CN105976034A - Vehicle precision service platform - Google Patents
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Abstract
The invention provides an e-repair intelligent selection vehicle precision service platform which comprises a client, a server and a database. The database and the server are built together through a public cloud technology. The client is connected with and accesses the server through an interface arranged on the server. The client comprises a merchant and a vehicle owner. The platform provides accurate, fast, efficient, all-round and one-stop after-sales service for a large number of vehicle owners. The services comprise vehicle washing, maintenance, repair, beauty, rescue and many other aspects. The vehicle owner only needs to open the mobile phone application of e-repair intelligent selection. The platform can recommend the best service for the vehicle owner according to vehicle maintenance habits and records of the vehicle owner to meet the vehicle maintenance need of the vehicle owner. After the vehicle owner books a service, the vehicle owner can carry out payment through Wechat payment and alipay, and accepts the service in the near merchant under the guidance of the software. O2O closed-loop is carried out after the whole vehicle is completed.
Description
Technical field
The present invention relates to Internet of Things ammeter and field of energy-saving technology, be specifically related to a kind of e and repair intelligence and select the accurate service platform of automobile.
Background technology
2015, China's automobile guarantee-quantity reached 1.7 hundred million.After Chinese automobile, market scale enters high-speed development period, from the beginning of 2012 249000000000, cumulative year after year about 100,000,000,000, it is contemplated that will be close to 800,000,000,000 by 2015.The aspect such as the main centralized maintenance in market, maintenance after automobile.At present, the whole nation 480,000, mechanism of total motor vehicles maintenance, nearly 3,000,000 people of practitioner, complete year maintenance and measure 3.3 hundred million times.
But the development in market is still in the primary stage after China's automobile.The enterprise of 75% takes in below 10,000,000, and takes in enterprise more than 1,000,000,000 and only account for 1%.Compared to the after-sale service enterprise in over ten billion market, mature market, Europe, the average turnover of current line tap in the industry the most only accounts for the millesimal share in market.
After Chinese automobile, the main pain spot of service market includes:
(1) service quality is uneven
After Chinese automobile, dragons and fishes jumbled together in service market, and overall credibility is relatively low, and service charge is without standard.
(2) price is opaque
CCTV discloses, and car owner meets with up to the 73% of swindle, let alone other type Automobile Service shop in 4S shop.
(3) car owner lacks Professional knowledge
According to investigations, the car owner of 90% lacks maintenance knowledge, does not knows how to select maintenance project, easily by flicker.
For above-mentioned pain spot, the present invention is by B2B2C and 020 fusion mode, improve service quality, break price fixing, there is provided accurate for numerous car owners, fast, the most comprehensive, service after one-stop car, service content contains carwash, maintenance, maintenance, beauty treatment, numerous aspects such as rescue, car owner only need to open " e repaiies intelligence choosing " mobile phone application, our platform just can be according to maintain the car custom and the maintenance record of car owner, optimal service is recommended for car owner, meet the automobile maintenance demand of car owner nearby, car owner is after subscription services, wechat can be passed through, Unionpay or Alipay pay, and nigh businessman accepts service under the guide of software, complete O2O closed loop after whole car.
Summary of the invention
The problem that it is an object of the invention to overcome prior art to exist, it is provided that a kind of e repaiies intelligence and selects the accurate service platform of automobile.
For realizing above-mentioned technical purpose, reaching above-mentioned technique effect, the present invention is achieved through the following technical solutions:
A kind of e repaiies intelligence and selects the accurate service platform of automobile, including client, server end and data base, together with described data base and server end are built by publicly-owned cloud, described client is connected by the interface being arranged on server end and accesses server end, described client includes businessman's end and car owner's end, it is characterised in that:
Described businessman end includes registering log-in module, bench top module, smart message module, operation centre's module, my module, order processing flow module, described bench top module, operation centre's module, order processing flow module and message module are for configuring the business information in the application of automobile market businessman, and described registration log-in module, smart message module and my module are for configuring the general module information of conventional APP；The business information of described bench top module configuration comprises: retail shop shows and functional performance information when daily sales, accumulative income, account balance, the various state of order and operation centre's information；The business information of described operation centre module configuration comprises: adds commodity, treat that added merchandise control, undercarriage merchandise control, merchandise control on sale and main management vehicle are arranged, for providing a whole set of management of product scheme on line for businessman；Described I module configuration general APP information comprise: order switch, my wallet, trade company's certification and the basic setup information of shop and APP；
Described car owner's end includes registering login module, and intelligence selects shop module, my module, maintenance instruction module, Ordering Module and evaluation module；Described intelligence selects shop module for the exhibition information in differently configured kind shop；Described maintenance instruction module, according to the different vehicle of car owner, vehicle conditions, configures e and repaiies intelligence and select the big data algorithm of platform Intelligent Matching maintenance set meal；My module described be used for configuring reward voucher use, manage, evaluate, order list and individual's related data and configuration information.
