ABSTRACT:With the goal to achieve an accuracy navigation within the building environment, it is critical to explore a feasible way for building the connectivity relationships among 3D geographical features called in-building topology network. Traditional topology construction approaches for indoor space always based on 2D maps or pure geometry model, which remained information insufficient problem. Especially, an intelligent navigation for different applications depends mainly on the precise geometry and semantics of the navigation network. The trouble caused by existed topology construction approaches can be smoothed by employing IFC building model which contains detailed semantic and geometric information. In this paper, we present a method which combined a straight media axis transformation algorithm (S-MAT) with IFC building model to reconstruct indoor geometric topology network. This derived topology aimed at facilitating the decision making for different in-building navigation. In this work, we describe a multi-step deviation process including semantic cleaning, walkable features extraction, Multi-Storey 2D Mapping and S-MAT implementation to automatically generate topography information from existing indoor building model data given in IFC.

ABSTRACT:Public security incidents have been increasingly challenging to address with their new features, including large-scale mobility, multistage dynamic evolution, spatio-temporal concurrency and uncertainty in the complex urban environment, which require spatiotemporal association analysis among multiple regional video data for global cognition. However, the existing video data organizational methods that view video as a property of the spatial object or position in space dissever the spatio-temporal relationship of scattered video shots captured from multiple video channels, limit the query functions on interactive retrieval between a camera and its video clips and hinder the comprehensive management of event-related scattered video shots. GeoVideo, which maps video frames onto a geographic space, is a new approach to represent the geographic world, promote security monitoring in a spatial perspective and provide a highly feasible solution to this problem. This paper analyzes the large-scale personnel mobility in public safety events and proposes a multi-level, event-related organization method with massive GeoVideo data by spatio-temporal trajectory. This paper designs a unified object identify(ID) structure to implicitly store the spatio-temporal relationship of scattered video clips and support the distributed storage management of massive cases. Finally, the validity and feasibility of this method are demonstrated through suspect tracking experiments.

Storage reliability, which describes the failure or deterioration of items in a dormant state, is considered in this paper. The study presented here is focused on the estimation of the storage reliability after a certain amount of storage time. We start with simple non‐parametric estimation of the current reliability and then study the problem of parametric estimation based on a simple Weibull distribution assumption. Both maximum likelihood estimation and graphical techniques are considered in this case. The study is useful for planning a storage environment and making a decision about the maximum length of storage. Furthermore, the information can be used in the design and improvement of products for which the storage is an important part of the product's life cycle. A numerical example is provided to enlighten the idea.