Comprehensive tempo-spatial data collection in crowd sensing using a heterogeneous sensing vehicle selection method

The wide distribution of mobile vehicles installed with various sensing devices and wireless communication interfaces has made vehicular mobile crowd sensing possible in practice. However, owing to the heterogeneity of vehicles in terms of sensing interfaces and mobilities, collecting comprehensive tempo-spatial sensing data with only one sensing vehicle is impossible. Moreover, the sensing data collected may expire in the future; as a result, sensing vehicles may have to continuously collect sensing data to ensure the relevance of such data. Although including more sensing vehicles can improve the quality of collected sensing data, this step also requires additional cost. Thus, how to continuously collect comprehensive tempo-spatial sensing data with a limited number of heterogeneous sensing vehicles is a critical issue in vehicular mobile crowd sensing systems. In this work, a heterogeneous sensing vehicle selection (HVS) method for the collection of comprehensive tempo-spatial sensing data is proposed. On the basis of the spatial distribution and sensing interfaces of sensing vehicles and the tempo-spatial coverage of collected sensing data, a utility function is designed in HVS to estimate the sensing capacity of sensing vehicles. Then, according to the utilities of sensing vehicles and the restriction on the number of recruited sensing vehicles, sensing vehicle selection is modeled as a knapsack problem. Finally, a greedy optimal sensing vehicle selection algorithm is designed. Real trace-driven simulations show that the HVS algorithm can collect sensing data with a higher coverage ratio in a more uniform and continuous manner than existing mobile crowd sensing methods.     

移动群智感知中基于雾节点协作的感知用户身份隐私保护

在移动群智感知中,攻击者可利用感知用户间的社交关联信息以及感知用户身份信息与感知数据的关联性重构感知用户间的社交圈,进一步攻击用户社交团体。针对这一问题,提出一种基于雾节点协作的感知用户身份隐私保护方案。首先,创建任务分配中心（TC）和数据中心（DC）,并由位于终端边缘的2个雾节点承载,分别处理感知任务的合理分配问题和感知数据的聚合计算问题;然后,通过差分隐私加噪干扰防御攻击者获取感知用户间具体的社交关联权重;最后,感知用户使用不同的盲身份分别与TC和DC通信,防止攻击者同时获取感知用户的身份信息和感知数据。安全分析表明,所提方案可以确保感知用户在完成感知任务过程中的身份隐私信息安全。实验结果显示,所提方案可以有效保护感知用户间的社交关联信息,且具有较低的时延。     

Cyber-physical-social collaborative sensing: from single space to cross-space

The development of wireless sensor networking, social networking, and wearable sensing techniques has advanced the boundaries of research on understanding social dynamics. Collaborative sensing, which utilizes diversity sensing and computing abilities across different entities, has become a popular sensing and computing paradigm. In this paper, we first review the history of research in collaborative sensing, which mainly refers to single space collaborative sensing that consists of physical, cyber, and social collaborative sensing. Afterward, we extend this concept into cross-space collaborative sensing and propose a general reference framework to demonstrate the distinct mechanism of cross-space collaborative sensing. We also review early works in cross-space collaborative sensing, and study the detail mechanism based on one typical research work. Finally, although cross-space collaborative sensing is a promising research area, it is still in its infancy. Thus, we identify some key research challenges with potential technical details at the end of this paper.     

基于指数信任度函数的频谱感知改进算法

从多个用户合作感知的角度出发,针对目前的融合规则没有考虑感知结果的信任度,对现有的分布式感知算法进行改进,提出基于指数信任度的频谱感知算法;在认知无线电网络安全方面,将异常点感知引入到感知融合规则中,在指数信任度算法的基础上提出一种基于异常点的频谱感知算法,能抵御认知无线网络中出现故障的或者恶意认知用户;在提高感知速度和可靠性方面,结合指数信任度算法和异常点感知算法,将对感知信息的审核引入到频谱感知算法中,提出一种基于审核的频谱感知算法,该算法在提高感知速度的基础上能获得更好的感知性能。     

A context-aware sensing strategy with deep reinforcement learning for smart healthcare