Further, described data base uses MySQL database, and described server uses SpringMVC, Spring and Mybatis to integrate formula server.
Further, the interface of described server uses Restful style.
Further, described data base configures technical data and the auto parts machinery data of multiple different brands model of storage various.
Further, described car owner's end is additionally provided with data collection point, and for Real-time Collection user data, described user data includes user's vehicle, age, is accustomed to car custom, zone of action and maintenance.
Further, the e during the intelligence of described car owner's end selects shop module and maintenance instruction module repaiies intelligence and selects the big data algorithm of platform to include: the Xian Xia shops proposed algorithm weighting the collaborative filtering of uncertain neighbour based on position, the care products set meal modular design algorithm based on template and orienting hereditary variation and the vehicle failure modes algorithm analyzed based on distance travelled weighted fuzzy clustering.
Further, the Xian Xia shops proposed algorithm step of described collaborative filtering based on the uncertain neighbour of position weighting is:
Step 1.1) first the similarity of user and product is carried out position weighting with the geographical position factor of user, to ensure data validity；
Step 1.2) by introducing Near Neighborhood Factor in customer group and product, neighbour's point set of adaptively selected prediction recommendation target is as recommending group, and the trust subgroup that calculating probability is higher；
Step 1.3) calculate Xian Xia shops recommendation list finally by uncertain neighbour's dynamic measurement method.
Further, described care products set meal modular design algorithm steps based on template and orientation hereditary variation is:
Step 2.1) gather the price range of vehicle, consumer select in the past custom, accessory brand influence force data；
Step 2.2) it is combined according to the maintenance set decking made
Step 2.3) use orientation Mutation Arithmetic of GA for combined result, use binary system whole real number hybrid coding, use reflection method to calculate fitness function Kauai and apply selection pressure to colony, and the optimum individual of every generation has been carried out single variation, according to predeterminated target, maintenance set meal set is oriented optimization；
Step 2.4) calculate the maintenance set meal set for this vehicle and the maintenance set meal that can be accepted extensively by consumer.
Further, described vehicle failure modes algorithm steps based on distance travelled weighted fuzzy clustering analysis is:
Step 3.1) gather specific vehicle and the detection of vehicular traffic and the big data of maintenance record, these big data include: the parameters such as the type of fault, fault parameter, time of failure；
Step 3.2) carry out standardization fault data matrix according to above-mentioned big data, fault data matrix uses the feature of the distance travelled distribution function of fault generation be weighted, and then sets up fuzzy similarity matrix, and initialize Subject Matrix；
Step 3.3) then start iterative computation, approach the minimum of object function convergence；
Step 3.4) after iteration terminates, final Subject Matrix judge the class belonging to data, analyze with fault occurs relevant key parameter, such as distance travelled, upper road time, parameter values for detection, obtain fault cluster result.
The invention has the beneficial effects as follows:
(1) " e repaiies intelligence choosing " platform
" e repair intelligence choosing " is the O2O platform orientated as and provide precisely service after automobile.Platform services after providing accurate, quick, the most comprehensive, one-stop car for numerous car owners, service content contain carwash, maintain, keep in repair, improve looks, numerous aspects such as rescue.Platform can according to car owner maintain the car custom and maintenance record etc., recommend optimal service for car owner, meet the automobile maintenance demand of car owner nearby.
While servicing car owner, " E repaiies intelligence choosing " passing through " cloud computing technology " is that businessman provides free information-based support, to meet the demands such as the daily maintenance management of businessman, stock control, purchasing management, sales management, customer relation management.By " E repaiies intelligence choosing, and " the businessman management end APP of platform, the operation that businessman boss can understand each shops in real time is dynamic, it is achieved mobile anywhere or anytime manages.
