{"title":"Vehicle sensing data acquisition and analysis","authors":"Linna Wu, Lizhuo Zhang, Huan Li, Hengtian Ding","doi":"10.1145/3277868.3277873","DOIUrl":"https://doi.org/10.1145/3277868.3277873","url":null,"abstract":"In this research, we explore the process of using the on-board device to recognize the driving events and collect massive vehicle sensing data. We collect about more than 1,900 million GPS data points and more than 700 million event data records in China from 13/04/2016 to 16/01/2017 for 9 months. These massive GPS data and event data can be used to promote a diversity of applications, e.g., insurance applications and intelligent transportation systems.","PeriodicalId":320905,"journal":{"name":"Proceedings of the First Workshop on Data Acquisition To Analysis","volume":"8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-11-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125272138","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}
P. Pannuto, B. Kempke, Bradford Campbell, P. Dutta
{"title":"Indoor ultra wideband ranging samples from the DecaWave DW1000 including frequency and polarization diversity","authors":"P. Pannuto, B. Kempke, Bradford Campbell, P. Dutta","doi":"10.1145/3277868.3277874","DOIUrl":"https://doi.org/10.1145/3277868.3277874","url":null,"abstract":"When performing RF ranging in a complex indoor environment, the error of a single channel estimate can vary widely. A key insight of the PolyPoint and SurePoint ranging protocols is that individual nodes can efficiently capture multiple independent samples of the RF channel. For each point in space, nodes capture twenty seven independent samples by varying the spectrum sampled and the polarization of antennas. This dataset includes all of the measurements reported in the PolyPoint and SurePoint papers, which comprises several thousand points in a complex indoor environment. Precise 3D coordinates of nodes were captured using an optical motion capture system calibrated to millimeter accuracy. Several tracking studies are included, with continuous samples over time as a node moves through the environment.","PeriodicalId":320905,"journal":{"name":"Proceedings of the First Workshop on Data Acquisition To Analysis","volume":"121 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-11-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122332236","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}
K. Arendt, Aslak Johansen, B. Jørgensen, M. Kjærgaard, C. Mattera, Fisayo Caleb Sangogboye, J. Schwee, C. Veje
{"title":"Room-level occupant counts, airflow and CO2 data from an office building","authors":"K. Arendt, Aslak Johansen, B. Jørgensen, M. Kjærgaard, C. Mattera, Fisayo Caleb Sangogboye, J. Schwee, C. Veje","doi":"10.1145/3277868.3277875","DOIUrl":"https://doi.org/10.1145/3277868.3277875","url":null,"abstract":"The area of occupant sensing is lacking public datasets to baseline and foster data-driven research. This abstract describes a dataset covering room-level occupant counts, in-room ventilation airflow and CO2 data from an office building. This dataset can among others be used for developing and evaluating data-driven algorithms for occupant sensing and building analytics.","PeriodicalId":320905,"journal":{"name":"Proceedings of the First Workshop on Data Acquisition To Analysis","volume":"15 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-11-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124265688","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}
Bernhard Großwindhager, M. Rath, Josef Kulmer, M. Bakr, C. Boano, K. Witrisal, K. Römer
{"title":"Dataset: single-anchor indoor localization with decawave DW1000 and directional antennas","authors":"Bernhard Großwindhager, M. Rath, Josef Kulmer, M. Bakr, C. Boano, K. Witrisal, K. Römer","doi":"10.1145/3277868.3277879","DOIUrl":"https://doi.org/10.1145/3277868.3277879","url":null,"abstract":"Highly-accurate localization of wireless devices is a critical feature of future Internet-of-Things applications. Due to its superior time-domain resolution, ultra-wideband (UWB) technology allows centimeter-level positioning accuracy. Still, setting up an anchor-based UWB localization system requires extensive labour and costs. Recent works have shown that, instead of multiple physical anchors, the exploitation of multipath reflections from walls minimizes the required infrastructure to a single anchor. This dataset contains an extensive measurement campaign in two complex indoor environments with one anchor. It contains line-of-sight as well as non-line-of-sight situations. Furthermore, we have acquired datasets using directional antennas at the anchor to allow observing the impact of the angular domain on the localization performance.","PeriodicalId":320905,"journal":{"name":"Proceedings of the First Workshop on Data Acquisition To Analysis","volume":"227 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-11-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134374460","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}
{"title":"Bluetooth low energy in the wild dataset","authors":"Thomas Zachariah, Meghan Clark, P. Dutta","doi":"10.1145/3277868.3277882","DOIUrl":"https://doi.org/10.1145/3277868.3277882","url":null,"abstract":"In 2015, we performed a study to learn which Bluetooth Low Energy peripheral devices were most prevalent among consumers, as well as which services these devices provided and utilized in practice. Additionally, we sought to investigate the real-world usage of standard Bluetooth services versus custom protocols among developers. The study involved a continuous month-long scan taken on two floors of an academic building. The resulting dataset consists of scan results from approximately 3000 unique devices.","PeriodicalId":320905,"journal":{"name":"Proceedings of the First Workshop on Data Acquisition To Analysis","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-11-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129897063","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}
