Access Layer Research Articles

Application of Multilevel Local Feature Coding in Music Genre Recognition

When the current method is used to recognize music genre style, the extracted features are not fused, which leads to poor recognition effectiveness. Therefore, the application research based on multilevel local feature coding in music genre recognition is proposed. Features of music are extracted from timbre, rhythm, and pitch, and the extracted features are fused based on D-S evidence theory. The fused music features are input into the improved deep learning network, and the storage system structure is determined from the advantages of cloud storage availability, manageability, and expansibility. It is divided into four modules: storage layer, management layer, structure layer, and access layer. The model of music genre style recognition is constructed to realize the application research based on multilevel local feature coding in music genre recognition. The experimental results show that the recognition accuracy of the proposed method is always at a high level, and the mean square error positively correlated with the number of beats. After segmentation, the waveform is denser, which has a good application effect.

Hybrid IoT and Data Fusion Model for e-Commerce Big Data Analysis

This article is aimed at studying the e-commerce big data recommendation model based on data fusion and the Internet of Things. This article chooses an embedded system for the construction of an e-commerce platform and uses data fusion technology to collect, transmit, and filter useful information from various information sources. Then, the collected information and data are analyzed and integrated, and visualization algorithms are used to better present data analysis, and association rules and structural similarity methods for electronic comparison are uses. This article uses the B/S architecture to design the overall framework of the data access layer, business logic layer, and user presentation layer; collects, organizes, stores, and presents the acquired consumer information; and finally analyzes the e-commerce background, platform performance, and supply and demand analysis. The experimental results show that the average clustering coefficient of the platform (0.7559) is smaller than the average clustering coefficient value of 8 items in the store (0.811) and smaller than the average network diameter and average path length of the online store (3.86, 7.7). Store products are better than store products, and the diameter and length of the product should be larger (2.71, 5.75). The recall rate of the e-commerce big data platform and model matching review method designed in this paper is 5% higher than that of the word matching model method and has a better expected effect in terms of user supply and demand.

Video Freeze Assessment of TPCAST Wireless Virtual Reality: An Experimental Study

Wireless virtual reality (VR) offers a seamless user experience but has to cope with higher sensitivity to temporal impairments induced on the wireless link. Apart from bandwidth dynamics and latency, video freezes and their lengths are important temporal performance indicators that impact on the quality of experience (QoE) of networked VR applications and services. This paper reports an experimental study that focuses on the VR video frame freeze length characteristics of a wireless VR solution. A comprehensive measurement campaign using a commercial TPCAST wireless VR solution with an HTC Vive head-mounted display was conducted to obtain real VR video traces. The number of detected freezes and freeze intensities are reported both accumulated over four room quadrants as well as for each of the four quadrants subject to six transmitter-receiver distances. The statistical analysis of the VR video traces of the different experiments includes histograms of the freeze lengths and cumulative complementary histograms of the freeze length. The results of this analysis offer insights into the density of the underlying distributions of the measured data, illustrate the impact of the room topology on the freeze characteristics, and suggest the statistical modeling of the freeze characteristics as exponential and geometric distributions. The statistical models of the freeze characteristics may be included in wireless VR simulators supporting the development of physical layer, medium access layer, and higher layer functionalities. They also may serve as network-disturbance models for VR QoE studies, e.g., generating realistic freeze events in wireless VR stimuli.

A practical approach for geographic prioritization and targeting of insecticide-treated net distribution campaigns during public health emergencies and in resource-limited settings

BackgroundThe use of data in targeting malaria control efforts is essential for optimal use of resources. This work provides a practical mechanism for prioritizing geographic areas for insecticide-treated net (ITN) distribution campaigns in settings with limited resources.MethodsA GIS-based weighted approach was adopted to categorize and rank administrative units based on data that can be applied in various country contexts where Plasmodium falciparum transmission is reported. Malaria intervention and risk factors were used to rank local government areas (LGAs) in Nigeria for prioritization during mass ITN distribution campaigns. Each factor was assigned a unique weight that was obtained through application of the analytic hierarchy process (AHP). The weight was then multiplied by a value based on natural groupings inherent in the data, or the presence or absence of a given intervention. Risk scores for each factor were then summated to generate a composite unique risk score for each LGA. This risk score was translated into a prioritization map which ranks each LGA from low to high priority in terms of timing of ITN distributions.ResultsA case study using data from Nigeria showed that a major component that influenced the prioritization scheme was ITN access. Sensitivity analysis results indicate that changes to the methodology used to quantify ITN access did not modify outputs substantially. Some 120 LGAs were categorized as ‘extremely high’ or ‘high’ priority when a spatially interpolated ITN access layer was used. When prioritization scores were calculated using DHS-reported state level ITN access, 108 (90.0%) of the 120 LGAs were also categorized as being extremely high or high priority. The geospatial heterogeneity found among input risk factors suggests that a range of variables and covariates should be considered when using data to inform ITN distributions.ConclusionThe authors provide a tool for prioritizing regions in terms of timing of ITN distributions. It serves as a base upon which a wider range of vector control interventions could be targeted. Its value added can be found in its potential for application in multiple country contexts, expediated timeframe for producing outputs, and its use of systematically collected malaria indicators in informing prioritization.