Platform provides maintenance product for car owner, is guided by mobile phone A PP and goes car owner to go to join shops under line and consume.Platform is that unified shop of building and operation standard are formulated in each Urban Operation center simultaneously, it is provided that supply chain and technical support.The profit of platform is essentially from platform value-added services such as advertisement, product promotion, supply chain services.
(2) Urban Operation center
Integrated lubricant distributor, sets up Urban Operation center in each main cities, provides unified management and service for Xian Xia shops.Service content includes shop of building, training, public technology platform, material allocation etc..The profit at Urban Operation center is also from above service.
(3) shops is serviced under line
Under line by the way of joining, build and there is unifying identifier, unified decoration style, the shops of unified operation standard, and provide standardized service by these shops for car owner.Owing to shop standard, supply chain support, the importing of standard are built in upper end, add the competitiveness of Xian Xia shops.The profit of Xian Xia shops is essentially from the platform support such as platform water conservancy diversion, spare and accessory parts are preferential.
(4) car owner
Car owner is guided by APP on line, and online lower shops completes maintenance.In this mode, car owner enjoys service price and the service quality of standard.
Accompanying drawing explanation
Fig. 1 is car owner's end entire block diagram of the present invention；
Fig. 2 is businessman's end entire block diagram of the present invention.
Detailed description of the invention
Below with reference to the accompanying drawings and in conjunction with the embodiments, the present invention is described in detail.
With reference to shown in Fig. 1, a kind of e repaiies intelligence and selects the accurate service platform of automobile, including client, server end and data base, together with described data base and server end are built by publicly-owned cloud, described client is connected by the interface being arranged on server end and accesses server end, described client includes businessman's end and car owner's end, it is characterised in that:
Described businessman end includes registering log-in module, bench top module, smart message module, operation centre's module, my module, order processing flow module, described bench top module, operation centre's module, order processing flow module and message module are for configuring the business information in the application of automobile market businessman, and described registration log-in module, smart message module and my module are for configuring the general module information of conventional APP；The business information of described bench top module configuration comprises: retail shop shows and functional performance information when daily sales, accumulative income, account balance, the various state of order and operation centre's information；The business information of described operation centre module configuration comprises: adds commodity, treat that added merchandise control, undercarriage merchandise control, merchandise control on sale and main management vehicle are arranged, for providing a whole set of management of product scheme on line for businessman；Described I module configuration general APP information comprise: order switch, my wallet, trade company's certification and the basic setup information of shop and APP；
Described car owner's end includes registering login module, and intelligence selects shop module, my module, maintenance instruction module, Ordering Module and evaluation module；Described intelligence selects shop module for the exhibition information in differently configured kind shop；Described maintenance instruction module, according to the different vehicle of car owner, vehicle conditions, configures e and repaiies intelligence and select the big data algorithm of platform Intelligent Matching maintenance set meal；My module described be used for configuring reward voucher use, manage, evaluate, order list and individual's related data and configuration information.
Described data base uses MySQL database, and described server uses SpringMVC, Spring and Mybatis to integrate formula server.
The interface of described server uses Restful style.
Described data base configures technical data and the auto parts machinery data of multiple different brands model of storage various, gathers the technical data storing 20,000 various, the accessory data of more than 40 ten thousand different brands models in the present embodiment.
Described car owner's end is additionally provided with data collection point, and for Real-time Collection user data, described user data includes user's vehicle, age, is accustomed to car custom, zone of action and maintenance.
The intelligence of described car owner's end is selected the e in shop module and maintenance instruction module to repair intelligence to select the big data algorithm of platform to include: weight the Xian Xia shops proposed algorithm of the collaborative filtering of uncertain neighbour based on position, based on template and the care products set meal modular design algorithm of orientation hereditary variation and the vehicle failure modes algorithm analyzed based on distance travelled weighted fuzzy clustering.
The Xian Xia shops proposed algorithm step of described collaborative filtering based on the uncertain neighbour of position weighting is:
Step 1.1) first the similarity of user and product is carried out position weighting with the geographical position factor of user, to ensure data validity；
Step 1.2) by introducing Near Neighborhood Factor in customer group and product, neighbour's point set of adaptively selected prediction recommendation target is as recommending group, and the trust subgroup that calculating probability is higher；
Step 1.3) calculate Xian Xia shops recommendation list finally by uncertain neighbour's dynamic measurement method.