Health sensing system (HSS), offering a variety of health services, has attracted considerable research attention in the area of smart healthcare. However, continuous sensing inevitably brings dramatic energy consumption of mobile sensing devices. On the other hand, the reduction of sensing time duration causes excessive delay in sensing a user state change and the missing of critical physiologic signal. Thus, the trade-off between energy consumption and delay constitutes a primary challenge in the design of HSS. In this paper, we propose an adaptive sensing strategy to intelligently determine the trigger time for sensing physiological parameters at a HSS. Furthermore, human context recognition (HCR) is adopted to design context-aware sensing strategy, where the health condition, sensing requirements, and dependence on physiological data are considered simultaneously. To devise the sensing strategy, we first generate a dynamic observation model. Next, we propose a sort retention double-DQN based sensing strategy. In comparison to traditional double-DQN, the proposed approach can effectively enhance learning stability and sample efficiency. With SRD-DQN, we can obtain the optimized solution for the schedule of the successive window according to the current state. We implement blood pressure and heart rate monitoring simulations to evaluate the performance of the proposed sensing strategy. Simulation results reveal that the sensing strategy can effectively restrain energy consumption and delay, and SRD-DQN converges faster than traditional DQN.     

MEMS-based monolithic three-axis fiber-optic acceleration sensor

In this paper, a MEMS-based monolithic three-axis fiber-optic acceleration sensor is proposed, consisting of three optical fiber collimators and a three-axis acceleration sensing chip. The novel acceleration sensor includes two horizontal sensing units and one vertical sensing unit integrated on a single silicon substrate. Three optical fiber collimators are on the same side of the three-axis sensing chip, thus reducing the package size and cost. In each sensing unit, the micromirror, suspended on a pair of torsion beams, has a torsional angle in response to acceleration in sensing direction. The torsion angle is monitored using fiber-optic detection technique. The sensing system operation principle has been analyzed theoretically, its mechanical performances were simulated using the FEM simulation, and its fabricated process flow was proposed. Using bulk micromachining technologies, the horizontal and the vertical sensing units were successfully fabricated. Finally the individual fabricated sensing units were packaged and tested.     

Recent progress in tactile sensing and sensors for robotic manipulation: can we turn tactile sensing into vision?1

This paper surveys recently published literature on tactile sensing in robotic manipulation to understand effective strategies for using tactile sensing and the issues involved in tactile sensing. It consists of a brief review of existing tactile sensors for robotic grippers and hands, review of modalities available from tactile sensing, review of the applications of tactile sensing in robotic manipulations, and discussion of the issues of tactile sensing and an approach to make tactile sensors more useful. We emphasize vision-based tactile sensing because of its potential to be a good tactile sensor for robots.     

基于高效协作感知算法的认知无线电研究*

针对协作频谱感知中感知开销过高问题,提出了一种联合考虑选择最佳的感知节点数以及感知的信道数来降低协作感知开销的方法。该算法分析了协作感知算法中感知节点数、感知的授权信道数与协作感知精度以及感知开销之间的关系。仿真结果表明,与其他算法相比,该算法能够有效地降低感知开销并提高系统的感知性能,验证了该算法的有效性。     

Placement of Accelerometers for High Sensing Resolution in Micromanipulation

High sensing resolution is required in sensing of surgical instrument motion in micromanipulation tasks. Accelerometers can be employed to sense physiological motion of the instrument during micromanipulation. Various configurations of accelerometer placement had been introduced in the past to sense motion of a rigid-body such as a surgical instrument. Placement (location and orientation) of accelerometers fixed in the instrument plays a significant role in achieving high sensing resolution. However, there is no literature or work on the effect of placement of accelerometers on sensing resolution. In this paper, an approach of placement of accelerometers within an available space to obtain highest possible sensing resolution in sensing of rigid-body motion in micromanipulation tasks is proposed. Superiority of the proposed placement approach is shown in sensing of a microsurgical instrument angular motion by comparing sensing resolutions achieved as a result of employing the configuration following the proposed approach and the existing configurations. Apart from achieving high sensing resolution, and design simplicity, the proposed placement approach also provides flexibility in placing accelerometers; hence it is especially useful in applications with limited available space to mount accelerometers.     

