Star sensors are an important means of autonomous navigation and access to space information for satellites.They have been widely deployed in the aerospace field.To satisfy the requirements for high resolution,timelin...Star sensors are an important means of autonomous navigation and access to space information for satellites.They have been widely deployed in the aerospace field.To satisfy the requirements for high resolution,timeliness,and confidentiality of star images,we propose an edge computing algorithm based on the star sensor cloud.Multiple sensors cooperate with each other to forma sensor cloud,which in turn extends the performance of a single sensor.The research on the data obtained by the star sensor has very important research and application values.First,a star point extraction model is proposed based on the fuzzy set model by analyzing the star image composition,which can reduce the amount of data computation.Then,a mappingmodel between content and space is constructed to achieve low-rank image representation and efficient computation.Finally,the data collected by the wireless sensor is delivered to the edge server,and a differentmethod is used to achieve privacy protection.Only a small amount of core data is stored in edge servers and local servers,and other data is transmitted to the cloud.Experiments show that the proposed algorithm can effectively reduce the cost of communication and storage,and has strong privacy.展开更多
The current IT cloud computing is playing a vital role in most of the areas such as Education, Research, Health care, etc. The cloud computing technology involving in sensor networks embedded system and IOT (Inte...The current IT cloud computing is playing a vital role in most of the areas such as Education, Research, Health care, etc. The cloud computing technology involving in sensor networks embedded system and IOT (Internet of Things). At present scenario, the sensors collected the information from the particular environment, where the sensors are fixed and transfer the collected information to cloud storage, here the challenge is the data transmission i.e. data that traverse from sensor to cloud environment are the big issue and maximum number of data loss is very high especially in dynamic routing environment. If data loss is identified in any routing path then automatically the information will transfer to alternate routing path. In this paper, we introduce a new algorithm for automatic routing path selection that can be integrated with cloud technology. This algorithm supports when data loss is found in the particular path of a network, then it selects an alternate route to transfer the data. The proposed model is comparatively more efficient than the prior methodologies. The implementation of the proposed work is done on NS3 simulator, and the performance metric is analyzed.展开更多
Mobile edge users(MEUs)collect data from sensor devices and report to cloud systems,which can facilitate numerous applications in sensor‑cloud systems(SCS).However,because there is no effective way to access the groun...Mobile edge users(MEUs)collect data from sensor devices and report to cloud systems,which can facilitate numerous applications in sensor‑cloud systems(SCS).However,because there is no effective way to access the ground truth to verify the quality of sensing devices’data or MEUs’reports,malicious sensing devices or MEUs may report false data and cause damage to the platform.It is critical for selecting sensing devices and MEUs to report truthful data.To tackle this challenge,a novel scheme that uses unmanned aerial vehicles(UAV)to detect the truth of sensing devices and MEUs(UAV‑DT)is proposed to construct a clean data collection platform for SCS.In the UAV‑DT scheme,the UAV delivers check codes to sensor devices and requires them to provide routes to the specified destination node.Then,the UAV flies along the path that enables maximal truth detection and collects the information of the sensing devices forwarding data packets to the cloud during this period.The information collected by the UAV will be checked in two aspects to verify the credibility of the sensor devices.The first is to check whether there is an abnormality in the received and sent data packets of the sensing devices and an evaluation of the degree of trust is given;the second is to compare the data packets submitted by the sensing devices to MEUs with the data packets submitted by the MEUs to the platform to verify the credibility of MEUs.Then,based on the verified trust value,an incentive mechanism is proposed to select credible MEUs for data collection,so as to create a clean data collection sensor‑cloud network.The simulation results show that the proposed UAV‑DT scheme can identify the trust of sensing devices and MEUs well.As a result,the proportion of clean data collected is greatly improved.展开更多
