In the era of big data, smart cities have become a promising prospect for governments, citizens, and industrials. Many ideas and their derived systems for smart cities depend on big data for achieving a goal of data intelligence. However, there is an urgent transformation trend from data intelligence to service intelligence in the vision of smart cities due to the living requirements of citizens. People-centric service intelligence in smart cities has to support the realization of people’s needs within urban and social domains. This paper introduces a concept of people-centric service intelligence, defines the level of it and its challenges in the aspect of infrastructure, human dynamics, human understanding and prediction, and the human–machine interface. Then, this paper proposes the theoretical framework and technical frameworks of people-centric service intelligence, and the service intelligence schemas for future construction of smart cities. It will be helpful for governments and industries to design people-centric service intelligence for improving the quality of life, the capabilities of good sustainability, and better development.

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Visual landmarks are important navigational aids for research into and design of applications for last mile pedestrian navigation, e.g., business card route of pedestrian navigation. The business card route is a route between a fixed origin (e.g., campus entrance) to a fixed destination (e.g., office). The changing characteristics and combinations of various sensors’ data in smartphones or navigation devices can be viewed as invisible salient landmarks for business card route of pedestrian navigation. However, the advantages of these invisible landmarks have not been fully utilized, despite the prevalence of GPS and digital maps. This paper presents an improvement to the Dempster–Shafer theory of evidence to find invisible landmarks along predesigned pedestrian routes, which can guide pedestrians by locating them without using digital maps. This approach is suitable for use as a “business card” route for newcomers to find their last mile destinations smoothly by following precollected sensor data along a target route. Experiments in real pedestrian navigation environments show that our proposed approach can sense the location of pedestrians automatically, both indoors and outdoors, and has smaller positioning errors than purely GPS and Wi-Fi positioning approaches in the study area. Consequently, the proposed methodology is appropriate to guide pedestrians to unfamiliar destinations, such as a room in a building or an exit from a park, with little dependency on geographical information.

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This paper presents a new method for improving the accuracy of GPS/IMU/DMI integrated high-precision positioning system mounted on land vehicles. The system comprises a Position and Orientation System (POS) Computer System, an Inertial Measurement Unit (IMU), a Distance Measuring Indicator (DMI) and two Global Positioning System (GPS) antenna. The system provides continuous and accurate vehicle position and orientation information through areas of poor or no Global Positioning System (GPS) service. The relation among vehicle frame, reference frame, IMU frame and DMI frame are very important, a GPS/IMU/DMI integrated high-precision positioning approach is introduced in this paper to efficiently measure and calibrate these relations in order to improve the precision of system. Accurate measurements of the position parameters are necessary to ensure optimum GPS/IMU/DMI integrated position performance. At first, paper introduces several professional nouns, then brings forward Seven sets of parameters should be measure in this system. At last , a testing Vehicle has been designed to testing the availability, feasibility, and veracity of system. The result indicate that we can improve the precision of GPS/IMU/DMI integrated high-precision positioning system not only through ameliorating arithmetic ,but also using system project idea.