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| 1 | From automated home to sustainable,healthy and manufacturing home:a new story enabled by the Internet-of-Things and Industry 4.0显示文摘This paper seeks to expand on the role for future homes in relation to automation,sustainability,healthcare and manufacturing.The world is changing and the home along with it.Services provided in the home will no longer act separately but will be all the more integrated into each other as new connections between services increase the value for residents in the home.This paper presents some of the possible integrated services and a close-up of the networked manufacturing service.A conceptual communication infrastructure for the service is finally provided. | Jakob Branger Zhibo Pang | 2015 | Journal of Management Analytics2015，2，4： | 2 |
| 2 | An emerging technology-wearable wireless sensor networks with applications in human health condition monitoring显示文摘Monitoring health conditions over a human body to detect anomalies is a multidisciplinary task,which involves anatomy,artificial intelligence,and sensing and computing networks.A wearable wireless sensor network(WWSN)turns into an emerging technology,which is capable of acquiring dynamic data related to a human body’s physiological conditions.The collected data can be applied to detect anomalies in a patient,so that he or she can receive an early alert about the adverse trend of the health condition,and doctors can take preventive actions accordingly.In this paper,a new WWSN for anomaly detections of health conditions has been proposed,system architecture and network has been discussed,the detecting model has been established and a set of algorithms have been developed to support the operation of the WWSN.The novelty of the detected model lies in its relevance to chronobiology.Anomalies of health conditions are contextual and assessed not only based on the time and spatial correlation of the collected data,but also based on mutual relations of the data streams from different sources of sensors.A new algorithm is proposed to identify anomalies using the following procedure:(1)collected raw data is preprocessed and transferred into a set of directed graphs to represent the correlations of data streams from different sensors;(2)the directed graphs are further analyzed to identify dissimilarities and frequency patterns;(3)health conditions are quantified by a coefficient number,which depends on the identified dissimilarities and patterns.The effectiveness and reliability of the proposed WWSN has been validated by experiments in detecting health anomalies including tachycardia,arrhythmia and myocardial infarction. | Hairong Yan LiDa Xu Zhuming Bi Zhibo Pang Jie Zhang Yong Chen | 2015 | Journal of Management Analytics2015，2，2： | 2 |
| 3 | Towards Task-Free Privacy-Preserving Data Collection显示文摘With the rapid developments of Internet of Things(IoT)and proliferation of embedded devices,large volume of personal data are collected,which however,might carry massive private information about attributes that users do not want to share.Many privacy-preserving methods have been proposed to prevent privacy leakage by perturbing raw data or extracting task-oriented features at local devices.Unfortunately,they would suffer from significant privacy leakage and accuracy drop when applied to other tasks as they are designed and optimized for predefined tasks.In this paper,we propose a novel task-free privacy-preserving data collection method via adversarial representation learning,called TF-ARL,to protect private attributes specified by users while maintaining data utility for unknown downstream tasks.To this end,we first propose a privacy adversarial learning mechanism(PAL)to protect private attributes by optimizing the feature extractor to maximize the adversary’s prediction uncertainty on private attributes,and then design a conditional decoding mechanism(ConDec)to maintain data utility for downstream tasks by minimizing the conditional reconstruction error from the sanitized features.With the joint learning of PAL and ConDec,we can learn a privacy-aware feature extractor where the sanitized features maintain the discriminative information except privacy.Extensive experimental results on real-world datasets demonstrate the effectiveness of TF-ARL. | Zhibo Wang Wei Yuan Xiaoyi Pang Jingxin Li Huajie Shao | 2022 | China Communications2022，19，7： | 0 |
| 4 | High-precision Calibration of Camera and IMU on Manipulator for Bio-inspired Robotic System显示文摘Inspired by box jellyfish that has distributed and complementary perceptive system,we seek to equip manipulator with a camera and an Inertial Measurement Unit(IMU)to perceive ego motion and surrounding unstructured environment.Before robot perception,a reliable and high-precision calibration between camera,IMU and manipulator is a critical prerequisite.This paper introduces a novel calibration system.First,we seek to correlate the spatial relationship between the sensing units and manipulator in a joint framework.Second,the manipulator moving trajectory is elaborately designed in a spiral pattern that enables full excitations on yaw-pitch-roll rotations and x-y-z translations in a repeatable and consistent manner.The calibration has been evaluated on our collected visual inertial-manipulator dataset.The systematic comparisons and analysis indicate the consistency,precision and effectiveness of our proposed calibration method. | Yinlong Zhang Wei Liang Sichao Zhang Xudong Yuan Xiaofang Xia Jindong Tan Zhibo Pang | 2022 | Journal of Bionic Engineering2022，19，2： | 0 |
| 5 | Monocular Visual-Inertial and Robotic-Arm Calibration in a Unifying Framework显示文摘Reliable and accurate calibration for camera,inertial measurement unit(IMU)and robot is a critical prerequisite for visual-inertial based robot pose estimation and surrounding environment perception.However,traditional calibrations suffer inaccuracy and inconsistency.To address these problems,this paper proposes a monocular visual-inertial and robotic-arm calibration in a unifying framework.In our method,the spatial relationship is geometrically correlated between the sensing units and robotic arm.The decoupled estimations on rotation and translation could reduce the coupled errors during the optimization.Additionally,the robotic calibration moving trajectory has been designed in a spiral pattern that enables full excitations on 6 DOF motions repeatably and consistently.The calibration has been evaluated on our developed platform.In the experiments,the calibration achieves the accuracy with rotation and translation RMSEs less than 0.7°and 0.01 m,respectively.The comparisons with state-of-the-art results prove our calibration consistency,accuracy and effectiveness. | Yinlong Zhang Wei Liang Mingze Yuan Hongsheng He Jindong Tan Zhibo Pang | 2022 | IEEE/CAA Journal of Automatica Sinica2022，9，1： | 0 |
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