Described care products set meal modular design algorithm steps based on template and orientation hereditary variation is:
Step 2.1) gather the price range of vehicle, consumer select in the past custom, accessory brand influence force data；
Step 2.2) it is combined according to the maintenance set decking made
Step 2.3) use orientation Mutation Arithmetic of GA for combined result, use binary system whole real number hybrid coding, use reflection method to calculate fitness function Kauai and apply selection pressure to colony, and the optimum individual of every generation has been carried out single variation, according to predeterminated target (as increased price discrimination, meet accessory brand coverage rate etc.), maintenance set meal set is oriented optimization；
Step 2.4) calculate the maintenance set meal set for this vehicle and the maintenance set meal that can be accepted extensively by consumer.
Described vehicle failure modes algorithm steps based on distance travelled weighted fuzzy clustering analysis is:
Step 3.1) gather specific vehicle and the detection of vehicular traffic and the big data of maintenance record, these big data include: the parameters such as the type of fault, fault parameter, time of failure；
Step 3.2) carry out standardization fault data matrix according to above-mentioned big data, fault data matrix uses the feature of the distance travelled distribution function of fault generation be weighted, and then sets up fuzzy similarity matrix, and initialize Subject Matrix；
Step 3.3) then start iterative computation, approach the minimum of object function convergence；
Step 3.4) after iteration terminates, final Subject Matrix judge the class belonging to data, analyze with fault occurs relevant key parameter, such as distance travelled, upper road time, parameter values for detection, obtain fault cluster result.
The foregoing is only the preferred embodiments of the present invention, be not limited to the present invention, for a person skilled in the art, the present invention can have various modifications and variations.All within the spirit and principles in the present invention, any modification, equivalent substitution and improvement etc. made, should be included within the scope of the present invention.
Claims (9)
1.e repaiies intelligence and selects the accurate service platform of automobile, including client, server end and data base, together with described data base and server end are built by publicly-owned cloud, described client is connected by the interface being arranged on server end and accesses server end, described client includes businessman's end and car owner's end, it is characterised in that:
Described businessman end includes registering log-in module, bench top module, smart message module, operation centre's module, my module, order processing flow module, described bench top module, operation centre's module, order processing flow module and message module are for configuring the business information in the application of automobile market businessman, and described registration log-in module, smart message module and my module are for configuring the general module information of conventional APP；The business information of described bench top module configuration comprises: retail shop shows and functional performance information when daily sales, accumulative income, account balance, the various state of order and operation centre's information；The business information of described operation centre module configuration comprises: adds commodity, treat that added merchandise control, undercarriage merchandise control, merchandise control on sale and main management vehicle are arranged, for providing a whole set of management of product scheme on line for businessman；Described I module configuration general APP information comprise: order switch, my wallet, trade company's certification and the basic setup information of shop and APP；
Described car owner's end includes registering login module, and intelligence selects shop module, my module, maintenance instruction module, Ordering Module and evaluation module；Described intelligence selects shop module for the exhibition information in differently configured kind shop；Described maintenance instruction module, according to the different vehicle of car owner, vehicle conditions, configures e and repaiies intelligence and select the big data algorithm of platform Intelligent Matching maintenance set meal；My module described be used for configuring reward voucher use, manage, evaluate, order list and individual's related data and configuration information.
E the most according to claim 1 repaiies intelligence and selects the accurate service platform of automobile, it is characterised in that described data base uses MySQL database, and described server uses SpringMVC, Spring and Mybatis to integrate formula server.
E the most according to claim 1 and 2 repaiies intelligence and selects the accurate service platform of automobile, it is characterised in that the interface of described server uses Restful style.
E the most according to claim 1 repaiies intelligence and selects the accurate service platform of automobile, it is characterised in that described data base configures technical data and the auto parts machinery data of multiple different brands model of storage various.
E the most according to claim 1 repaiies intelligence and selects the accurate service platform of automobile, it is characterized in that, described car owner's end is additionally provided with data collection point, and for Real-time Collection user data, described user data includes user's vehicle, age, is accustomed to car custom, zone of action and maintenance.