Research on Intelligent Control System of Air Conditioning based on Internet of Things Intelligent Control System of Air Conditioning

The current air conditioning intelligent control system cannot achieve the ideal energy-saving effect. The indoor temperature and humidity control is not good enough either. Therefore, an intelligent air-conditioning control system based on Internet of Things technology is designed. The hardware part of the system includes system control motherboard, sensor module, execution control structure, wireless communication module and access layer. The software includes the design of communication layer, the design of monitoring management, and the design of intelligent indoor air-conditioning temperature remote control algorithm. The experimental results show that the control effect of the intelligent air conditioner is more accurate and energy-saving, the opening degree of the air conditioning valve is larger, and the comfort is improved. The indoor temperature and humidity of the proposed system are both more ideal.

Information exchange platform for digital art teaching in colleges and universities based on internet of things technology

In order to solve the low efficiency and speed of information exchange in the traditional art of digital information exchange platform, the paper proposed and designed a new networking technology based on digital teaching college art information exchange platform.. In support of networking technology, the design needed a teaching information acquisition layer, transport layer, an access layer and a service layer, with the hierarchical construct art digital teaching exchange and sharing of information on the internet. With the support of the platform, ant colony algorithm is improved, and the ant colony algorithm classified information was used to improve art education, teaching information to complete the integration of fine arts. Experimental results show that in the designed exchange platform, the exchange of information was more efficient and has faster responses.

A Blockchain Application Prototype for the Internet of Things

The emergence of the Internet of things (IoT), associated with the explosion in the number of connected objects, and the growth in user needs, makes the Internet network very complex. IoT objects are diverse and heterogeneous, which requires establishing interoperability and efficient identity management on the one hand. On the other hand, centralized architectures such as cloud-based ones can have overhead and high latency, with a potential risk of failure. Facing these challenges, Blockchain technology, with its decentralized architecture based on a distributed peer-to-peer network, offers a new infrastructure that allows IoT objects to interact reliably and securely. In this paper, a new approach is proposed with a three-layer architecture: layer of sensing and collection of data made up of the IoT network, layer of processing and saving of data exchanges at the Blockchain level, and access and visualization layer via a web interface. The prototype implemented in this study allows all transactions (data exchanges) generated by IoT devices to be recorded and stored on a dedicated Blockchain, assuring the security of IoT objects' communications. This prototype also enables access to and visualization of all data and information, thus enhancing the IoT network's transparency.

Energy Efficient UAV-Based Service Offloading Over Cloud-Fog Architectures

Unmanned Aerial Vehicles (UAVs) are poised to play a central role in revolutionizing future services offered by the envisioned smart cities, thanks to their agility, flexibility, and cost-efficiency. UAVs are being widely deployed in different verticals including surveillance, search and rescue missions, delivery of items, and as an infrastructure for aerial communications in future wireless networks. UAVs can be used to survey target locations, collect raw data from the ground (i.e., video streams), generate computing task(s) and offload it to the available servers for processing. In this work, we formulate a multi-objective optimization framework for both the network resource allocation and the UAV trajectory planning problem using Mixed Integer Linear Programming (MILP) optimization model. In consideration of the different stake holders that may exist in a Cloud-Fog environment, we minimize the sum of a weighted objective function, which allows network operators to tune the weights to emphasize/de-emphasize different cost functions such as the end-to-end network power consumption (EENPC), processing power consumption (PPC), UAV’s total flight distance (UAVTFD), and UAV’s total power consumption (UAVTPC). Our optimization models and results enable the optimum offloading decisions to be made under different constraints relating to EENPC, PPC, UAVTFD and UAVTPC which we explore in detail. For example, when the UAV’s propulsion efficiency (UPE) is at its worst (10% considered), offloading via the macro base station is the best choice and a maximum power saving of 34% can be achieved. Extensive studies on the UAV’s coverage path planning (CPP) and computation offloading have been conducted, but none has tackled the issue in a practical Cloud-Fog architecture in which all the elements of the access, metro and core layers are considered when evaluating the service offloading in a distributed architecture like the Cloud-Fog.

