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The measuring ZMP of self-balancing exoskeleton robot is calibrated by using the neural network

The measuring ZMP of self-balancing exoskeleton robot is cal...

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2021 IEEE International conference on Real-Time Computing and Robotics, RCAR 2021

作者： Xu, Yang Xiao, Yang Ma, Yue Zheng, Liangsheng He, Yong Chongqing University of Posts and Telecommunications School of Automation Chongqing400065 China Shenzhen Institute of Advanced Technology Chinese Academy of Sciences Guangdong Provincial Key Laboratory of Robotics and Intelligent System Shenzhen518055 China CAS Key Laboratory of Human-Machine Intelligence-Synergy Systems Shenzhen Institute of Advanced Technology Chinese Academy of Sciences Shenzhen518055 China University of Chinese Academy of Sciences Beijing100049 China

ISBN: (纸本)9781665436786

The exoskeleton robot is an auxiliary device to help the disabled people walk, and the self-balancing exoskeleton robot is one which is to keep balance without the assistance of external crutches. In order to keep the balance of the self-balancing exoskeleton robot, it is necessary to get the position of the Zero Moment Point by measuring the pressure of the footplate, and make the position of ZMP in range of supporting area. In this experiment, the footplate is used with the double-deck structure, this structure is compared with the single-deck structure, the double-dack structure will not lose the information of the collected ZMP without direct touch with the sensor, and it is lighter than another structure with dozens of sensors. But there is an inevitable structural coupling in the double-deck structure, which makes the ZMP have a large measurement error. In order to solve this problem, a novel idea is proposed, with the help of the powerful processing and learning capabilities of the neural network, four kinds of neural networks are used to calibrate measured position of ZMP so that reducing error of the measured ZMP. By comparing position of the actual ZMP before and after the calibration with the ideal position of ZMP and computing the errors to judge the effect of the calibration. Through experimental comparison, it is concluded that the different neural networks eliminate error of the measured ZMP in different extent. When the GRNN neural network is used to calibrate position of ZMP, the effect is the most ideal. © 2021 IEEE.

关键词： Errors

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Development of Smart Flood Monitoring and Early Warning System using Weather Forecasting Data and Wireless sensor networks-A Review

Development of Smart Flood Monitoring and Early Warning Syst...

引用

intelligent Communication Technologies and Virtual Mobile networks (ICICV), International conference on

作者： M.J Subashini R. Sudarmani S Gobika R Varshini School of Engineering Avinashilingam Institute for Home Science and Higher Education for Women Coimbatore India

ISBN: (数字)9781665419604

ISBN: (纸本)9781665429986

Flooding could be a normal marvel and it is an overflow of water that submerges the land area, which is ordinarily dry in nature bv creating a negative effect on the society due to its tall misfortune on human lives. Due to the negative imnact on the residents and coastal areas, flood prediction and alerting nlavs an important role in the current generation. Recently, a severe flooding took place in the Indian state Kerala during the last monsoon season with a heavy unusual rain, which has led to a severe loss and not happened previously during the century. Within the fortnight, nearly the died people strength is 373, where almost 83% of the dams in the state are opened out to avoid further loss of lives. Thus, the chances of flood occurring should be periodically monitored. Hence, an early warning system is required to save the lives of the people in the endangered areas by using Wireless sensor Network fWSN). In this paper, a system of Wireless sensor networks has been developed and it comprises of sensor hubs that are conveyed at the particular surge and helpless areas for performing a real-time surge checking and discovery. Wireless sensor networks (WSN) can be deployed for many other real time projects, as the data could be collected rapidly and efficiently. The sensor node consists of certain sensors such as temperature sensor, ultrasonic and rain sensor with limited processing and communication capabilities. The detected information from the sensors is transmitted to the microprocessor for further preparation. The processed information is transmitted to cloud by using a LoRA (Long Range) module. A mobile application has been developed to provide an early warning to the people in the affected areas, where mobile is very handy and conveys information as soon as possible. Hence, the latest technology like sensor network will be used to determine the accurate level of flooding and also the mobile phone connected with this technology will send the forecasting info

关键词： Wireless communication Temperature sensors Wireless sensor networks Rain Real-time systems Floods Surges

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The Scalable Group Testing of Invalid Signatures based on Latin Square in Wireless sensors networks

The Scalable Group Testing of Invalid Signatures based on La...