This paper presents a prototype of an Integrated Cloud-Based Wireless Sensor Network (WSN) developed to monitor pH, conductivity and dissolved oxygen parameters from wastewater discharged into water sources. To provid...This paper presents a prototype of an Integrated Cloud-Based Wireless Sensor Network (WSN) developed to monitor pH, conductivity and dissolved oxygen parameters from wastewater discharged into water sources. To provide realtime online monitoring and Internet of Things (IoT) capability, the system collects and uploads sensor data to ThingSpeak cloud via GPRS internet connectivity with the help of AT commands in combination with HTTP GET method. Moreover, the system sends message alert to the responsible organ through GSM/GPRS network and an SMS gateway service implemented by Telerivet mobile messaging platform. In this prototype, Telerivet messaging platform gives surrounding communities a means of reporting observed or identified water pollution events via SMS notifications.展开更多
针对传统消防监控系统存在开发成本高、误警率高、实时监控不便的问题,提出一种基于物联网云平台的智慧消防远程监控系统。采用STM32单片机作为中枢控制芯片,经多传感器采集温度、湿度、烟雾、火焰等环境数据,通过窄带物联网(NB-IoT,Nar...针对传统消防监控系统存在开发成本高、误警率高、实时监控不便的问题,提出一种基于物联网云平台的智慧消防远程监控系统。采用STM32单片机作为中枢控制芯片,经多传感器采集温度、湿度、烟雾、火焰等环境数据,通过窄带物联网(NB-IoT,Narrow Band Internet of Things)上传至OneNET云平台。经数据分析后以可视化方式呈现,对异常数据触发报警实时响应。通过手机APP实现数据实时监测及一键处置。经测试,监控系统报警准确率高于97.2%,数据延迟低于50 ms,表明该系统能够实现消防火警的无线远程监控,并做出快速反应,满足中小微企业和普通家庭用户的消防监控需要。展开更多
在自动驾驶感知系统中视觉传感器与激光雷达是关键的信息来源,但在目前的3D目标检测任务中大部分纯点云的网络检测能力都优于图像和激光点云融合的网络,现有的研究将其原因总结为图像与雷达信息的视角错位以及异构特征难以匹配,单阶段...在自动驾驶感知系统中视觉传感器与激光雷达是关键的信息来源,但在目前的3D目标检测任务中大部分纯点云的网络检测能力都优于图像和激光点云融合的网络,现有的研究将其原因总结为图像与雷达信息的视角错位以及异构特征难以匹配,单阶段融合算法难以充分融合二者的特征.为此,本文提出一种新的多层多模态融合的3D目标检测方法:首先,前融合阶段通过在2D检测框形成的锥视区内对点云进行局部顺序的色彩信息(Red Green Blue,RGB)涂抹编码;然后将编码后点云输入融合了自注意力机制上下文感知的通道扩充PointPillars检测网络;后融合阶段将2D候选框与3D候选框在非极大抑制之前编码为两组稀疏张量,利用相机激光雷达对象候选融合网络得出最终的3D目标检测结果.在KITTI数据集上进行的实验表明,本融合检测方法相较于纯点云网络的基线上有了显著的性能提升,平均mAP提高了6.24%.展开更多
在图优化框架的基础上,设计多传感器融合方案和有效的优化方法,提出一套具有鲁棒性的定位与建图(Simultaneous Localization and Mapping,SLAM)方案,能够有效应对室内外复杂环境。进一步发展激光-视觉后端建图融合方法,构建具备全新地...在图优化框架的基础上,设计多传感器融合方案和有效的优化方法,提出一套具有鲁棒性的定位与建图(Simultaneous Localization and Mapping,SLAM)方案,能够有效应对室内外复杂环境。进一步发展激光-视觉后端建图融合方法,构建具备全新地图表达形式的点云网格化地图。同时使用低成本传感器,设计实现基于多传感器融合的高性能低成本背包扫描系统,整体完成在未知环境中的自我定位和稠密建图,且在低性能CPU设备上将长时间运动带来的每100 m的轨迹误差平均降低至厘米级。提出的基于多传感器融合方案,在精度、算力消耗上能够匹配现有主流方案,对获取各种环境条件下的系统准确定位结果和丰富的空间信息具有重要意义。展开更多
基金supported by Science and Technology Rising Star of Shaanxi Youth (No.2021KJXX-61)The Open Project Program of the State Key Lab of CAD&CG,Zhejiang University (No.A2206).
文摘Star sensors are an important means of autonomous navigation and access to space information for satellites.They have been widely deployed in the aerospace field.To satisfy the requirements for high resolution,timeliness,and confidentiality of star images,we propose an edge computing algorithm based on the star sensor cloud.Multiple sensors cooperate with each other to forma sensor cloud,which in turn extends the performance of a single sensor.The research on the data obtained by the star sensor has very important research and application values.First,a star point extraction model is proposed based on the fuzzy set model by analyzing the star image composition,which can reduce the amount of data computation.Then,a mappingmodel between content and space is constructed to achieve low-rank image representation and efficient computation.Finally,the data collected by the wireless sensor is delivered to the edge server,and a differentmethod is used to achieve privacy protection.Only a small amount of core data is stored in edge servers and local servers,and other data is transmitted to the cloud.Experiments show that the proposed algorithm can effectively reduce the cost of communication and storage,and has strong privacy.
文摘The current IT cloud computing is playing a vital role in most of the areas such as Education, Research, Health care, etc. The cloud computing technology involving in sensor networks embedded system and IOT (Internet of Things). At present scenario, the sensors collected the information from the particular environment, where the sensors are fixed and transfer the collected information to cloud storage, here the challenge is the data transmission i.e. data that traverse from sensor to cloud environment are the big issue and maximum number of data loss is very high especially in dynamic routing environment. If data loss is identified in any routing path then automatically the information will transfer to alternate routing path. In this paper, we introduce a new algorithm for automatic routing path selection that can be integrated with cloud technology. This algorithm supports when data loss is found in the particular path of a network, then it selects an alternate route to transfer the data. The proposed model is comparatively more efficient than the prior methodologies. The implementation of the proposed work is done on NS3 simulator, and the performance metric is analyzed.
