{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,12]],"date-time":"2025-10-12T04:24:39Z","timestamp":1760243079471,"version":"build-2065373602"},"reference-count":53,"publisher":"MDPI AG","issue":"6","license":[{"start":{"date-parts":[[2015,6,15]],"date-time":"2015-06-15T00:00:00Z","timestamp":1434326400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100002341","name":"Academy of Finland","doi-asserted-by":"publisher","award":["272195"],"award-info":[{"award-number":["272195"]}],"id":[{"id":"10.13039\/501100002341","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Micromachines"],"abstract":"<jats:p>The rapid advance in mobile communications has made information and services ubiquitously accessible. Location and context information have become essential for the effectiveness of services in the era of mobility. This paper proposes the concept of  geo-context that is defined as an integral synthesis of geographical location, human motion state and mobility context. A geo-context computing solution consists of a positioning engine, a motion state recognition engine, and a context inference component. In the geo-context concept, the human motion states and mobility context are associated with the geographical location where they occur. A hybrid geo-context computing solution is implemented that runs on a smartphone, and it utilizes measurements of multiple sensors and signals of opportunity that are available within a smartphone. Pedestrian location and motion states are estimated jointly under the framework of hidden Markov models, and they are used in a reciprocal manner to improve their estimation performance of one another. It is demonstrated that pedestrian location estimation has better accuracy when its motion state is known, and in turn, the performance of motion state recognition can be improved with increasing reliability when the location is given. The geo-context inference is implemented simply with the expert system principle, and more sophisticated approaches will be developed.<\/jats:p>","DOI":"10.3390\/mi6060699","type":"journal-article","created":{"date-parts":[[2015,6,15]],"date-time":"2015-06-15T10:57:58Z","timestamp":1434365878000},"page":"699-717","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":9,"title":["Reciprocal Estimation of Pedestrian Location and Motion State toward a Smartphone Geo-Context Computing Solution"],"prefix":"10.3390","volume":"6","author":[{"given":"Jingbin","family":"Liu","sequence":"first","affiliation":[{"name":"Department of Remote Sensing and Photogrammetry, Finnish Geospatial Research Institute, National Land Survey of Finland, Masala 02431, Finland"},{"name":"Centre of Excellence in Laser Scanning Research, Academy of Finland, Finland"}]},{"given":"Lingli","family":"Zhu","sequence":"additional","affiliation":[{"name":"Department of Remote Sensing and Photogrammetry, Finnish Geospatial Research Institute, National Land Survey of Finland, Masala 02431, Finland"},{"name":"Centre of Excellence in Laser Scanning Research, Academy of Finland, Finland"}]},{"given":"Yunsheng","family":"Wang","sequence":"additional","affiliation":[{"name":"Department of Remote Sensing and Photogrammetry, Finnish Geospatial Research Institute, National Land Survey of Finland, Masala 02431, Finland"},{"name":"Centre of Excellence in Laser Scanning Research, Academy of Finland, Finland"}]},{"given":"Xinlian","family":"Liang","sequence":"additional","affiliation":[{"name":"Department of Remote Sensing and Photogrammetry, Finnish Geospatial Research Institute, National Land Survey of Finland, Masala 02431, Finland"},{"name":"Centre of Excellence in Laser Scanning Research, Academy of Finland, Finland"}]},{"given":"Juha","family":"Hyypp\u00e4","sequence":"additional","affiliation":[{"name":"Department of Remote Sensing and Photogrammetry, Finnish Geospatial Research Institute, National Land Survey of Finland, Masala 02431, Finland"},{"name":"Centre of Excellence in Laser Scanning Research, Academy of Finland, Finland"}]},{"given":"Tianxing","family":"Chu","sequence":"additional","affiliation":[{"name":"Conrad Blucher Institute of Surveying & Science, Texas A & M University Corpus Christi,  Corpus Christi, TX 78412-5868, USA"}]},{"given":"Keqiang","family":"Liu","sequence":"additional","affiliation":[{"name":"Conrad Blucher Institute of Surveying & Science, Texas A & M University Corpus Christi,  Corpus Christi, TX 78412-5868, USA"}]},{"given":"Ruizhi","family":"Chen","sequence":"additional","affiliation":[{"name":"Conrad Blucher Institute of Surveying & Science, Texas A & M University Corpus Christi,  Corpus Christi, TX 78412-5868, USA"}]}],"member":"1968","published-online":{"date-parts":[[2015,6,15]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"125","DOI":"10.1016\/j.eswa.2014.07.042","article-title":"Indoor localization in a hospital environment using Random Forest classifiers","volume":"42","author":"Calderoni","year":"2015","journal-title":"Expert Syst. 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