[0036] In order to make the objectives, technical solutions, and advantages of the present invention clearer, the present invention will be further described in detail below in conjunction with specific embodiments and with reference to the accompanying drawings. It should be understood that these descriptions are only exemplary and are not intended to limit the scope of the present invention. In addition, in the following description, descriptions of well-known structures and technologies are omitted to avoid unnecessarily obscuring the concept of the present invention.
[0037] The terms used in the present invention are only for the purpose of describing specific embodiments and are not intended to limit the present invention. The singular forms "a", "said" and "the" used in the present invention and the appended claims are also intended to include plural forms, unless the context clearly indicates other meanings. It should also be understood that the term "and/or" used herein refers to and includes any or all possible combinations of one or more associated listed items.
[0038] Such as figure 1 As shown, in one embodiment, the smart city data processing method may include the following steps:
[0039] S1) The application server receives the user request data sent by the user terminal through the communication unit, and then extracts the characteristic information of the user request data through the data extraction unit.
[0040] Specifically, the characteristic information of the data requested by the user includes: related topics of the data requested by the user, core word information, core word sequence, word frequency, etc. User terminals are smart phones, notebook computers, tablet computers, desktop computers and other smart devices with communication functions.
[0041] S2) The data analysis unit judges whether the user requested data includes security feature data according to the feature information of the user requested data.
[0042] Specifically, if the data analysis unit determines that the user request data includes security feature data, S2.1 is executed, that is, the application server allocates the user request data to the smart police unit. Among them, the safety feature data is data related to safety, for example: data containing key information such as distress calls and alarms.
[0043] In this way, the smart city service distribution system can identify user requests containing security feature data, and quickly distribute them to smart police units without going through the response value calculation step, realizing rapid response and distribution to security-related user requests .
[0044] S3) The response value calculation unit in the application server calculates the response value of each smart city business unit relative to the user request data; this step includes:
[0045] S3.1) Access the smart city database and extract historical user request data of each smart city business unit, and then create a historical dimension vector for each historical user request data.
[0046] Preferably, the smart city database includes multiple smart city business unit sub-databases, and each sub-database stores historical user request data of a corresponding smart city business unit. Store the created historical dimension vector and corresponding historical user request data in the corresponding smart city business unit sub-database.
[0047] S3.2) Create an instant dimensional vector for the data requested by the current user.
[0048] S3.3) According to the analysis of the real-time dimension vector and the historical dimension vector, the n historical dimension vectors that are closest to the real-time dimension vector in each smart city business unit are obtained.
[0049] Specifically, the distance function is used to calculate the distance between the instant dimension vector and each historical dimension vector, and the distance function for calculating the distance between the instant dimension vector and the historical dimension vector is
[0050] d=||A-Y|| 2
[0051] Where the dimension vector space is the c-dimensional real vector space R c , A is the instant dimension vector, and Y is the historical dimension vector in the current smart city business unit;
[0052] Sort the calculated distances in ascending order, and then select the n historical dimension vectors with the smallest distance.
[0053] S3.4) Calculate the dimension value of each smart city business unit based on the distance analysis between n historical dimension vectors and instant dimension vectors;
[0054] The dimension value is used to indicate the matching degree of the user request data with the current smart city business unit. The smaller the dimension value of the smart city business unit, the more the user request data matches the current smart city business unit; the larger the dimension value, the user request data The less it matches the current smart city business unit.
[0055] Preferably, the calculation formula of the dimension value is:
[0056]
[0057] Where A is the instant dimension vector, i is the index of the historical dimension vector, B i Is the i-th closest historical dimension vector of the instant dimension vector in the current smart city business unit, and n is the number of historical dimension vectors that are closest to the instant dimension vector in the current smart city business unit.
[0058] S3.5) Calculate the response value of each smart city business unit relative to the user request data according to the dimension value of each smart city business unit and the urgency of the user request data. The urgency of the user request data is used to indicate the urgency of the user request data to be processed.
[0059] Specifically, the response value calculation formula is:
[0060]
[0061] Where S is the response value, m is the urgency of the user request data, α is the enhancement index, A is the instant dimension vector, i is the index of the historical dimension vector, and B i Is the i-th closest historical dimension vector of the instant dimension vector in the current smart city business unit, and n is the number of historical dimension vectors that are closest to the instant dimension vector in the current smart city business unit.
[0062] Because the dimension value is the key factor in calculating the response value, the enhancement index α is set when calculating the response value. The enhancement index α is used to control the enhancement degree of the dimensional value, thereby increasing the degree of influence of the dimensional value on the calculation of the response value. Make the calculation result of the response value more accurate.
[0063] Preferably, word segmentation is performed on the user request data to filter out keywords. The keywords include modal particles and core words. The keyword frequency information is analyzed, ie the frequency of each keyword, and then the urgency is analyzed. The urgency calculation formula is
[0064]
[0065] Where a is the keyword index, b is the number of keywords, C a Is the weight of the a-th keyword, M a Is the word frequency of the a-th keyword. The core words are the vocabulary that may usually be included in an incident that requires emergency treatment.
[0066] S4) The application server sends the response value of each smart city business unit to the service mapping server. The service mapping server generates a service mapping instruction based on the response value of each smart city business unit, and then maps the user request data to the corresponding smart city service Unit and store user request data in the smart city database.
