Scope and Topics of the Workshop
In recent years, the location information of people has become increasingly important for many emerging applications, such as large-coverage Location Based Services (LBS), smart buildings, and analytics of user spatial location big data. Although the Global Positioning System (GPS) provides satisfactory outdoor positioning services, it does not work indoor. WiFi fingerprinting based on Received Signal Strength Indicator (RSSI) has been widely used in commercial indoor positioning systems because of its high accuracy and ubiquitousness. To build up radio maps, professionals consume huge amount of time to conduct site surveying for the ground truth location labels. Therefore, at present, the traditional fingerprinting systems are merely deployed at certain buildings where a site survey has been conducted by professionals. They cannot achieve ubiquitous positioning with large coverage for a massive number of buildings e.g., in the scenario of smart cities.
To achieve ubiquitous positioning, efficient ways for calibrating indoor positioning systems have become an emerging topic in recent years. To avoid intensive training efforts in fingerprinting, it is becoming interesting for researchers to crowdsense radio maps. Crowdsensing indoor positioning systems collect location-related information from crowdsourcing users instead of professionals, such as WiFi RSSI, Pedestrian Dead Reckoning (PDR) traces, and GPS, to automatically build radio maps. Besides WiFi fingerprinting, indoor positioning systems based on visible light, ultra-wide band signals (UWB signals), and (ultrasonic) sound signals have been investigated but they also face the problem of training with intensive efforts. Besides the efficiency of indoor positioning systems, enhanced positioning solutions in both outdoor and indoor environments are also interested in this workshop, especially the enhanced solutions for cooperated positioning among multiple targets, sensor-fusion based seamless outdoor-indoor positioning by fusing multiple positioning techniques, such as magnetic field, visible light, UWB signals (ultrasonic) sound signals, WiFi, Bluetooth, cellular signals, inertial sensors and GPS, machine learning techniques for indoor positioning.
TOPICS OF INTEREST INCLUDE, BUT ARE NOT LIMITED TO, THE FOLLOWING:
- Crowdsensing indoor positioning;
- Indoor Positioning with ubiquitous signals, such as magnetic field, visible light, WiFi, Bluetooth, cellular signals;
- Indoor positioning with wireless signals, such as Ultra-Wide Band signals, mmWave;
- Cooperated positioning;
- Sensors fusion based positioning;
- Indoor positioning with wearable sensors;
- Seamless indoor and outdoor positioning;
- Machine learning techniques for indoor positioning;
- Signal processing in indoor positioning.
Papers submitted to the workshop should be written in English conforming to the IEEE Conference Proceedings Format. The paper should be submitted through the edas submission system. Prospective authors are invited to submit full papers up to 6 pages in length. Accepted and presented papers will be included into the IEEE explore. Authors of accepted papers, or at least one of them, are requested to register and present their work at the workshop, otherwise their papers will be removed from the digital libraries of IEEE after the conference.
All papers to the workshop must be submitted through EDAS, using the link:
Technical Paper Submission: 15 May 2019
Technical Paper Notification: 25 June 2019
Zan Li, Jilin University (email@example.com)
Bo Wang, Jilin University (firstname.lastname@example.org)
Dayang Sun, Jilin University (email@example.com)
Zhongliang Zhao, University of Bern (firstname.lastname@example.org)