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Proceedings of the 2nd Workshop on Data Acquisition To Analysis最新文献

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Dataset: Channel state information for different activities, participants and days 数据集:不同活动、参与者和日期的通道状态信息
Proceedings of the 2nd Workshop on Data Acquisition To Analysis Pub Date : 2019-11-10 DOI: 10.1145/3359427.3361913
J. K. Brinke, N. Meratnia
{"title":"Dataset: Channel state information for different activities, participants and days","authors":"J. K. Brinke, N. Meratnia","doi":"10.1145/3359427.3361913","DOIUrl":"https://doi.org/10.1145/3359427.3361913","url":null,"abstract":"In our current society, unobtrusive sensing has become an important tool to monitor the physical world, as it is easy to use and privacy-aware. Remote sensing is a new and heavily researched technology based on the analysis of radio signals. A particular field research in this area is the analysis of channel state information with the raw signal, as this contains the most information. While most research focuses on analysis of individuals or clustered data, little to no research has gone into the analysis of channel state information of multiple people over multiple days for different and comparable activities. This dataset contains data of nine different participants over three different days, with an two participants repeating the activities over an additional three days. The dataset is available at the 4TU.ResearchData under the CC BY-NC-SA license [4].","PeriodicalId":267440,"journal":{"name":"Proceedings of the 2nd Workshop on Data Acquisition To Analysis","volume":"97 1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-11-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116709668","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 9
Synchronization between Sensors and Cameras in Movement Data Labeling Frameworks 运动数据标记框架中传感器与摄像机的同步
Proceedings of the 2nd Workshop on Data Acquisition To Analysis Pub Date : 2019-11-10 DOI: 10.1145/3359427.3361920
Jacob W. Kamminga, Michael D. Jones, Kevin Seppi, N. Meratnia, P. Havinga
{"title":"Synchronization between Sensors and Cameras in Movement Data Labeling Frameworks","authors":"Jacob W. Kamminga, Michael D. Jones, Kevin Seppi, N. Meratnia, P. Havinga","doi":"10.1145/3359427.3361920","DOIUrl":"https://doi.org/10.1145/3359427.3361920","url":null,"abstract":"Obtaining labeled data for activity recognition tasks is a tremendously time consuming, tedious, and labor-intensive task. Often, ground-truth video of the activity is recorded along with sensordata recorded during the activity. The data must be synchronized with the recorded video to be useful. In this paper, we present and compare two labeling frameworks that each has a different approach to synchronization. Approach A uses time-stamped visual indicators positioned on the data loggers. The approach results in accurate synchronization between video and data but adds more overhead and is not practical when using multiple sensors, subjects, and cameras simultaneously. Also, synchronization needs to be redone for each recording session. Approach B uses Real-Time Clocks (RTCs) on the devices for synchronization, which is less accurate but has several advantages: multiple subjects can be recorded on various cameras, it becomes easier to collect more data, and synchronization only needs to be done once across multiple recording sessions. Therefore, it is easier to collect more data which increases the probability of capturing an unusual activity. The best way forward is likely a combination of both approaches.","PeriodicalId":267440,"journal":{"name":"Proceedings of the 2nd Workshop on Data Acquisition To Analysis","volume":"161 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-11-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127365211","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 3
Occupancy Sensing and Activity Recognition with Cameras and Wireless Sensors 摄像机和无线传感器的占用感测和活动识别
Proceedings of the 2nd Workshop on Data Acquisition To Analysis Pub Date : 2019-11-10 DOI: 10.1145/3359427.3361911
Yang Zhao, P. Tu, Ming-Ching Chang
{"title":"Occupancy Sensing and Activity Recognition with Cameras and Wireless Sensors","authors":"Yang Zhao, P. Tu, Ming-Ching Chang","doi":"10.1145/3359427.3361911","DOIUrl":"https://doi.org/10.1145/3359427.3361911","url":null,"abstract":"We present a system work combining visual cameras and wireless sensors for human occupancy detection and activity recognition. We describe our testbed system, data collected from a human subject study, observations from long-term occupancy experiments, and preliminary analytical results. We apply machine learning algorithms to the human activity recognition data, and identify challenges in applying the state-of-the-art deep learning techniques to wireless sensing of human activity. We find that packet loss due to wireless interference has a significant effect on time series classification. We also find that the convolutional neural networks significantly outperforms the conventional support vector machine method, but further experiments need to be performed to investigate environment-independent classification and the overfitting issue. Finally, we discuss future research topics that can use our testbed of wireless sensors and visual cameras to automate data labeling in deep learning model training.","PeriodicalId":267440,"journal":{"name":"Proceedings of the 2nd Workshop on Data Acquisition To Analysis","volume":"32 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-11-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129238577","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 8