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6th International conference on intelligent Computing and Signal processing (ICSP)

作者： Hong Wang Xiangyang Liu Yunhong Xie Han Zeng Information and Communication College National University of Defense Technology NUDT Xi’an China

Digital signature is more appropriate for message security in Wireless sensors networks (WSNs), which is energy-limited, than costly encryption. However, it meets with difficulty of verification when a large amount of message-signature pairs swarm into the central node in WSNs. In this paper, a scalable group testing algorithm based on Latin square (SGTLS) is proposed, which focus on both batch verification of signatures and invalid signature identification. To address the problem of long time-delay during individual verification, we adapt aggregate signature for batch verification so as to judge whether there are any invalid signatures among the collection of signatures once. In particular, when batch verification fails, an invalid signature identification algorithm is presented based on scalable OR-checking matrix of Latin square, which can adjust the number of group testing by itself with the variation of invalid signatures. Comprehensive analyses show that SGTLS has more advantages, such as scalability, suitability for parallel computing and flexible design (Latin square is popular), than other algorithm.

关键词： Wireless communication Wireless sensor networks Scalability Signal processing algorithms Signal processing Parallel processing Encryption

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Speeding Up IPv4 Connections via IPv6 Infrastructure

Speeding Up IPv4 Connections via IPv6 Infrastructure

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International conference on Mobile Ad-hoc and sensor networks, MSN

作者： Ruiyu Fang Guoliang Han Xin Wang Congxiao Bao Xing Li Yang Chen Shanghai Key Lab of Intelligent Information Processing School of Computer Science Fudan University China INDIRECTIONNET China Tsinghua University China

Although IPv6 has been proposed to solve the IP address exhaustion problem for decades, the transition process from IPv4 to IPv6 is rather slow due to the possible loss of users and increased costs for ISPs compared with the potential profits. In order to accelerate this process and make full use of the IPv6 network, in this paper, we propose a user-transparent solution named NetBoost by transferring IPv4 traffic through the IPv6 core network. We also implement a simulator called NetBoostSim to further verify the usefulness and prospective performance gain of NetBoost in different network environments. By deploying our system upon both real and simulated network environments, we showcase that better performance for IPv4 end-to-end connections can be acquired by utilizing the light-loaded IPv6 network to transfer traffic from heavy-loaded IPv4 core network, using stateless IPv4/IPv6 translation techniques. In this way, our system can serve as an incentive for ISPs to upgrade to pure IPv6 networks gradually without concerns for the user churn.

关键词： Limiting Costs Performance gain Throughput sensors IP networks

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CAP-Net: A Deep Learning-Based Angle Prediction Approach for ISAC-Enabled RIS-Assisted V2I Communications

CAP-Net: A Deep Learning-Based Angle Prediction Approach for...

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International conference on Communication Technology (ICCT)

作者： Ruixiang Wang Fanghao Xia Jingxuan Huang Xinyi Wang Zesong Fei School of Information and Electronics Beijing Institute of Technology (BIT) Beijing China Yangtze River Delta Graduate School of Beijing Institute of Technology (Jiaxing) Jiaxing China

In the vehicle-to-infrastructure (V2I) scenarios, it is challenging to acquire accurate channel state information (CSI) due to the high mobility of the communication channels, which leads to considerable pilot overhead. To tackle this issue, we employ both integrated sensing and communication (ISAC) technique and reconfigurable intelligent surface (RIS) technique to reduce the pilot overhead significantly while maximizing the achievable rate. In particular, we consider a RIS-assisted ISAC system serving the vehicle and design a transmission protocol based on communication-sensing-computing integration architecture for the proposed system, where the ISAC base station (BS) and the dedicated sensors deployed at the RIS receive the reflected echo signals from the user equipment (UE) via the BS-UE-BS link and the BS-UE-sensors link, respectively. Then the CSI of the UE can be acquired from the received signals. Furthermore, to provide both high-quality and low-latency communication services, we propose a covariance-based angle prediction neural network (CAP-Net) to predict the angle parameters facilitating the joint transmit and reflective beamforming design for the next time slot. Simulation results show that the proposed RIS-assisted ISAC system with the CAP-Net achieves better communication performance compared with other baseline schemes and can approach the upper bound in terms of achievable rate.

