Two-dimensional inkjet technology has made great progress in colorful plane printing. However, color printing technology for three-dimensional model is currently only at the exploratory stage; there are few reports on this issue. In this article, a free-form surface-oriented five-axis single-point printing technology with exclusive color nozzle is proposed. The single-point color nozzle consists of four print heads: prints cyan, magenta, yellow, and black pigment. For high-efficiency color printing, each print head prints on the same single point when the color nozzle moves along the surface. The method of color printing along the surface normal direction is proposed as normal direction printing mode. The algorithm of print point generation is introduced, and the path planning method of self-adaptive slicing and self-adaptive printing filling is proposed. In addition, a five-axis single-point printing platform is designed. Experiments are done to demonstrate the feasibility of the printing system.

No abstract

No abstract

With the rapid development of social economy, the importance of ecological civilization is increasing day by day. The level of environmental monitoring will directly affect the control of total pollution sources and the evaluation of environmental quality. Crowd sensing is to use the group computing power of users with smart devices to quickly collect surrounding multidimensional data, analyze and calculate based on these massive perception data, and then dig out group behavior patterns and other regular information. In order to meet the basic requirements of environmental protection work put forward by the government in the new era, this paper proposes mobile positioning and crowd sensing technologies, explains the distribution map method and adaptive weighting data fusion related algorithms, and designs and develops a mobile positioning system based on mobile positioning. The system of crowd sensing of urban healthy street monitoring is designed, and then we use this PM2.5 monitoring system to monitor the relevant environmental data of a street in Shanghai and use normalization to process the experimental data. The experimental data and statistical results show that this performance of the system is good, and the accuracy of image PM2.5 monitoring reaches 90%–95%. More than 90% of street residents are also very satisfied with this system, believing that it can play a role in supervising urban healthy street.

No abstract