Designing a Vehicle Mounted High Resolution Multi-Spectral 3D Scanner: Concept Design 设计车载高分辨率多光谱3D扫描仪:概念设计
Proceedings of the 2nd Workshop on Data Acquisition To Analysis Pub Date : 2019-11-10 DOI: 10.1145/3359427.3361921
G. Meyers, Chengxi Zhu, M. Mayfield, D. Tingley, J. Willmott, D. Coca
{"title":"Designing a Vehicle Mounted High Resolution Multi-Spectral 3D Scanner: Concept Design","authors":"G. Meyers, Chengxi Zhu, M. Mayfield, D. Tingley, J. Willmott, D. Coca","doi":"10.1145/3359427.3361921","DOIUrl":"https://doi.org/10.1145/3359427.3361921","url":null,"abstract":"Buildings can improve their energy efficiency through retrofitting and thus decrease energy demand throughout the life of the building. However, evaluating building retrofit opportunities at a city level is a significant challenge. This requires identifying where in the city the biggest energy efficiency gains can be made and in the most cost-effective way. A surveyor is typically relied upon to manually assess a building for insulation absence, defective installation, thermal leakage and other similar issues. To perform these inspections across whole cities would be prohibitively time intensive. There is therefore a need for a faster approach to detect and prioritise a city's retrofit requirements so that effective value for money decisions can be made. In this paper, the concept design of a vehicle mounted integrated sensing platform to collect high resolution visual, thermal and 3D scene data of the built environment at a city scale is presented. Initial design considerations are first explored before an initial concept design is presented and evaluated. From the evaluation, a number of concerns about the design were raised. Based on these findings, a significantly revised concept design is subsequently presented that addresses the aforementioned issues.","PeriodicalId":267440,"journal":{"name":"Proceedings of the 2nd Workshop on Data Acquisition To Analysis","volume":"51 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-11-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129040235","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 5
A Signal Quality Assessment Metrics for Vibration-based Human Sensing Data Acquisition 基于振动的人体传感数据采集信号质量评估指标
Proceedings of the 2nd Workshop on Data Acquisition To Analysis Pub Date : 2019-11-10 DOI: 10.1145/3359427.3361918
Yue Zhang, Lin Zhang, H. Noh, Pei Zhang, Shijia Pan
{"title":"A Signal Quality Assessment Metrics for Vibration-based Human Sensing Data Acquisition","authors":"Yue Zhang, Lin Zhang, H. Noh, Pei Zhang, Shijia Pan","doi":"10.1145/3359427.3361918","DOIUrl":"https://doi.org/10.1145/3359427.3361918","url":null,"abstract":"Sensing signal quality affects signal processing efficiency, feature extraction, and learning accuracy. An efficient and accurate assessment of sensing system signal quality is essential for 1) large-scale cyber-physical system deployment and 2) datasets sharing and comparison. In this paper, we present a signal quality assessment -- S-score -- for vibration-based human sensing applications from two aspects -- the hardware implementation and the deployment structure. The 1) signal-to-noise ratio and 2) the signal frequency response consistency over 2.1) sensing hardware, and 2.2) deployment structure are essential factors for structural vibration sensing signal evaluation. The S-score metrics combines these factors to a value between 0 and 1 with application-oriented weights. We compared the proposed metrics to two baselines, and our metrics achieved the highest correlation to the system performance, which is the indicator of the data quality.","PeriodicalId":267440,"journal":{"name":"Proceedings of the 2nd Workshop on Data Acquisition To Analysis","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-11-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124228280","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 8
Channel State Information (CSI) analysis for Predictive Maintenance using Convolutional Neural Network (CNN) 基于卷积神经网络(CNN)的预测维修通道状态信息(CSI)分析
Proceedings of the 2nd Workshop on Data Acquisition To Analysis Pub Date : 2019-11-10 DOI: 10.1145/3359427.3361917
Prachi Bagave, Jeroen Linssen, W. Teeuw, J. K. Brinke, N. Meratnia
{"title":"Channel State Information (CSI) analysis for Predictive Maintenance using Convolutional Neural Network (CNN)","authors":"Prachi Bagave, Jeroen Linssen, W. Teeuw, J. K. Brinke, N. Meratnia","doi":"10.1145/3359427.3361917","DOIUrl":"https://doi.org/10.1145/3359427.3361917","url":null,"abstract":"With the onset of the fourth industrial revolution, predictive maintenance using wireless sensing technologies has been in high demand. This motivates to investigate the potential of WiFi CSI as a sensor for understanding the operation of machines. Since rotating motors are one of the fundamental elements in many complex machines, this paper focuses on the classification of CSI signals influenced by rotating motors at different speeds. As WiFi CSI technology is still not mature, we focus on data collection and study the sensitivity and reliability of data for this type of applications. We observe that CNNs are suitable to classify the speeds of motors and is also sensitive to speeds close to each other when operated in ideal network condition. However, in practical network conditions, unreliability of the data and the inability of CNN to classify it remains a challenge.","PeriodicalId":267440,"journal":{"name":"Proceedings of the 2nd Workshop on Data Acquisition To Analysis","volume":"9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-11-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115401491","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 7