Mapping Agricultural Drainage Extent in the U.S. Corn Belt: The Value of Multiple Methods

Highlights A new 30 m resolution drainage extent dataset is explorable through an online web interface. Alternative methods of mapping drainage extent have advantages in different locations. Multiple drainage extent datasets provide tools for improved hydrology assessment in the Corn Belt. Abstract. Artificial drainage is essential to agricultural productivity in much of the Midwest, and has an important impact on hydrology and water quality. Planners, engineers, resource professionals, and others who are interested in Corn Belt hydrology would benefit from increased understanding of existing drainage installations. The objective of this work is to increase access to and understanding of options for estimating subsurface/surface drainage extent and the advantages and disadvantages of different methods to benefit data users who need to know what products are appropriate for their specific application. This includes creating an online accessible drainage estimate data layer for the entire Corn Belt region; comparing three different drainage extent products for this region and investigating the various applications of these three products in four case study locations in Indiana, Iowa, Missouri, and Minnesota. Results show how different drainage datasets can be utilized depending on the nature of the research question and conditions of the investigation. Keywords: Agricultural drainage extent, Geospatial analysis, Tile drainage.

CAPTON—Centralized All-Path Transmission for Over-Subscribed Datacenter Networks

This work addresses an often-overlooked challenge in designing datacenter traffic control schemes. Specifically, most existing schemes were designed for network topologies with non-blocking network core. While this enabled the development of elegant solutions, core networks in practice are more likely to be <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">over-subscribed</i> by the access layer network due to cost considerations. Consequently, existing traffic control schemes may perform sub-optimally in real-world over-subscribed datacenter networks. This work proposes a new centralized flow-based scheduling scheme called CAPTON which schedules flow according to remaining flow size and link capacities to avoid congestion in over-subscribed networks. CAPTON employs all-path transmission to exploit all available paths and redundant links between source and destination hosts to maximize resource utilization and eliminate the need for routing. Unlike switch-based approaches, CAPTON does not require additional support from network switches and thus can be readily deployed in current datacenters equipped with commodity switches.

Reliability and robust resource allocation for Cache-enabled HetNets: QoS-aware mobile edge computing

Mobile edge computing is a key feature of next-generation mobile networks aimed at providing a variety of services for different applications by performing related processing tasks closer to the user equipment. Due to the high frame loss rate during multi-hop transmissions in wireless edge computing networks, the problem of reliability and system safety will be of great importance. Data caching is a necessity to provide reliable edge computing and, at the same time a major consumer of energy. So, we propose a reliable mobile edge computing system using active caching and robust resource allocation approaches. This paper presents an energy-efficient stochastic network calculus framework to control edge-computing data flows for active data-caching systems. In accordance with the entrance processes of different QoS-class data streams, closed-form problems were formulated to determine the correlation between resource utilization and the violation probability of each data flow. Also, in the access layer, this paper proposes a reliable user association and resource allocation approach which maximizes the overall energy efficiency of cache-enabled cellular networks in addition to improving system safety. In this energy-cooperative approach, the power can be shared among the cells using a grid network. The simulation results show that the proposed approach can effectively increase the network reliability and power efficiency while guaranteeing the acceptable fairness level for uniform and hotspot user distribution models. The numerical results also exhibit considerable power saving for different traffic models in addition to increasing the total network throughput by up to 25%.

Intelligent Classification Method of Low Occupancy Big Data Based on Grid Index

In order to enhance the load balance in the big data storage process and improve the storage efficiency, an intelligent classification method of low occupancy big data based on grid index is studied. A low occupancy big data classification platform was built, the infrastructure layer was designed using grid technology, grid basic services were provided through grid system management nodes and grid public service nodes, and grid application services were provided using local resource servers and enterprise grid application services. Based on each server node in the infrastructure layer, the basic management layer provides load forecasting, image backup, and other functional services. The application interface layer includes the interfaces required for the connection between the platform and each server node, and the advanced access layer provides the human-computer interaction interface for the operation of the platform. Finally, based on the obtained main structure, the depth confidence network is constructed by stacking several RBM layers, the new samples are expanded by adding adjacent values to obtain the mean value, and the depth confidence network is used to classify them. The experimental results show that the load of different virtual machines in the low occupancy big data storage process is less than 40%, and the load of each virtual machine is basically the same, indicating that this method can enhance the load balance in the data storage process and improve the storage efficiency.

