Real-time urban traffic monitoring has become an important part of modern urban management, and traffic big data collected by video monitoring is wildly applied to urban management and traffic control. However, such huge citywide monitoring traffic big data is rarely used for urban traffic and urban computing research. The vehicle type mining and application analysis were implemented on the citywide monitoring traffic big data of a provincial capital city. Firstly, three types of vehicles with important influence on urban traffic:periodic private car, taxi and public commuter bus were defined. And the corresponding mining method for each type of vehicles was proposed. Experiments on 120 million vehicle records collected from 1704 video monitoring points in Jinan demonstrated the effectiveness of the proposed definitions and mining methods. Secondly, with four communities as examples, the residents' traffic modes and the relationships between the modes and the distribution of surrounding Points of Interest (POI) were mined and analyzed. Moreover, the potential applications of the urban traffic big data incorporated with POI in urban planning, demand forecasting and preference recommendation were explored.

Aiming at the possible fraud problem of maintenance service picture information in industry chain collaboration Software as a Service (SaaS) platform's after sales maintenance service, a scheme for collecting and dealing with the after-sales service information by mobile intelligent terminal equipment based on Android platform was proposed. Firstly, the proposed solution collected maintenance service information through processing of digital image of mobile intelligent terminal. Secondly, the proposed solution utilized the recognition technology of images and characters for key information contained in maintenance service information such as chassis number and odometer. Thirdly, the proposed solution embedded the above key information in the collected images via digital watermarking technology. Lastly, mobile intelligent terminal and the after-sales service system were integrated through Web service. The feasibility and effectiveness about the scheme of after-sales service information acquisition based on the Android platform are verified by specific use of after-sales service image information acquisition to prevent fraud in industry chain collaboration SaaS platform's after sales maintenance service.

A workflow customization model for a collaborative Software-as-a-Service (SaaS) platform of industrial chains was proposed based on the mapping between workflow with operation and the custom relationship between the enterprise groups with workflow. A drive rule and a load and control mode of the workflow model were proposed to provide the dynamic load based on the identities of users. The proposed method was validated by the workflow customization on out application of the after service of automobile parts industrial chains, which showed that it met the needs of workflow customization on the collaborative SaaS platform of industrial chains.