关键词： Upper bound Protocols Array signal processing Vehicle-to-infrastructure Simulation Neural networks sensor systems

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Matching sensor Ontologies with Neural Network

Matching Sensor Ontologies with Neural Network

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IEEE International conference on Trust, Security and Privacy in Computing and Communications (TrustCom)

作者： Xingsi Xue Haolin Wang Yunmeng Zhao Yikun Huang Hai Zhu Intelligent Information Processing Research Center Fujian University of Technology Fuzhou China School of Computer Science and Mathematics Fujian University of Technology Fuzhou China Concord University College Fujian Normal University Fuzhou China School of Network Engineering Zhoukou Normal University Zhoukou China

ISBN: (纸本)9781665416597

With the widespread adoption of sensors, many research efforts in recent years have focused on the wireless sensor networks. Since a wireless sensor network consists of a large number of sensors, its trusted communication become a hot research topic. sensor ontology matching technology is able to solve the sensor information heterogeneity problem, which ensures the communication quality among different wireless sensor networks. In the matching process, different classes of similarity measures have different contributions in matching sensor ontologies. How to determine the optimal weights to aggregate multiple similarity measures to obtain high quality ontology alignment becomes a challenge in sensor ontology matching domain. To face this challenge, this work proposes a neural network-based sensor ontology matching technique. In particular, a single layer perceptron is used to aggregate multiple similarity measures and the neural model is trained with different training examples to obtain higher ontology matching accuracy. The experimental results show that the proposed approach is able to determine higher quality alignment results compared to other matchers under different domain knowledge such as bibliographic and real sensor ontologies.

关键词： Wireless communication Weight measurement Training Wireless sensor networks Atmospheric measurements Aggregates Ontologies

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Smart Window Design for the Prevention of Rainstorm, Sun Exposure and Haze Based on IOT Technology

Smart Window Design for the Prevention of Rainstorm, Sun Exp...

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Computer, Internet of Things and Control Engineering (CITCE), International conference on

作者： Si-Han Yang Jun Zhou Shanghai No. 2 Junior Middle School Shanghai China Shanghai Jing’an District Youth Activity Center Shanghai China

ISBN: (纸本)9781665421850

In order to promote the intelligentization of the home environment, a smart window control system based on the IOT (Internet of Things) is designed, and its software and hardware solutions are deeply analyzed. The smart window uses the ARM microprocessor as the control center and constructs a sensor local area network through ZigBee wireless communication electronic technology. The CC2530 chip is set as the coordinator in the wireless network communication module, and the remaining CC2530 chips control the window nodes. The window node integrates temperature and humidity sensors, rain and snow sensors, smoke sensors, and motor control modules. Various sensors collect information and send it to the corresponding CC2530 chip for analysis and processing and control the motor module to realize the intelligent closing of the window. The test results show that the system has realized functions such as intelligent monitoring, intelligent ventilation, rain and snow protection, and anti-theft, and has good practicability and market prospects.

关键词： Temperature sensors Rain Snow Wireless networks Zigbee Process control Humidity

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1.3 Working at the Intersection of Machine Learning, Signal processing, sensors, and Circuits

1.3 Working at the Intersection of Machine Learning, Signal ...

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IEEE International conference on Solid-State Circuits (ISSCC)

作者： Dina Katabi Massachusetts Institute of Technology Cambridge MA

ISBN: (数字)9781728195490

ISBN: (纸本)9781728195506

Wireless technologies have propelled major advances in various industries including telecommunications, entertainment, and smart environments. Today, radios are embedded in cellphones, wearable devices, sensors, and control systems. Yet, in all of these diverse domains, radios are used for communications. Even when embedded in a sensor, the radio signals are used for communicating the sensed data, rather than performing the sensing function. We argue that future innovations should leverage radio signals for sensing. Radio signals are fascinating creatures: they travel in space, traverse walls and occlusions, and reflect off people and objects. The reflected signals are modulated by people's movements, actions, respiration, and heart beats. By analyzing such radio reflections, we can learn much information about people and their physiological signals, and leverage such knowledge to enable new capabilities and novel applications.

