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	Application of Social Sensors in Natural Disasters Emergency Management: A Review 期刊论文 OAI收割 IEEE TRANSACTIONS ON COMPUTATIONAL SOCIAL SYSTEMS, 2023, 卷号: 10, 期号: 6, 页码: 3143-3158 作者: Shi, Kaize; Peng, Xueping; Lu, Hao; Zhu, Yifan; Niu, Zhendong \| 收藏 \| 浏览/下载：9/0 \| 提交时间：2024/07/03 Sensors Emergency services Sentiment analysis Social networking (online) Sensor phenomena and characterization Intelligent sensors Earthquakes Decision support system emergency management parallel system social network analysis social sensor sudden natural disaster
	Pedestrian Dead Reckoning Based on Walking Pattern Recognition and Online Magnetic Fingerprint Trajectory Calibration 期刊论文 OAI收割 IEEE INTERNET OF THINGS JOURNAL, 2021, 卷号: 8, 期号: 3, 页码: 2011-2026 作者: Wang, Qu; Luo, Haiyong; Xiong, Hao; Men, Aidong; Zhao, Fang \| 收藏 \| 浏览/下载：37/0 \| 提交时间：2021/12/01 Legged locomotion Trajectory Estimation Fingerprint recognition Dead reckoning Sensors Heading estimation indoor positioning Internet of Things (IoT) online calibration pedestrian dead reckoning (PDR) walking pattern recognition
	A communication-free leader-follower formation method for UGVs via sensors fusion 会议论文 OAI收割 2018-8-11 作者: Lin LL(林玲龙); Wang ZL(王智灵); Liang HW(梁华为); Xu FY(徐凤煜); Huang JJ(黄俊杰) \| 收藏 \| 浏览/下载：26/0 \| 提交时间：2021/12/08 communication-free leader-follower UGVs sensors fusion online estimator
	Improve the performance of full-scale continuous treatment of municipal wastewater by combining a numerical model and online sensors 期刊论文 OAI收割 WATER SCIENCE AND TECHNOLOGY, 2018, 卷号: 78, 期号: 8, 页码: 1658-1667 作者: Ma, Jinfeng; Chen, Qiuwen; Wang, Qibin; Yan, Hanlu; Chen, Cheng \| 收藏 \| 浏览/下载：208/0 \| 提交时间：2019/06/21 nutrient removal efficiency online sensors operation optimization process model wastewater treatment plant (WWTP)
	An intelligent video surveillance system (EI CONFERENCE) 会议论文 OAI收割 2010 International Conference on E-Product E-Service and E-Entertainment, ICEEE2010, November 7, 2010 - November 9, 2010, Henan, China Gao S. 收藏 \| 浏览/下载：15/0 \| 提交时间：2013/03/25 This paper presents an intelligent video surveillance system. The system is composed of one or more nodes flexibly according to the application scenarios such as private properties banks and museums. Each node is an autonomous vision-based device capable to perform intelligent tasks. It is able to digitize and compress the acquired analog video signals in MPEG-4 standard and then transmit the compressed video stream to the control center. At the same time the node makes use of a statistical approach for real-time detecting moving object and online alarm generation to enable a single human operator to monitor activities over a complex area using a distributed network of active video sensors. The node is implemented on a platform with high performance to ensure that the algorithm is able to run in real-time. Applications demonstrate that the intelligent system has an excellent performance in many scenarios to help people make decisions more accurately and rapidly. 2010 IEEE.