基金National Natural Science Foundation of China under Grant No.62032020Hunan Science and Technology Plan⁃ning Project under Grant No.2019RS3019the National Key Research and Development Program of China under Grant 2018YFB1003702.
文摘Mobile edge users(MEUs)collect data from sensor devices and report to cloud systems,which can facilitate numerous applications in sensor‑cloud systems(SCS).However,because there is no effective way to access the ground truth to verify the quality of sensing devices’data or MEUs’reports,malicious sensing devices or MEUs may report false data and cause damage to the platform.It is critical for selecting sensing devices and MEUs to report truthful data.To tackle this challenge,a novel scheme that uses unmanned aerial vehicles(UAV)to detect the truth of sensing devices and MEUs(UAV‑DT)is proposed to construct a clean data collection platform for SCS.In the UAV‑DT scheme,the UAV delivers check codes to sensor devices and requires them to provide routes to the specified destination node.Then,the UAV flies along the path that enables maximal truth detection and collects the information of the sensing devices forwarding data packets to the cloud during this period.The information collected by the UAV will be checked in two aspects to verify the credibility of the sensor devices.The first is to check whether there is an abnormality in the received and sent data packets of the sensing devices and an evaluation of the degree of trust is given;the second is to compare the data packets submitted by the sensing devices to MEUs with the data packets submitted by the MEUs to the platform to verify the credibility of MEUs.Then,based on the verified trust value,an incentive mechanism is proposed to select credible MEUs for data collection,so as to create a clean data collection sensor‑cloud network.The simulation results show that the proposed UAV‑DT scheme can identify the trust of sensing devices and MEUs well.As a result,the proportion of clean data collected is greatly improved.
文摘This paper presents a prototype of an Integrated Cloud-Based Wireless Sensor Network (WSN) developed to monitor pH, conductivity and dissolved oxygen parameters from wastewater discharged into water sources. To provide realtime online monitoring and Internet of Things (IoT) capability, the system collects and uploads sensor data to ThingSpeak cloud via GPRS internet connectivity with the help of AT commands in combination with HTTP GET method. Moreover, the system sends message alert to the responsible organ through GSM/GPRS network and an SMS gateway service implemented by Telerivet mobile messaging platform. In this prototype, Telerivet messaging platform gives surrounding communities a means of reporting observed or identified water pollution events via SMS notifications.
文摘针对传统消防监控系统存在开发成本高、误警率高、实时监控不便的问题,提出一种基于物联网云平台的智慧消防远程监控系统。采用STM32单片机作为中枢控制芯片,经多传感器采集温度、湿度、烟雾、火焰等环境数据,通过窄带物联网(NB-IoT,Narrow Band Internet of Things)上传至OneNET云平台。经数据分析后以可视化方式呈现,对异常数据触发报警实时响应。通过手机APP实现数据实时监测及一键处置。经测试,监控系统报警准确率高于97.2%,数据延迟低于50 ms,表明该系统能够实现消防火警的无线远程监控,并做出快速反应,满足中小微企业和普通家庭用户的消防监控需要。
文摘在自动驾驶感知系统中视觉传感器与激光雷达是关键的信息来源,但在目前的3D目标检测任务中大部分纯点云的网络检测能力都优于图像和激光点云融合的网络,现有的研究将其原因总结为图像与雷达信息的视角错位以及异构特征难以匹配,单阶段融合算法难以充分融合二者的特征.为此,本文提出一种新的多层多模态融合的3D目标检测方法:首先,前融合阶段通过在2D检测框形成的锥视区内对点云进行局部顺序的色彩信息(Red Green Blue,RGB)涂抹编码;然后将编码后点云输入融合了自注意力机制上下文感知的通道扩充PointPillars检测网络;后融合阶段将2D候选框与3D候选框在非极大抑制之前编码为两组稀疏张量,利用相机激光雷达对象候选融合网络得出最终的3D目标检测结果.在KITTI数据集上进行的实验表明,本融合检测方法相较于纯点云网络的基线上有了显著的性能提升,平均mAP提高了6.24%.
文摘在图优化框架的基础上,设计多传感器融合方案和有效的优化方法,提出一套具有鲁棒性的定位与建图(Simultaneous Localization and Mapping,SLAM)方案,能够有效应对室内外复杂环境。进一步发展激光-视觉后端建图融合方法,构建具备全新地图表达形式的点云网格化地图。同时使用低成本传感器,设计实现基于多传感器融合的高性能低成本背包扫描系统,整体完成在未知环境中的自我定位和稠密建图,且在低性能CPU设备上将长时间运动带来的每100 m的轨迹误差平均降低至厘米级。提出的基于多传感器融合方案,在精度、算力消耗上能够匹配现有主流方案,对获取各种环境条件下的系统准确定位结果和丰富的空间信息具有重要意义。