E the most according to claim 1 repaiies intelligence and selects the accurate service platform of automobile, it is characterized in that, the intelligence of described car owner's end is selected the e in shop module and maintenance instruction module to repair intelligence to select the big data algorithm of platform to include: weight the Xian Xia shops proposed algorithm of the collaborative filtering of uncertain neighbour based on position, based on template and the care products set meal modular design algorithm of orientation hereditary variation and the vehicle failure modes algorithm analyzed based on distance travelled weighted fuzzy clustering.
E the most according to claim 6 repaiies intelligence and selects the accurate service platform of automobile, it is characterised in that the Xian Xia shops proposed algorithm step of described collaborative filtering based on the uncertain neighbour of position weighting is:
Step 1.1) first the similarity of user and product is carried out position weighting with the geographical position factor of user, to ensure data validity；
Step 1.2) by introducing Near Neighborhood Factor in customer group and product, neighbour's point set of adaptively selected prediction recommendation target is as recommending group, and the trust subgroup that calculating probability is higher；
Step 1.3) calculate Xian Xia shops recommendation list finally by uncertain neighbour's dynamic measurement method.
E the most according to claim 6 repaiies intelligence and selects the accurate service platform of automobile, it is characterised in that described care products set meal modular design algorithm steps based on template and orientation hereditary variation is:
Step 2.1) gather the price range of vehicle, consumer select in the past custom, accessory brand influence force data；
Step 2.2) it is combined according to the maintenance set decking made
Step 2.3) use orientation Mutation Arithmetic of GA for combined result, use binary system whole real number hybrid coding, use reflection method to calculate fitness function Kauai and apply selection pressure to colony, and the optimum individual of every generation has been carried out single variation, according to predeterminated target, maintenance set meal set is oriented optimization；
Step 2.4) calculate the maintenance set meal set for this vehicle and the maintenance set meal that can be accepted extensively by consumer.
E the most according to claim 6 repaiies intelligence and selects the accurate service platform of automobile, it is characterised in that described vehicle failure modes algorithm steps based on distance travelled weighted fuzzy clustering analysis is:
Step 3.1) gather specific vehicle and the detection of vehicular traffic and the big data of maintenance record, these big data include: the parameters such as the type of fault, fault parameter, time of failure；
Step 3.2) carry out standardization fault data matrix according to above-mentioned big data, fault data matrix uses the feature of the distance travelled distribution function of fault generation be weighted, and then sets up fuzzy similarity matrix, and initialize Subject Matrix；
Step 3.3) then start iterative computation, approach the minimum of object function convergence；
Step 3.4) after iteration terminates, final Subject Matrix judge the class belonging to data, analyze with fault occurs relevant key parameter, such as distance travelled, upper road time, parameter values for detection, obtain fault cluster result.
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Cited By (23)
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| CN106779103A (en) * | 2016-12-19 | 2017-05-31 | 深圳惠养车科技有限公司 | A kind of self-service cash device of automobile maintenance station |
| CN106961520A (en) * | 2017-03-20 | 2017-07-18 | 北京小米移动软件有限公司 | Carwash based reminding method, device and terminal |
| CN107222542A (en) * | 2017-06-08 | 2017-09-29 | 东华大学 | A kind of construction method of cloud service management system |
| CN107742219A (en) * | 2017-09-28 | 2018-02-27 | 上海赛趣网络科技有限公司 | Socialization customer relation management platform for market after automobile |
| CN108053297A (en) * | 2017-12-30 | 2018-05-18 | 中建材信息技术股份有限公司 | A kind of public cloud is in the occupation mode of automobile industry |
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| CN109754313A (en) * | 2018-12-18 | 2019-05-14 | 斑马网络技术有限公司 | The online cleaning method of vehicle, device, system and storage medium |
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| CN110866770A (en) * | 2018-08-28 | 2020-03-06 | 北京京东尚科信息技术有限公司 | Prediction method and prediction system for vehicle maintenance scheme |
| CN111178032A (en) * | 2019-12-18 | 2020-05-19 | 福建升腾资讯有限公司 | Form batch entry method, system, equipment and medium based on collaborative filtering |
| CN111401586A (en) * | 2020-04-09 | 2020-07-10 | 东风小康汽车有限公司重庆分公司 | Method and device for generating vehicle maintenance recommendation information |
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