Dataset: User side acquisition of People-Centric Sensing in the Internet-of-Things 数据集:物联网中以人为中心的传感的用户端采集
Proceedings of the 2nd Workshop on Data Acquisition To Analysis Pub Date : 2019-11-10 DOI: 10.1145/3359427.3361914
Chenguang Liu, Jie Hua, T. Kalbarczyk, Sangsu Lee, C. Julien
{"title":"Dataset: User side acquisition of People-Centric Sensing in the Internet-of-Things","authors":"Chenguang Liu, Jie Hua, T. Kalbarczyk, Sangsu Lee, C. Julien","doi":"10.1145/3359427.3361914","DOIUrl":"https://doi.org/10.1145/3359427.3361914","url":null,"abstract":"We envision a world where people-centric sensing and personalized services can be achieved without centralized data collection and processing or the reliance on video-based surveillance. To help assess the feasibility of building context-aware applications while allowing users to fully control their potentially sensitive data, we studied the feasibility of people-centric sensing using only user-side data acquisition. Using only off-the-shelf, energy restricted sensor kits in a smart environment together with an energy-efficient message exchange scheme implemented on top of Bluetooth Low Energy, the collected dataset provides insight on a continuous cyber-physical view from users' individual perspectives. The availability of the dataset encourages further studies of users' activities, for instance to perform distributed inference on users' social interactions and activity trajectories.","PeriodicalId":267440,"journal":{"name":"Proceedings of the 2nd Workshop on Data Acquisition To Analysis","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-11-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130489128","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 1
Dataset: Occupancy Detection, Tracking, and Estimation Using a Vertically Mounted Depth Sensor 数据集:使用垂直安装的深度传感器的占用检测，跟踪和估计
Proceedings of the 2nd Workshop on Data Acquisition To Analysis Pub Date : 2019-11-10 DOI: 10.1145/3359427.3361916
F. Flores, Sirajum Munir, Matias Quintana, Anand P. Krishnan, M. Berges
{"title":"Dataset: Occupancy Detection, Tracking, and Estimation Using a Vertically Mounted Depth Sensor","authors":"F. Flores, Sirajum Munir, Matias Quintana, Anand P. Krishnan, M. Berges","doi":"10.1145/3359427.3361916","DOIUrl":"https://doi.org/10.1145/3359427.3361916","url":null,"abstract":"Occupancy detection, tracking, and estimation has a wide range of applications including improving building energy efficiency, safety, and security of the occupants. As depth sensors are getting cheaper, they offer a viable solution to estimate occupancy accurately in a non-privacy invasive manner. Even though there are publicly available depth datasets, they do not consider placing the sensor in the ceiling looking downwards to estimate occupancy. We deployed four Kinect for XBOX One in four CMU classrooms and conference rooms for a period of four weeks in 2017 and collected over 6 TB of depth data. We annotate this huge dataset by labelling bounding boxes around occupants and release the annotated dataset.","PeriodicalId":267440,"journal":{"name":"Proceedings of the 2nd Workshop on Data Acquisition To Analysis","volume":"5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-11-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114144898","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 7
Dataset: Wireless Link Quality Estimation on FlockLab - and Beyond 数据集:无线链路质量估计在FlockLab -和超越
Proceedings of the 2nd Workshop on Data Acquisition To Analysis Pub Date : 2019-11-10 DOI: 10.1145/3359427.3361907
Romain Jacob, Reto Da Forno, Roman Trüb, Andreas Biri, L. Thiele
{"title":"Dataset: Wireless Link Quality Estimation on FlockLab - and Beyond","authors":"Romain Jacob, Reto Da Forno, Roman Trüb, Andreas Biri, L. Thiele","doi":"10.1145/3359427.3361907","DOIUrl":"https://doi.org/10.1145/3359427.3361907","url":null,"abstract":"In wireless networks, link quality quantifies how \"challenging\" the environment is for a communication protocol. The performance of protocols are often compared using wireless testbeds and it is therefore important to monitor the testbed's link quality to ensure a fair comparison ground across different protocols. Thus, we are collecting link quality estimation data for FlockLab, an extensively used public testbed. We publish this dataset together with our data collection firmware. This firmware has been designed to facilitate the collection of similar datasets for other wireless networks. The dataset and firmware are publicly available together on Zenodo: doi.org/10.5281/zenodo.3354718.","PeriodicalId":267440,"journal":{"name":"Proceedings of the 2nd Workshop on Data Acquisition To Analysis","volume":"48 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-11-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127230003","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 8
Proceedings of the 2nd Workshop on Data Acquisition To Analysis 第二届数据采集与分析研讨会论文集
Proceedings of the 2nd Workshop on Data Acquisition To Analysis Pub Date : 1900-01-01 DOI: 10.1145/3359427
{"title":"Proceedings of the 2nd Workshop on Data Acquisition To Analysis","authors":"","doi":"10.1145/3359427","DOIUrl":"https://doi.org/10.1145/3359427","url":null,"abstract":"","PeriodicalId":267440,"journal":{"name":"Proceedings of the 2nd Workshop on Data Acquisition To Analysis","volume":"17 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134555809","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
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