@inproceedings{2016_2C_metroeye,
  title={Metroeye: smart tracking your metro trips underground},
  author={Gu, Weixi and Jin, Ming and Zhou, Zimu and Spanos, Costas J and Zhang, Lin},
  booktitle={International Conference on Mobile and Ubiquitous Systems: Computing, Networking and Services (MobiQuitous)},
  url_pdf={metroeye_paper.pdf},
  url_link={https://dl.acm.org/doi/10.1145/2968219.2971437},
  url_poster={metroeye.pdf},
  keywords={Smart city, Data mining},
  abstract={Subway has become the first choice of traveling for people in metropolis due to its efficiency and convenience. Yet passengers have to rely on subway broadcasts to know their locations because popular localization services (e.g. GPS and wireless localization technologies) are often unavailable underground. To this end, we propose MetroEye, a fine-grained passenger tracking service underground. MetroEye leverages smartphone sensors to record ambient contextual features, and infers the state of passengers (including stop, running, and interchange) during a metro trip using a Conditional Random Field (CRF) model. MetroEye further provides arrival alarm services based on individual passenger state, and aggregates crowdsourced interchange durations to guide passengers for intelligent metro trip planning. Experimental results within 6 months across over 14 subway trains in 3 major cities demonstrate that MetroEye outperforms the state-of-the-art.},
  pages={84--93},
  year={2016},
  note={<font style="color:#FF0000">(Best Paper Runner-up)</font>}
}

{"_id":"ocZsTrpmoT8XEjvpi","bibbaseid":"gu-jin-zhou-spanos-zhang-metroeyesmarttrackingyourmetrotripsunderground-2016","author_short":["Gu, W.","Jin, M.","Zhou, Z.","Spanos, C. J","Zhang, L."],"bibdata":{"bibtype":"inproceedings","type":"inproceedings","title":"Metroeye: smart tracking your metro trips underground","author":[{"propositions":[],"lastnames":["Gu"],"firstnames":["Weixi"],"suffixes":[]},{"propositions":[],"lastnames":["Jin"],"firstnames":["Ming"],"suffixes":[]},{"propositions":[],"lastnames":["Zhou"],"firstnames":["Zimu"],"suffixes":[]},{"propositions":[],"lastnames":["Spanos"],"firstnames":["Costas","J"],"suffixes":[]},{"propositions":[],"lastnames":["Zhang"],"firstnames":["Lin"],"suffixes":[]}],"booktitle":"International Conference on Mobile and Ubiquitous Systems: Computing, Networking and Services (MobiQuitous)","url_pdf":"metroeye_paper.pdf","url_link":"https://dl.acm.org/doi/10.1145/2968219.2971437","url_poster":"metroeye.pdf","keywords":"Smart city, Data mining","abstract":"Subway has become the first choice of traveling for people in metropolis due to its efficiency and convenience. Yet passengers have to rely on subway broadcasts to know their locations because popular localization services (e.g. GPS and wireless localization technologies) are often unavailable underground. To this end, we propose MetroEye, a fine-grained passenger tracking service underground. MetroEye leverages smartphone sensors to record ambient contextual features, and infers the state of passengers (including stop, running, and interchange) during a metro trip using a Conditional Random Field (CRF) model. MetroEye further provides arrival alarm services based on individual passenger state, and aggregates crowdsourced interchange durations to guide passengers for intelligent metro trip planning. Experimental results within 6 months across over 14 subway trains in 3 major cities demonstrate that MetroEye outperforms the state-of-the-art.","pages":"84–93","year":"2016","note":"<font style=\"color:#FF0000\">(Best Paper Runner-up)</font>","bibtex":"@inproceedings{2016_2C_metroeye,\n title={Metroeye: smart tracking your metro trips underground},\n author={Gu, Weixi and Jin, Ming and Zhou, Zimu and Spanos, Costas J and Zhang, Lin},\n booktitle={International Conference on Mobile and Ubiquitous Systems: Computing, Networking and Services (MobiQuitous)},\n url_pdf={metroeye_paper.pdf},\n url_link={https://dl.acm.org/doi/10.1145/2968219.2971437},\n url_poster={metroeye.pdf},\n keywords={Smart city, Data mining},\n abstract={Subway has become the first choice of traveling for people in metropolis due to its efficiency and convenience. Yet passengers have to rely on subway broadcasts to know their locations because popular localization services (e.g. GPS and wireless localization technologies) are often unavailable underground. To this end, we propose MetroEye, a fine-grained passenger tracking service underground. MetroEye leverages smartphone sensors to record ambient contextual features, and infers the state of passengers (including stop, running, and interchange) during a metro trip using a Conditional Random Field (CRF) model. MetroEye further provides arrival alarm services based on individual passenger state, and aggregates crowdsourced interchange durations to guide passengers for intelligent metro trip planning. Experimental results within 6 months across over 14 subway trains in 3 major cities demonstrate that MetroEye outperforms the state-of-the-art.},\n pages={84--93},\n year={2016},\n note={<font style=\"color:#FF0000\">(Best Paper Runner-up)</font>}\n}\n\n","author_short":["Gu, W.","Jin, M.","Zhou, Z.","Spanos, C. J","Zhang, L."],"key":"2016_2C_metroeye","id":"2016_2C_metroeye","bibbaseid":"gu-jin-zhou-spanos-zhang-metroeyesmarttrackingyourmetrotripsunderground-2016","role":"author","urls":{" pdf":"http://www.jinming.tech/papers/metroeye_paper.pdf"," link":"https://dl.acm.org/doi/10.1145/2968219.2971437"," poster":"http://www.jinming.tech/papers/metroeye.pdf"},"keyword":["Smart city","Data mining"],"metadata":{"authorlinks":{}}},"bibtype":"inproceedings","biburl":"http://www.jinming.tech/papers/myref.bib","dataSources":["sTzDHHaipTZWjp8oe","Y64tp2HnDCfXgLdc5"],"keywords":["smart city","data mining"],"search_terms":["metroeye","smart","tracking","metro","trips","underground","gu","jin","zhou","spanos","zhang"],"title":"Metroeye: smart tracking your metro trips underground","year":2016}