Early fire detection using convolutional neural networks during surveillance for effective disaster management

Virtual reality geographical interactive scene semantics research for immersive geography learning

A network virtual reality (VR) engine for interactive analysis and smart city immersive visualization which integrates several latest information technologies, i.e., Web virtual reality (WebVR), Internet of Things (IoT), and three-dimensional (3-D) geographical information system (3-DGIS) with peer-to-peer (P2P) network, has been proposed in this study. It can be used in big spatial data (e.g., remote sensing data) organization and presentation while achieving the online sharing by hash-based P2P networks. In the P2P network, a map, which contains the real geographic space users and the virtual scene user avatar with prep the virtual network nodes, has been made. Moreover, it can also support the following integrated functions of VRGIS: 3-D spatial analysis function, 3-D visualization for spatial information process, and Web engine for 3-D globe and smart big city. To evaluate WebVRGIS system, a user study had been conducted by comparing it with virtual community system. The performance evaluation results had confirmed the higher usability and user satisfaction of the proposed WebVRGIS system.

Virtual Reality Smart City Based on WebVRGIS

Axial and visibility graph analysis models are combined with GIS and Space Syntax to study the corresponding relationship between street network and specific city life in Hankou, China, based on three scales - city, district, and community, so as to interpret the hidden structure out of complex urban form through the spatial logic of street network. In this paper, a quantitative analysis is made on selected parameters in Space Syntax, including Integration, Choice, density of road, and Ht index. The result indicates that there is certain correlation among these parameters. Moreover, these parameters also present certain changing patterns along with the increase of analysis radius. The results reveal that the street network of Hankou presents a multi-hierarchical structure and spatial wholeness from all these three scales. This characteristic creates vitality and diversity while maintaining the feature of wholeness for the urban space. Research has turned out that community-scale street network performs a positive role to keep neighborhoods alive. Therefore, it is an important strategy for maintaining the vitality of urban space and realizing coordination and unification between parts and the whole. It is proposed in this paper that a good street network is a key factor for carrying forward urban context of Hankou. Undoubtedly, it is worthy of reflecting on large-scale demolition of existing urban space, especially in historical areas. Afterwards, the paper proposes a hierarchically synergetic planning strategy based on the analysis. More attention should be paid to street network to preserve diversity, continuity, and integrity, and finally archive holistically sustainable development within a city.

Assessment of lively street network based on geographic information system and space syntax

In this paper, two mHealth applications are introduced, which can be employed as the terminals of bigdata based health service to collect information for electronic medical records (EMRs). The first one is a hybrid system for improving the user experience in the hyperbaric oxygen chamber by 3D stereoscopic virtual reality glasses and immersive perception. Several HMDs have been tested and compared. The second application is a voice interactive serious game as a likely solution for providing assistive rehabilitation tool for therapists. The recorder of the voice of patients could be analysed to evaluate the long-time rehabilitation results and further to predict the rehabilitation process.

Bigdata Oriented Multimedia Mobile Health Applications

The collaboration of nodes in cognitive wireless networks is a large challenge This paper studies the collaborative multi-hop routing in cognitive networks We propose a new algorithm to construct the collaborative routing in multi-hop cognitive networks Our algorithm takes into account the interference among nodes including primary and secondary users The clustering and collaboration are exploited to improve the performance of collaborative routing in multi-hop cognitive wireless networks with multiple primary and secondary users By analyzing the maximum transmission distance, collaborations, transmission angle control and power control, and channel allocation, we propose a new clustering-based collaborative multi-hop cognitive routing algorithm to attain better network performance Simulation results show that our approach is feasible and effective

Collaborative Multi-hop Routing in Cognitive Wireless Networks

Origin-Destination (OD) traffic anomalies reflect network-level traffic anomaly behaviors, which is significantly dangerous to network operation. OD traffic anomalies in a network are investigated in this paper, using statistical analysis based on principle component analysis (PCA). Firstly, we use PCA method to analyze network traffic characteristics and to divide OD flows in the network into both normal and abnormal subspace. Then in abnormal subspace, OD flows are grouped according to common destination address. At the same time, we compute statistical correlations between OD flows in each group and detect traffic anomaly behavior. Finally, we exploit traffic data from a real network to validate our method. Simulation results show that our approach can effectively and accurately detect OD traffic anomalies.

Xu Ying

Papers

Collaborative Multi-hop Routing in Cognitive Wireless Networks

Statistical analysis for origin-destination traffic anomalies