Qiyan Li

An information integration platform for mobile computing

An information integration platform is developed to transport messages, files, structural data, semi structural data, and stream media at the same time. The GPS (Global Position System) information of the vehicles can be sent to the control center by wireless communication network such as GPRS (General Packet Radio Service), CDMA (Code Division Multiple Access), Internet and Intranet. The information integration platform control center can then dispatch command and receives information from the mobile terminals. GPS, GPRS, CDMA, Internet, Intranet and M-DMB (Mobile Digital Multimedia Broadcasting) network are all integrated into the platform. Different kinds of data can be sent and received simultaneity. The stream media can replay in time. There are two key technologies in the information integration platform; one is server cluster, other is mobile terminal development.

Remote video monitor of vehicles in cooperative information platform

Detection of vehicles plays an important role in the area of the modern intelligent traffic management. And the pattern recognition is a hot issue in the area of computer vision. An auto- recognition system in cooperative information platform is studied. In the cooperative platform, 3G wireless network, including GPS, GPRS (CDMA), Internet (Intranet), remote video monitor and M-DMB networks are integrated. The remote video information can be taken from the terminals and sent to the cooperative platform, then detected by the auto-recognition system. The images are pretreated and segmented, including feature extraction, template matching and pattern recognition. The system identifies different models and gets vehicular traffic statistics. Finally, the implementation of the system is introduced.

Resource Symmetric Dispatch Model for Internet of Things on Advanced Logistics

Business applications in advanced logistics service are highly concurrent. In this paper, we propose a resource symmetric dispatch model for the concurrent and cooperative tasks of the Internet of Things. In the model, the terminals receive and deliver commands, data, and information with mobile networks, wireless networks, and sensor networks. The data and information are classified and processed by the clustering servers in the cloud service platform. The cluster service, resource dispatch, and load balance are cooperative for management and monitoring of every application case during the logistics service lifecycle. In order to support the high performance of cloud service, resource symmetric dispatch algorithm among clustering servers and load balancing method among multi-cores in one server, including NIO (Non-blocking Input/Output) and RMI (Remote Method Invocation) are utilized to dispatch the cooperation of computation and service resources.

Resource sharing and remote utilization in communication servers

The communication cluster servers require many key technologies in an information integration platform. in order to improve dependability, scalability, and other QoS features, we design a system structure to meet these requirements. The resource sharing and remote utilizing are applied to resolving the dynamical resource dispatch and the tasks distribution. The thread model and mechanism of the thread pool in the Non-blocking input/Output (NiO) are created which include a case trigger mechanism. The system successfully resolves thousands of terminals connected to the information integrated platform. Messages, files, data, and other information can transport among the platform, the clients and the terminals.

Warehouse Optimization Model Based on Genetic Algorithm

This paper takes Bao Steel logistics automated warehouse system as an example. The premise is to maintain the focus of the shelf below half of the height of the shelf. As a result, the cost time of getting or putting goods on the shelf is reduced, and the distance of the same kind of goods is also reduced. Construct a multiobjective optimization model, using genetic algorithm to optimize problem. At last, we get a local optimal solution. Before optimization, the average cost time of getting or putting goods is 4.52996 s, and the average distance of the same kinds of goods is 2.35318 m. After optimization, the average cost time is 4.28859 s, and the average distance is 1.97366 m. After analysis, we can draw the conclusion that this model can improve the efficiency of cargo storage.

Cluster Computing in Drug Logistic Monitoring and Management

We applied the cluster computing as a key technology for a drug logistic information system that we developed. In order to improve the dependability, scalability, and other QoS features of the server cluster, resource dynamic dispatching, task distribution, and workflow controlling were among the key issues that we focused in our development.

A Cloud Model for Internet of Things on Logistic Supply Chain

In this paper we propose a cloud model of internet of things for logistic supply chains. In the cloud model, the cloud terminals can collect, receive and deliver information by integration of mobile networks, wireless networks, networks of sensors, including data, video and audio information. The data and information are classified and dealt with in the cloud service platform where the communication cluster servers, application servers, middleware servers and database servers are located. In this model the cluster service, resource dispatch and load balance are cooperative for every application group in the cloud in order to serve for the management and monitoring during the logistic supply chain lifecycle. In order to support high performance of cloud service, NIO (Non-blocking Input/Output) and RMI (Remote Method Invocation) are applied for the resource cooperative dispatch.

An embedded road crack detection system in a cooperative platform

A cooperative platform is studied for improving the efficiency of road crack detection. The platform is mainly divided into a mobile terminal with an embedded road crack detection system, which detects pavement surface cracks, and a control center which analyses the crack information and makes further decisions. The experimental results indicate that this real time platform is more efficient than classical road detection systems. Also a sample case of the platform is given to show the road crack detection results and output. The application of the road crack edge detection was realized in embedded Linux system in the cooperative platform. The evaluation report will be output in real time and sent to the central database from the embedded mobile terminal, including the corresponding position information in the GIS of the cooperative platform.

Study of the intelligent turning machining method based on geometrical feature recognition

Feature recognition is a key technology of the automatic intelligent turning machining method. This paper provides an intelligent turning machining method based on geometrical feature recognition, including putting up viewpoint, direction and cylindrical co-ordinate. For real-loops and unreal-loops in projection, an algorithm is taken forward to recognize the straight faces, turning circle (cone, frustum and cylinder) and slot, and creates a relationship functions among all the loops, determine the machinable turning cutting regions respectively according to the relationship functions. The study resolves the machinable problem in design stage, a method is supported to cooperative design and decreases the cost and save time. a hierarchy architecture of the center controller is constructed including integration process planning.