An English Online Homework Tutoring System Supported by Internet Database

College English tutoring is an important content of current research, and how to provide more effective methods for teaching tutoring is currently a hot research topic. Therefore, this paper designs an Internet-based online tutoring platform for college English teaching, which is accelerated by using the K-means clustering algorithm. The data processing efficiency and processing methods to improve user satisfaction require more practical experience to summarize. In the business logic layer, the uploaded information is mined through the K-means clustering algorithm to form an online tutoring university English database to provide platform data support, realize the business logic judgment of the data, convert the data in the database, and return to the user interface of other formats, to provide users with browsing and consulting. In the data access layer, the data from the business logic layer is processed. After the processing is completed, data can be added, deleted, modified, and checked in the database. Finally, the operation result of the database is fed back to the business logic layer for processing. Experimental results show that the designed platform has good data mining performance, low connection speed and low response delay, good compatibility, low CPU usage, fast resource sharing speed, and high user satisfaction. It can be connected to different operating systems.

Research on Mobile English Learning System Based on iOS

In order to improve the use experience of mobile learning and reduce the response delay caused by the slow positioning of system resources, research on mobile English learning systems based on iOS is proposed. Firstly, the value of realizing mobile learning is objectively analyzed, and the practical significance of the research is clarified from the perspectives of social development and learning conditions. On this basis, taking the intelligent client equipped with an iOS operating system as the hardware condition of the system, the system architecture, including data access layer, business logic layer, and presentation layer, is constructed by MVC. In the model module, it is divided into ten difficulty levels by using the frequency of vocabulary, the length of words, and the number of syllables of a single word. The learning resources of the reading class are uniformly represented by the vector space model, and the improved TF-IDF is used to calculate the weight of eigenvalues in the resources. According to the calculation results, the resources are also divided into ten difficulty levels, and the divided resources correspond to their respective databases and use regular expressions to find the learning resources that match the access request. Finally, with the support of the iOS protocol, the feedback mechanism between each module is constructed by Express.js. By analyzing the access requests sent and received by the view, the timely call to the target database resources is realized to improve the response rate of the system. The test results show that the function of the designed system can be realized stably, and the module response delay time is stable within 1s; under the ideal network environment, the buffer delay is in the range of 0.4–0.6 s, and the loading delay is no more than 1.8 s when the network speed is 3 Mpbs, which has a good user experience.

Secure transmission for cooperative NOMA systems with source‐relay selection

Both cooperative non-orthogonal multiple access (NOMA) and physical layer security (PLS) are promising techniques for future communication systems. This paper investigates the PLS performance of a cooperative NOMA system where multiple sources transmit a superposed message to two users by utilizing either amplify-and-forward (AF) or decode-and-forward (DF) relays in both non-colluding and colluding eavesdropper scenarios. A source-relay selection scheme is proposed for this system aiming at improving the secrecy performance. Additionally, the closed-form expression of the secrecy outage probability (SOP) is derived for the proposed source-relay selection schemes. It is demonstrated that in the proposed schemes, the theoretical results match well with the simulation results. In addition, the proposed schemes outperform the conventional OMA system in terms of SOP.

Effect of Entrepreneurship Education for College Students in the Context of a Mobile Internet Environment

College students are having a difficult time in hunting a job upon graduation. The mobile Internet helps to promote the employment of college graduates. In an environment of mobile Internet, this paper clarifies the current state of Entrepreneurship Education (EE) for college students, and discusses the effectiveness of EE in the context of a mobile Internet environment. The results show that: mobile Internet enriches the substance of EE courses in colleges, improves the environment of EE, facilitates the provision of EE for college students, makes the EE model fairer, and promotes the reform of the model. In addition, the EE platform built for college students can be broken down into three layers: a data access layer, a business logic layer, and a user interface layer.