资源受限的认知无线电系统优化合作频谱感知算法

认知无线电的首要任务就是动态地感知频谱,合作频谱感知提高了频谱感知的可靠性.目前大多数频谱感知算法采用全部认知无线电台参与感知,并且假设每个认知无线电台的信噪比的测量值为一常数.然而,由于无线信道的特性和环境差异,每个认知无线电台的信噪比是有差异的,同时系统资源也是有限的.基于此,在采用能量检测硬判决的合作频谱感知算法基础上,提出一种优化的频谱感知算法.它在满足给定系统探测概率及虚警概率前提下,采用部分性能较好的认知无线电台参与频谱感知,并使系统感知开销最小.理论和仿真证明了其合理及有效性.     

一种基于流水线架构的协作式频谱感知方法

协作式频谱感知在提高认知无线电网络频谱感知性能的同时,也带来额外的通信开销.针对此问题,提出了一种基于流水线架构的协作式频谱感知方法,并给出了与之相配合的快速数据融合算法.该方法采用流水线架构来调度各参与感知节点的频谱测量操作和结果回传操作,使得用于感知结果回传的时间开销也可用于频谱测量,从而拓宽了频谱测量的时间窗口.快速数据融合算法通过多线程序贯似然比检测技术消除了在检测过程中由于频谱状态变化而产生的不良影响,进一步提高了协作感知效率.     

基于压缩感知的遥感成像稀疏重构性能分析

压缩感知是一种新型的信息论，打破了传统的Shannon-Nyquist采样定理，能够以少量数据完成信号采样。稀疏重构是压缩感知由理论到实际的关键环节，为了将压缩感知有效地应用于遥感成像领域，研究了稀疏重构对遥感成像过程的影响。针对稀疏重构理论模型，分析了重构误差的成因；同时，针对典型的凸优化类算法和贪婪类算法，利用峰值信噪比指标对遥感图像重构误差进行评价。在仿真实验中，定量考察遥感图像在不同压缩采样率、不同重构算法下的稀疏重构性能。结果表明，稀疏重构算法能够成功重构遥感图像，各算法在不同压缩采样率下均表现出了较好的重构质量，整体上能够满足遥感成像应用，验证了压缩感知稀疏重构方法在遥感成像中应用的可行性。     

基于遥感数据访问与集成的网格中间件

借助数据网格强大的数据管理功能,可以整合分散复杂的遥感数据,为遥感数据处理提供一致的存取环境。遥感数据访问与集成网格中间件的研究目的是为访问分散的、异构的遥感数据提供统一的网格服务接口,使孤立的遥感数据之间实现资源共享。该文利用OGSA-DAI设计,实现了遥感数据访问和集成网格服务,构建了一个高性能遥感数据共享系统,分析了系统的关键性技术及实际应用。     

对遥感在城市更新监测应用中的认知和思考

对城市更新改造的监测是目前较新的遥感应用领域。鉴于当前城市更新领域有关的遥感监测研究现状,对城市更新中遥感监测的概念、涉及方法以及与业务应用关系等方面进行了介绍,通过简要综述城市遥感监测的研究进展,分析适用于城市更新中的遥感数据类型,给出遥感在城市更新中的应用实例,尝试论证遥感在城市更新改造中的价值和作用,填补该领域遥感应用认知上的空缺,提出遥感在该领域工作可能的发展方向和研究思路。     

机器人触觉传感技术研发的历史现状与趋势

触觉是机器人实现与外部环境直接作用的必需媒介．相对其它机器人传感技术触觉传 感技术已明显落后．本文从总体上简要回顾触觉传感技术研发历程，分析指出其中的不足与 主要原因．在简述目前触觉传感技术研发的现状后，介绍分析机器人技术发展的新趋势及随 之而来的触觉传感技术发展趋势．对今后触觉传感技术的研发提出我们的见解．     