关键词： Wireless communication Wireless sensor networks Technological innovation Wearable computers Telecommunications intelligent sensors Wearable sensors

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Single Satellite Optical Imagery Dehazing using SAR Image Prior Based on conditional Generative Adversarial networks

Single Satellite Optical Imagery Dehazing using SAR Image Pr...

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IEEE/CVF Winter conference on Applications of Computer Vision (WACV)

作者： Huang, Binghui Li, Zhi Yang, Chao Sun, Fuchun Song, Yixu Tsinghua Univ Beijing Natl Res Ctr Informat Sci & Technol BNRis Dept Comp Sci & Technol State Key Lab Intelligent Technol & Syst Beijing Peoples R China Shanghai Univ Engn Sci Shanghai Peoples R China

ISBN: (纸本)9781728165530

Satellite image dehazing aims at precisely retrieving the real situations of the obscured parts from the hazy remote sensing (RS) images, which is a challenging task since the hazy regions contain both ground features and haze components. Many approaches of removing haze focus on processing multi-spectral or RGB images, whereas few of them utilize multi-sensor data. The multi-sensor data fusion is significant to provide auxiliary information since RGB images are sensitive to atmospheric conditions. In this paper, a dataset called SateHaze1k is established and composed of 1200 pairs clear Synthetic Aperture Radar (SAR), hazy RGB, and corresponding ground truth images, which are divided into three degrees of the haze, i.e. thin, moderate, and thick fog. Moreover, we propose a novel fusion dehazing method to directly restore the haze-free RS images by using an end-to-end conditional generative adversarial network(cGAN). The proposed network combines the information of both RGB and SAR images to eliminate the image blurring. Besides, the dilated residual blocks of the generator can also sufficiently improve the dehazing effects. Our experiments demonstrate that the proposed method, which fuses the information of different sensors applied to the cloudy conditions, can achieve more precise results than other baseline models.

关键词： Generative adversarial networks

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Joint Time Allocation and Beamforming Design for IRS-Aided Coexistent Cellular and sensor networks

Joint Time Allocation and Beamforming Design for IRS-Aided C...

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2021 IEEE Global Communications conference (GLOBECOM)

作者： Yanze Zhu Yang Liu Jun Zhao Ming Li Qingqing Wu School of Information and Communication Engineering Dalian University of Technology School of Computer Science and Engineering Nanyang Technological University State Key Lab. of Internet of Things for Smart City Univ. of Macau

ISBN: (纸本)9781728181059

Internet of things (IoT) technology is an essential enabler to realize ubiquitous connections and pervasive intelli-gence for the future wireless communication system. The energy self-sustainability based on the wireless power transfer technique and the coexistence with heterogeneous networks will become two predominant attributes of IoT networks. In this paper we consider the system design in a context of coexistence of a wireless powered sensor network and a cellular system, both of which share common spectrum bandwidth and are assisted by intelligent reflecting surface (IRS). Specifically, the wireless sensors exploit the harvested energy from the cellular base station (BS) to transfer information to a data sink. We aim to design a cooperation scheme via jointly optimizing the time allocation of channel use, collaborative beamforming across networks and IRS phase-shifting control to improve the sensing network's throughput while guaranteeing the cellular users' quality of service. This design problem leads to a highly nonconvex and difficult mathematical optimization problem. Via utilizing the penalty-duality-decomposition (PDD) and successive convex approximation (SCA) methods, we have managed to develop an alternative optimization solution. Nu-merical results verify the effectiveness of our algorithm and demonstrate the benefits that come from the cooperative network design.

关键词： Wireless communication Wireless sensor networks Array signal processing System performance Wireless power transfer Throughput sensors

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