(Invited) Linking Ionomer/Electrocatalyst Interactions to Membrane Electrode Assembly Performance and Durability in Proton Exchange Membrane Fuel Cells

The proper integration of materials to enable high performing low temperature fuel cell operation has never been more crucial to realizing the isolated (e.g. half-cell or ex-situ) improvements of advanced electrocatalysts, supports and ionomers in an effort to maximize efficiency. The integration pathway for oxygen reduction electrocatalysts, from initial testing in a rotating disk electrode (RDE) to their apex form as porous electrodes in a membrane electrode assembly (MEA) is replete with potential pitfalls. Along the route to improving MEA level electrocatalyst kinetics and electrode transport properties are numerous choices relating to ink formulation (i.e. solvents and solvent ratios), ink processing and deposition methodology, ionomer content and chemistry and electrochemical MEA conditioning. Combined with carbon morphology/porosity, such variables can alter the final electrode morphology, influencing active site accessibility and ORR activity as well as oxygen transport resistance and electrode proton conductivity.[1–5]Here, the development and utilization of in situ diagnostics designed to probe specific phenomena (e.g. catalyst/ionomer interactions, molecular and Knudsen diffusion, electrochemical active site accessibility and catalyst layer proton resistance) will be presented as tools to contrast the ink, processing and fabrication methods necessary to achieve high performance PGM (e.g. Pt/C and Pt alloy/C) and PGM-free (e.g. FeNx/C) electrocatalysts based electrodes. For PGM based MEAs, the dynamic effects of electrochemical conditioning will be examined in an effort to both baseline MEA level performance and decouple the contributions of simultaneous electrocatalyst particle growth and the removal of system impurities.[6] The prerequisite understanding gleaned from the application of electrochemical diagnostics and MEA conditioning procedures will be combined with the development of a novel sulfonated ionic liquid block copolymer ionomer and tailored integration methodology to illustrate a pathway towards improved MEA level performance.[7] Lastly, alterations in ionomer interactions as a function of accelerated stress tests will be discussed, providing insight into the evolving electrode structure as the community targets more robust systems capable of efficient operation for 25,000 hrs.[8]References[1] A. Orfanidi, P.J. Rheinlander, N. Schulte, H.A. Gasteiger, Ink Solvent Dependence of the Ionomer Distribution in the Catalyst Layer of a PEMFC, Journal of The Electrochemical Society. (2018) 11.[2] S. Khandavalli, J.H. Park, N.N. Kariuki, D.J. Myers, J.J. Stickel, K. Hurst, K.C. Neyerlin, M. Ulsh, S.A. Mauger, Rheological Investigation on the Microstructure of Fuel Cell Catalyst Inks, ACS Appl. Mater. Interfaces. (2018) 13.[3] D.A. Cullen, R. Koestner, R.S. Kukreja, Z.Y. Liu, S. Minko, O. Trotsenko, A. Tokarev, L. Guetaz, H.M. Meyer, C.M. Parish, K.L. More, Imaging and Microanalysis of Thin Ionomer Layers by Scanning Transmission Electron Microscopy, J. Electrochem. Soc. 161 (2014) F1111–F1117. https://doi.org/10.1149/2.1091410jes.[4] T. Van Cleve, S. Khandavalli, A. Chowdhury, S. Medina, S. Pylypenko, M. Wang, K.L. More, N. Kariuki, D.J. Myers, A.Z. Weber, S.A. Mauger, M. Ulsh, K.C. Neyerlin, Dictating Pt-Based Electrocatalyst Performance in Polymer Electrolyte Fuel Cells, from Formulation to Application, ACS Appl. Mater. Interfaces. 11 (2019) 46953–46964. https://doi.org/10.1021/acsami.9b17614.[5] G. Wang, L. Osmieri, A.G. Star, J. Pfeilsticker, K.C. Neyerlin, Elucidating the Role of Ionomer in the Performance of Platinum Group Metal-free Catalyst Layer via in situ Electrochemical Diagnostics, J. Electrochem. Soc. 167 (2020) 044519. https://doi.org/10.1149/1945-7111/ab7aa1.[6] S. Kabir, D.J. Myers, N. Kariuki, J. Park, G. Wang, A. Baker, N. Macauley, R. Mukundan, K.L. More, K.C. Neyerlin, Elucidating the Dynamic Nature of Fuel Cell Electrodes as a Function of Conditioning: An ex Situ Material Characterization and in Situ Electrochemical Diagnostic Study, ACS Appl. Mater. Interfaces. 11 (2019) 45016–45030. https://doi.org/10.1021/acsami.9b11365.[7] Y. Li, T.V. Cleve, R. Sun, R. Gawas, G. Wang, M. Tang, Y.A. Elabd, J. Snyder, K.C. Neyerlin, Modifying the Electrocatalyst−Ionomer Interface via Sulfonated Poly(ionic liquid) Block Copolymers to Enable High- Performance Polymer Electrolyte Fuel Cells, ACS Energy Letters. (2020) 6.[8] D.A. Cullen, K.C. Neyerlin, R.K. Ahluwalia, R. Mukundan, K.L. More, R.L. Borup, A.Z. Weber, D.J. Myers, A. Kusoglu, New roads and challenges for fuel cells in heavy-duty transportation, Nature Energy. (2021) 1–13. https://doi.org/10.1038/s41560-021-00775-z.

