of obtaining the triggering time of the corresponding emergency garbage disposal and the position information of the classified trash can triggering the emergency disposal event for data analysis are as follows:
calling the numbers of all the triggering emergency garbage disposal events of which the triggering time of the emergency garbage disposal in the third database is from the last Monday to the last Sunday, and counting the total number of all the emergency garbage disposal events completed from the last Monday to the last Sunday, so as to obtain the times of emergency garbage disposal in the last week and upload the times to the third database;
calculating the average daily emergency garbage disposal times of the last week by applying a pre-constructed calculation formula of the average daily emergency garbage disposal times of the last week, wherein the pre-constructed calculation formula of the average daily emergency garbage disposal times of the last week is as follows:
wherein lambda is the average number of times of emergency garbage disposal in the last week every day, and Y is the number of times of emergency garbage disposal in the last week;
the times of emergency garbage disposal in one week meet Poisson distribution, the probability of the times of emergency garbage disposal which averagely occurs in the next week every day is calculated by applying a pre-constructed probability density function formula of the times of emergency garbage disposal in one week every day, and the pre-constructed probability density function formula of the times of emergency garbage disposal in one week every day is specifically as follows:
wherein k is a positive integer, and P is the probability of emergency treatment of garbage k times per week on average;
substituting the lambda into a probability density function formula of the daily emergency treatment garbage frequency, sequentially substituting the k into the probability density function formula of the daily emergency treatment garbage frequency according to a 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 the k when the total value of P is more than 0.8 as the weekly average daily emergency treatment garbage frequency.
5. The intelligent environmental sanitation management method based on the internet of things as claimed in claim 3, wherein the reasonable scheduling steps of the emergency garbage truck are as follows:
calling the numbers of all the triggering emergency garbage disposal events of which the triggering time of the emergency garbage disposal is from last Monday to last Sunday in the third database and the position information of the corresponding classified garbage throwing buckets;
dividing the city map into n areas, and respectively counting the total number of all emergency garbage disposal events in each area from the last Monday to the last Sunday based on the position information of the classified garbage cans triggering the emergency disposal events, so as to respectively obtain the emergency garbage disposal times of each area in the last week;
calling the number of times of emergency garbage disposal of the last week in the third database, and sequentially dividing the number of times of emergency garbage disposal of each region of the last week by the number of times of emergency garbage disposal of the last week, thereby respectively obtaining the proportion of the number of times of emergency garbage disposal of each region of the last week to the number of times of emergency garbage disposal of the last week;
calculating the number of times of emergency garbage disposal per day in the current week when the total value of P is greater than 0.8 based on a probability density function formula of the number of times of emergency garbage disposal per day, wherein the number of emergency garbage trucks which are averagely scheduled per day in the current week is the same as the number of times of emergency garbage disposal per day in the current week;
the quantity of the emergency garbage trucks which are averagely scheduled every day in the week is multiplied by the proportion of the times of the emergency garbage disposal of each area in the last week to the times of the emergency garbage disposal of each area in the last week, so that the quantity of the emergency garbage trucks which are averagely scheduled every day in each area is obtained and distributed.
6. The intelligent environmental sanitation management method based on the internet of things of claim 1, wherein the screening of the suitable emergency garbage truck comprises the following steps:
the classified throwing garbage cans are sequentially numbered as query objects from a preset first database, so that the existing garbage volume information of various types of garbage in each classified throwing garbage can is queried, and the classified throwing garbage cans with the existing garbage volume of single type of garbage exceeding a second preset value and the existing garbage volumes of other types of garbage being smaller than the second preset value are screened out;
the method comprises the steps that the emergency garbage truck numbers are used as query objects one by one from a preset second database which stores the emergency garbage truck numbers and the information of the residual capacity 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 selects the single type of garbage exceeding the second preset value in the classified throwing garbage can and has the garbage volume smaller than the residual capacity of the same type of garbage storage area in the emergency garbage truck is taken as a proper emergency garbage truck.
7. The intelligent environmental sanitation management method based on the internet of things of claim 6, wherein the step of screening the emergency garbage trucks further comprises the step of, after screening the emergency garbage trucks according to the existing garbage volume and the remaining capacity in the emergency garbage trucks:
if a plurality of emergency garbage trucks meet the condition that the volume of the garbage in the garbage can needing emergency treatment is smaller than the residual capacity of the garbage storage areas of the same type in the emergency garbage trucks;
collecting the position information of all emergency garbage trucks meeting the conditions;
planning a driving path from all the emergency garbage trucks meeting the conditions to the classified garbage can needing emergency treatment based on the position information of all the emergency garbage trucks meeting the conditions and the position information of the classified garbage can needing emergency treatment;
and acquiring the distances of all the emergency garbage trucks meeting the conditions, comparing all the corresponding distances, and screening the emergency garbage truck corresponding to the shortest distance as a proper emergency garbage truck.
8. The utility model provides an wisdom sanitation management system based on thing networking which characterized in that: comprising a memory, a processor and a program stored on the memory and executable on the processor, the program being capable of being loaded and executed by the processor to implement a method for intelligent internet of things based environmental sanitation management as claimed in any one of claims 1 to 7.
9. A computer storage medium, characterized in that: a program which can be loaded and executed by a processor to implement the method for intelligent internet of things based sanitation management as claimed in any one of claims 1 to 7.
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