认知无线电网络中安全的协作频谱检测算法

在认知无线电网络中,当认知用户存在虚假感知信息SSDF时,协作频谱感知的性能会受到巨大影响。为了确保频谱感知的鲁棒性,提出了一种基于信誉度加权序贯频谱检测算法来识别恶意用户并减轻他们造成的影响。该算法通过使用认知用户的近期感知信息计算本地信誉度函数,再综合考虑其信誉值与感知过程中表现的稳定程度以消除恶意用户对主用户的传输效率带来的影响。仿真结果表明,在恶意攻击环境下,新算法优于现有典型协作频谱感知算法。     

群智感知激励机制研究综述

近年来,作为一种新的感知环境、收集数据和提供信息服务的模式,群智感知逐渐成为当前的研究热点之一.激励机制是群智感知研究中的一个重要问题,即通过设计合理的激励方式来激励足够多的参与者参与感知任务,并提供高质可靠的感知数据.对近年来在群智感知激励机制方面的研究工作进行综述,首先概述群智感知和群智感知激励机制;然后从关键技术入手,介绍4类主要激励方式和6类核心研究问题;最后,对现有工作进行对比分析,总结研究挑战,并指出未来发展方向,为相关研究人员提供有价值的参考.     

On developing theory of reservoir computing for sensing applications: the state weaving environment echo tracker (SWEET) algorithm

As a paradigm of computation, reservoir computing has gained an enormous momentum. In principle, any sufficiently complex dynamical system equipped with a readout layer can be used for any computation. This can be achieved by only adjusting the readout layer. Owning to this inherent flexibility of implementation, new applications of reservoir computing are being reported at a constant rate. However, relatively few studies focus on sensing, and in the ones that do, the reservoir is often exploited in a somewhat passive manner. The reservoir is used to post-process the signal from sensing elements that are placed separately, and the reservoir could be replaced by other information processing system without loss of functionality of the sensor (‘reservoir computing and sensing’). An entirely different novel class of sensing approaches is being suggested, to be referred to as ‘reservoir computing for sensing’, where the reservoir plays a central role. In the State Weaving Environment Echo Tracker (SWEET) sensing approach, the reservoir functions as the sensing element if the dynamical states of the reservoir and the environment one wishes to analyze are strongly interwoven. Some distinct characteristics of reservoir computing (in particular the separability and the echo state properties) are carefully exploited to achieve sensing functionality. The SWEET approach is formulated both as a generic device setup, and as an abstract mathematical algorithm. This algorithmic template could be used to develop a theory (or a class of theories) of ‘reservoir computing for sensing’, which could provide guidelines for engineering novel sensing applications. It could also provide ideas for a creative recycling of the existing sensing solutions. For example, the Horizon 2020 project RECORD-IT (Reservoir Computing with Real-time Data for future IT) exploits the SWEET sensing algorithm for ion detection. Accordingly, the terms SWEET sensing algorithm and the RECORD-IT sensing algorithm can be used interchangeably.     

Cognitions and Perspectives in Remote Sensing of Urban Renewal Monitoring

Currently urban renewal and transformation monitoring is a relatively new remote sensing application field. In view of current status and deficiencies in remote sensing of urban renewal, this paper introduces the basic concepts, methods and applications of remote sensing in this field. Through brief review of recent advances in remote sensing of urban monitoring, this paper interpreted the remote sensing data types suitable for urban renewal; examples of applications have been presented; for the purpose of illustrating the value of remote sensing in this field. Hopefully this paper can fill the knowledge gaps in the applications of remote sensing technology to urban renewal, and can inspire new thinking in this field. Possible future directions of remote sensing in this field are then pointed out.     

遥感技术在我国滑坡研究中的应用综述

中国滑坡遥感研究与应用已有30多年的发展历史,作为滑坡调查的主要手段在大型工程建设中的滑坡灾害调查及危险性评价中发挥了重要作用。从4方面阐述了遥感技术在我国滑坡研究中的应用：① 区域滑坡灾害遥感调查;② 大型单体滑坡遥感调查;③ 滑坡灾害遥感监测;④ 遥感应用于滑坡风险评估。随着遥感技术理论的逐步完善和遥感图像空间分辨率、时间分辨率与波谱分辨率的不断提高,遥感技术已成为滑坡灾害调查、动态监测与预警、灾情实时调查与损失评估等工作中不可缺少的重要手段之一。