Impact of MAC Layer on The Hidden and Exposed Terminal Problem in MANET

Wireless networking grows rapidly because of the human desires for mobility and for freedom from tethers, i.e., from physical connections to communication networks. Recent advances in wireless technology have equipped portable computers, such as notebook computers and personal digital assistants with wireless interfaces that allow networked communication even while a user is mobile. We will focus on a particular kind of wireless network: mobile ad hoc networks. A mobile ad hoc network is a self organizing and rapidly deployable network in which neither a wired backbone nor a centralized control exists. The network nodes communicate with one another over scarce wireless channels in a multi-hop fashion. The ad hoc network is adaptable to the highly dynamic topology resulted from the mobility of network nodes and the changing propagation conditions. Generally, protocols used at medium access and physical layers of ad hoc networks are similar to those used in infrastructure based wireless networks. It is a common practise in infrastructure based wireless networks to use pre-data exchange of control information to eliminate the hidden terminal" problem.

On-Demand Satellite Payload Execution Strategy for Natural Disasters Monitoring Using LoRa: Observation Requirements and Optimum Medium Access Layer Mechanisms

Natural disasters and catastrophes are responsible for numerous casualties and important economic losses. They can be monitored either with in-situ or spaceborne instruments. However, these monitoring systems are not optimal for an early detection and constant monitoring. An optimisation of these systems could benefit from networks of Internet of Things (IoT) sensors on the Earth’s surface, capable of automatically triggering on-demand executions of the spaceborne instruments. However, having a vast amount of sensors communicating at once with one satellite in view also poses a challenge in terms of the medium access layer (MAC), since, due to packet collisions, packet losses can occur. As part of this study, the monitoring requirements for an ideal spatial nodes density and measurement update frequencies of those sensors are provided. In addition, a study is performed to compare different MAC protocols, and to assess the sensors density that can be achieved with each of these protocols, using the LoRa technology, and concluding the feasibility of the monitoring requirements identified.

Implementation and future challenges of seismotectonic mapping system for earthquake emergency response

Earthquake emergency response maps represent a set of geographical maps related to the seismic activity, geological tectonic background, assessment of economy and population losses, secondary disaster probability, as well as other information for emergency response and rescue. It requires producing these kinds of maps as quickly as possible after an earthquake. The seismotectonic map is one of the most important maps for earthquake emergency response. In this study, we developed an earthquake emergency response system to produce the map automatically. This paper introduces a intelligent system framework using spatial analysis, version management and web communication technology for emergency response, data maintenance, remote map revision, version management and statistics, which is not discussed in previous studies. The system based on MySQL, ArcGIS platform, python, and curl. It can detect the earthquake fast report proactive. When capturing the official report, it activated the response function module. The system achieved the first version mapping, fault data pushing, and earthquake catalogue updating by data-driven method automatically and rapidly. The mapping process can be divided into map layout and expert knowledge. The expert knowledge part can be divided into a geography map and explanatory note. The system performed well on the map layout and geography map. The explanatory note in the map, which introduces regional tectonics and expert knowledge, can provide the nearest fault’s name, active age, and feature in the first version. Experts need to produce the second version manually. The fault data of 5°×5°area centred on the main shock is clipped and sent to a specified mailbox. The system added the earthquake parameters to the database. The result shows that this system finished these work well automatically and reduce the responds time and data maintenance time. If the earthquake causes serious calamity, seismogeology experts need to collect, summarize and analyse literature, document, and other information for successor versions and even predicting aftershock and disaster. It is practically needed to build a more intelligent and efficient system to produce a successor version of the map and push more knowledge in the future. The challenge in the future is to develop a more intelligent system to self-explain the seismotectonic map and push expert knowledge. This goal can only be achieved by processing expert knowledge data like regional lithology, tectonic structure, paleo earthquake, and historical earthquake in the database layer, data access layer, and business logic layer of the system.