Difference between revisions of "IPIN 2017"
Jump to navigation
Jump to search
Heike.Rohde (talk | contribs) |
Tim Holzheim (talk | contribs) (Added page provenance(#264) and contribution type(#271)) |
||
(One intermediate revision by one other user not shown) | |||
Line 9: | Line 9: | ||
|City=Sapporo | |City=Sapporo | ||
|Country=Japan | |Country=Japan | ||
− | |has general chair=Hideo Makino, Jesús Ureña | + | |Has coordinator=Masanori Sugimoto |
+ | |has general chair=Hideo Makino, Jesús Ureña | ||
|has program chair=Takeshi Kurata, Phong Nguyen | |has program chair=Takeshi Kurata, Phong Nguyen | ||
|has Proceedings Link=http://www.proceedings.com/36939.html | |has Proceedings Link=http://www.proceedings.com/36939.html | ||
+ | |pageCreator=Heike.Rohde | ||
+ | |pageEditor=Heike.Rohde | ||
+ | |contributionType=1 | ||
}} | }} | ||
* | * |
Latest revision as of 20:01, 1 April 2022
IPIN 2017 | |
---|---|
International Conference on Indoor Positioning and Indoor Navigation
| |
Event in series | IPIN |
Dates | 2017/09/18 (iCal) - 2017/09/21 |
Location | |
Location: | Sapporo, Japan |
Committees | |
Organizers: | Masanori Sugimoto |
General chairs: | Hideo Makino, Jesús Ureña |
PC chairs: | Takeshi Kurata, Phong Nguyen |
Table of Contents | |
- Topics of submission
- User Requirements
- Hybrid IMU Pedestrian Navigation & Foot Mounted Navigation
- Human Motion Monitoring
- High Sensitivity GNSS, Indoor GNSS, Pseudolites
- RTK GNSS with handheld devices
- Mitigating GNSS errors prior to moving indoors
- Self-contained sensors
- Signal Strength Based Methods, Fingerprinting
- UWB (Ultra-wideband)
- Passive & Active RFID
- Optical Systems
- Ultrasound Systems
- TOF, TDOA based Localization
- Localization, Algorithms for Wireless Sensor Networks
- Frameworks for Hybrid Positioning
- Industrial Metrology & Geodetic Systems, iGPS
- Radar Systems
- Mapping, SLAM
- Indoor Spatial Data Model & Indoor Mobile Mapping
- Novel uses of maps and 3D building models
- Magnetic Localization
- Innovative Systems
- Location Privacy
- Applications of Location Awareness & Context Detection
- Health and Wellness Applications