{"title":"PiMi","authors":"R. Ma, Lin Zhang","doi":"10.1145/3277868.3277869","DOIUrl":"https://doi.org/10.1145/3277868.3277869","url":null,"abstract":"Monitoring indoor PM2.5 concentration and understanding the cause of indoor PM2.5 pollution are essential for people's health in urban areas. Previous studies under controlled experiments are hard to be generalized and datasets under real circumstances are with small scale limited by either the material resources or the manpower resources. To address these challenges, we utilize the methodology of participatory sensing to collect 133 million indoor PM2.5 samples along with labels of building characteristics and human behaviors, from 407 ordinary citizens in Beijing. Together with the simultaneous outdoor PM2.5 concentrations from national air quality monitoring stations, our dataset provide opportunities for studies on indoor air quality, time series analysis as well as time series modeling.","PeriodicalId":320905,"journal":{"name":"Proceedings of the First Workshop on Data Acquisition To Analysis","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-11-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115024498","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}
{"title":"Structural vibration sensing to evaluate animal activity on a pig farm: extended abstract","authors":"Amelie Bonde, Shijia Pan, Orathai Sangpetch, Akkarit Sangpetch, Woranun Woramontri, Pei Zhang","doi":"10.1145/3277868.3277881","DOIUrl":"https://doi.org/10.1145/3277868.3277881","url":null,"abstract":"Automated monitoring of animal behavior can detect changes in animal welfare and health problems. Different animal behaviors can point to disease, unrest or inadequate management, and detecting such behaviors in real time allows automated monitoring to be a valuable tool in livestock production [2]. When monitoring pigs, important sow events such as oestrus, pregnancy or parturition may also be detected through continuous animal monitoring [1].","PeriodicalId":320905,"journal":{"name":"Proceedings of the First Workshop on Data Acquisition To Analysis","volume":"43 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-11-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123470683","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}
{"title":"Set and forget sensing with applets on IFTTT","authors":"Noah Klugman, P. Dutta","doi":"10.1145/3277868.3277880","DOIUrl":"https://doi.org/10.1145/3277868.3277880","url":null,"abstract":"Rich data sets can be collected trivially by bootstrapping off mobile phones and cloud services. We describe an end-to-end system built with IFTTT that requires no code to collect arrival and departure times from a geographic area on the campus of the University of California, Berkeley. This system was configured and deployed in less than one half hour, cost nothing to deploy or run, and functioned without interruption for seven months, taking 463 measurements of a single participant. Along with providing the data set, which provides some insight into the working life of a graduate student, we describe each part of the system architecture and discuss how a model of sensing-as-an-applet enables data streams with de-facto standardized, high reliability, and close-to-no-barrier of entry.","PeriodicalId":320905,"journal":{"name":"Proceedings of the First Workshop on Data Acquisition To Analysis","volume":"25 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-11-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131474957","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}
D. V. Le, Yingbo Liu, Rongrong Wang, Rui Tan, L. Ngoh
{"title":"A testbed and data yields for studying data center energy efficiency and reliability","authors":"D. V. Le, Yingbo Liu, Rongrong Wang, Rui Tan, L. Ngoh","doi":"10.1145/3277868.3277877","DOIUrl":"https://doi.org/10.1145/3277868.3277877","url":null,"abstract":"Many data centers still adopt low temperature setpoints, resulting in high energy consumption of their cooling systems. In our ongoing research project, we have built a data center testbed consisting of three test rooms hosting servers and network equipment. In particular, the testbed is equipped with cooling, heating, and ventilation systems that are under our full control. Thus, we can operate the testbed in a wide range of server room conditions. The test rooms and servers are instrumented with hardware and software sensors monitoring more than 200 measurement points. An extensive test plan is being executed to collect a large volume of data to understand the impact of environmental conditions on server's computing performance and reliability as well as the energy efficiency of the testbed. The results will provide important guidelines for building and operating energy-efficient data centers. We will work with relevant authorities towards providing the data collected from the testbed to the research communities.","PeriodicalId":320905,"journal":{"name":"Proceedings of the First Workshop on Data Acquisition To Analysis","volume":"9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-11-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131539722","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}
{"title":"Seat vibration for heart monitoring in a moving automobile: extended abstract","authors":"Amelie Bonde, Mostafa Mirshekari, Jonathon Fagert, Shijia Pan, H. Noh, Pei Zhang","doi":"10.1145/3277868.3277872","DOIUrl":"https://doi.org/10.1145/3277868.3277872","url":null,"abstract":"Continuous heart rate monitoring in cars can allow ambient health monitoring and help track driver stress and fatigue. We present a data set from accelerometers embedded in a car seat which includes ten people sitting in the passenger seat of a moving car, and surface ECG data of each user to provide ground truth of the heartbeat. This data can be used to analyze the heart activity of people in cars, despite the presence of high levels of noise from car motion, human motion, and the car engine.","PeriodicalId":320905,"journal":{"name":"Proceedings of the First Workshop on Data Acquisition To Analysis","volume":"18 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-11-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123845856","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}