[0067] The present invention can analyze user request data, select user request data containing safety-related data, and directly distribute them to the smart city police unit, analyze the degree of urgency, and perform emergency processing on emergencies. Therefore, the situation of irreparable loss caused by the failure of emergency treatment to be urgently handled is avoided.
[0068] In addition, the present invention allocates the corresponding smart city business unit to the user request data by calculating the response value of each smart city business unit relative to the user request data, which not only greatly improves efficiency and reduces labor costs, but also Reduce the inaccurate distribution results due to manual distribution.
[0069] In addition, the present invention creates a historical dimension vector through the historical request data in the sub-database of each smart city business unit, thereby calculating the dimension value of each smart city business unit, and according to the dimension value and user of each smart city business unit The urgency value of the requested data calculates the response value of each smart city business unit relative to the user request data, and matches the smart city business unit most suitable for the current user request based on the response value.
[0070] The present invention matches the smart city business unit most suitable for the user request based on the response value, which not only greatly improves the efficiency and reduces the labor cost, but also reduces the inaccurate distribution result caused by manual distribution. In the present invention, the more historical user request data, the more accurate the finally calculated response value, and the more accurate the matching smart city business unit.
[0071] Preferably, after the user data is mapped to the corresponding smart city business unit, the user request data and the corresponding instant dimension vector are stored in the corresponding smart city business unit sub-database. In this way, it can be used as historical user request data to process the next user request data. The more times the system is used to process user request data and the more historical user request data, the more accurate the processing result of user request data will be.
[0072] Preferably, the smart city business unit includes a smart police unit, a smart government unit, and a smart transportation unit. The smart police unit is used to prevent and stop illegal and criminal activities, and to process information related to personal safety and social security; the smart government unit is used to handle administrative approvals, government services, and consultations; the smart traffic unit is used to manage road traffic , Publish traffic data, process traffic-related requests and information.
[0073] Preferably, after receiving the data requested by the user, the smart police unit analyzes the urgency of the data requested by the user, and if the current location of the user is located immediately after the preset threshold is reached, it will contact the user as soon as possible, and contact the user closest to the current location Joint rescue by the police department of
[0074] In one embodiment, step S4 includes:
[0075] S4.1) The application server receives a list of response values of all smart city business units corresponding to the data requested by the user.
[0076] S4.2) The application server selects the smart city business unit with the highest response value, and generates a business mapping instruction based on the selected data.
[0077] S4.3) The service mapping server maps the user request data to the corresponding smart city service unit in response to the service mapping instruction, and stores the user request data in the smart city database. In addition, the user request data can also be stored in the corresponding smart city business unit sub-database.
[0078] In this embodiment, based on the response value list, the user request data is allocated to the smart city business unit with the highest response value. In this way, the user or management personnel are not required to select the data distribution requested by the user, which improves the efficiency and convenience of the data distribution requested by the user, and reduces related labor costs.
[0079] In another embodiment, step S4 includes:
[0080] S4.1) The application server receives the response value list of all smart city business units corresponding to the user request data;
[0081] S4.2) The application server selects the first L smart city business units with the largest response value, generates a user selection list and sends it to the user terminal, the user selects according to his needs, and generates user selection data;
[0082] Preferably, L is the number of smart city business units in the user selection list. L can be set according to user needs or the accuracy of the response value. Generally, L is set to 3.
[0083] S4.3) The user terminal sends the user selection data to the application server, and the application server generates a service mapping instruction based on the selection data and sends it to the service mapping server;
[0084] S4.4) The service mapping server maps the user request data to the corresponding smart city service unit in response to the service mapping instruction.
[0085] In this embodiment, after receiving the response value list, the application server sends the list of L smart city service units with the highest response value to the user terminal, and the user selects the smart city service unit for further consultation. When allocating user request data to smart city service units, this embodiment combines system recommendation and user active selection, giving the user a space for independent selection, and can effectively improve the user experience.
[0086] See figure 2 In one embodiment, the smart city service distribution system includes a user terminal, a smart city cloud platform, and multiple smart city service units. The user terminal and the smart city business unit respectively have a communication connection with the smart city cloud platform. User terminals include smart communication devices such as smart phones, notebook computers, and desktop computers.
[0087] The smart city cloud platform includes a business mapping server, an application server, and a smart city database. Among them, the business mapping server and the smart city database respectively have a communication connection with the application server.
[0088] The application server includes a communication unit, a data extraction unit, a data analysis unit and a response value calculation unit. Among them, the data extraction unit is used to extract the characteristic information of the data requested by the user and send it to the data analysis unit; the data analysis unit is used to analyze whether the characteristic information of the data requested by the user contains security feature information. The response value calculation unit is used to calculate the response value of each smart city business unit with respect to the data requested by the user.
[0089] The application server sends the response value of each smart city business unit to the business mapping server. The business mapping server generates a business mapping instruction based on the response value of each smart city business unit, and then sends the user request data to the corresponding smart city business unit. And store user request data in the smart city database.
[0090] The above are only specific embodiments of the present invention, but the protection scope of the present invention is not limited thereto. Any person skilled in the art can easily think of changes or substitutions within the technical scope disclosed by the present invention. It should be covered within the protection scope of the present invention.
