Narrow Results

This exploration aims to transfer, process and store multimedia information timely, accurately and comprehensively through computer comprehensive technology processing, and organically combine various elements under the background of big data analysis, so as to form a complete intelligent platform design for multimedia information processing and application. In this exploration, the intelligent vehicle monitoring system is taken as an example. Data acquisition, data transmission, real-time data processing, data storage and data application are realized through the real-time data stream processing framework of $\mathrm{\text{Flume}}+\mathrm{\text{Kafka}}+\mathrm{\text{Storm}}$ of big data technology. Data interaction is realized through Spring, Spring MVC, VUE front-end framework, and Ajax asynchronous communication local update technology. Data storage is achieved through Red is cache database, and intelligent vehicle operation supervision system is achieved through multimedia information technology processing. Its purpose is to manage the vehicle information, real-time monitor the running state of the vehicle and give an alarm when there are some problems. The basic functions of vehicle operation monitoring and management system based on big data analysis are realized. The research on the design of vehicle operation monitoring and management system based on big data analysis shows that big data technology can be applied to the design of computer multimedia intelligent platform, and provides a reference case for the development of computer multimedia intelligent platform based on big data analysis.

Twitter is considered as one of the world’s largest social networking sites which allow users to customize their public profile, connect with others and interact with connected users. The proposed work introduces a distributed real-time twitter sentiment analysis and visualization framework by implementing novel algorithms for twitter sentiment analysis called Emotion-Polarity-SentiWordNet. The framework is applied to build an interactive web application called “TwitSenti” which can benefit companies and other organizations in knowing the people’s sentiment towards the aspects such as brands, current events, etc., which in turn helps in quick decision-making and planning marketing strategies. The algorithm is validated against three existing classifiers and hence proved that Emotion-Polarity-SentiWordNet provides highest accuracy value of 85%. Also, the framework showed best scalability results when evaluated through web app as four node clusters, proves to be fast and can scale well with massive data.

BIM (Building Information Model) is a very effective technology in urban rail transit. In order to effectively support collaboration in BIM projects among multispecialty, a new data exchange and sharing interaction is developed to facilitate collaboration interactions. A BIM cloud document sharing model based on inter-specialty collaboration with Revit is established and a special document extraction algorithm is proposed firstly. Furthermore, a technical scheme based on FastDFS and document relationship management is developed for distributed document management with MySQL on a BIM cloud document access center. Finally, the synchronization of design model, document update application and document version information are realized with Kafka message middleware. Thus, the platform can fully support BIM collaboration.