Accurate indoor localization has the potential to transform the way people navigate indoors in a similar way that GPS transformed the way people navigate outdoors. Over the last 15 years, several indoor localization technologies have been proposed and experimented by both academia and industry, but we have yet to see large scale deployments. This competition aims to bring together real-time or near real-time indoor location technologies and compare their performance in the same space.
The competition is on! We are happy to announce that we have received 36 submissions from 32 teams spanning academia, industry, and startups!
All submissions have been assigned to one of two categories depending on the requirement to deploy custom hardware or not. The list of all submissions in each category is as follows:
|Pirkl et al.||Indoor Localization Based on Resonant Oscillating Magnetic Fields|
|Li et al.||Indoor Localization with Multi-modalities (Light)|
|Ashok et al.||InfraRad: A Radio-Optical Beaconing Approach for Accurate Indoor Localization|
|Adler et al.||FUBLoc - Accurate Range-based Indoor Localization and Tracking|
|Selavo et al.||Localization Using Digitally Steerable Antennas|
|Bestmann et al.||EasyPoint - Indoor Localization and Navigation Low Cost, Reliable and Accurate|
|Schmid et al.||High-Resolution Indoor RF Ranging|
|Ehrig et al.||A 60GHz System for Simultaneous Time of Flight Ranging and High-Speed Wireless Data Communication|
|Sark at al.||A Software Defined Radio for Time of Flight Based Ranging and Localization|
|Taylor et al.||Low-cost Hybrid Indoor Localization with Light Fixtures|
|Kleunen et al.||Locus: Space-based Indoor Positioning|
|Lazik et al.||ALPS: An Ultrasonic Localization System|
|Sigg et al.||Passive Device-Free Indoor Localization from RSSI|
|Dentamaro et al.||Nextome - Indoor Positioning and Navigation System|
|Jiang et al.||HiLoc: A TDoA-Fingerprint Hybrid Indoor Localization System|
|Abrudan et al.||IMU-Aided magneto-inductive Localization|
|Burgess at al.||Indoo.rs (iPhone + BLE)|
|Nikodem et al.||Indoor Localization Based on Low-Power Chirp Transceivers|
|Sigg et al.||Device-Free Indoor Localization|
|Yang et al.||A step into mm-scale treatment! Multipath-Resistant Tracking for Mobile RFID Tags|
|Brucato et al.||Modeling and Prototyping a Personal Object Finder. The NEVERLOST Real Time Localization System Use Case|
|Ferraz et al.||Ubee.in - An Indoor Location Solution for Mobile Devices|
|Li et al.||Indoor Localization with Multi-modalities (WiFi + sensors)|
|Zhang et al.||MaWi: A Hybrid Magnetic and Wi-Fi System for Scalable Indoor Localization|
|Laoudias at al.||Accurate Multi-Sensor Localization on Android Devices|
|Klepal et al.||MapUme - WiFi Based Localization System|
|Jiang et al.||FreeLoc: Infrastructure-Free Indoor Localization|
|GiPSTech||A Novel Hybrid/Geomagnetic Field Based Technology for Indoor Navigation|
|Zou et al.||WiFi Based Indoor Localization System by Using Weighted Path Loss and Extreme Machine Learning|
|Xiao et al.||Indoor Tracking Using Conditional Random Fields|
|Yun et al.||Vision-Based 3D Indoor localization|
|Marcaletti et al.||WINS: Tracking of Mobile Devices with WiFi Time-Of-Flight|
|Burgess at al.||Indoo.rs (Android + WiFI)|
|Ghose et al.||UnsupLoc - A System for infrastructure Friendly Unsupervised Indoor Localization|
|Quintas et al.||Indoor Localization and Tracking Using 802.11 networks and Smartphones|
|Ohrt et al.||Room-Based Indoor Localization using WiFi-Fingerprinting and Machine Learning|
Call for Contesters
Both academia and industry submissions are encouraged. All location techniques, such as ranging, fingerprinting, infrastructure, or device free, are welcome, except those that require end users’ manual measurements. Contesters can deploy their own infrastructure of up to 10 devices. Normal RF interference is expected, but no jammers for other deployments are allowed. The results must be shown on a portable device, such as a phone or a tablet/laptop that a person can easily carry around.
Demo submissions that do not meet one or more of the guidelines above will be included in the poster session and will be evaluated as a regular submission, but they will not be considered for prizes.
The competition will take place if at least 5 teams respond to this preliminary call for competition.
Depending on the nature and number of submissions multiple categories might be defined based on the accuracy (i.e., point-based vs. area based), the size, the cost, or the type (i.e., software vs. hardware) of the proposed solution. The final set of categories will be announced after the registration deadline.
A poster session dedicated to all competition participants will be organized during the conference. Participants will have the opportunity to explain their system to conference attendees.
Evaluation and Prize:
Results are judged based on both room/zone level accuracy and absolute accuracy, and an award will be given for the top 2 teams in each category. When accuracy ties, infrastructure requirements will be used for tie breaking. The winning team in each category will be invited to present their approach at the conference, and receive a cash award.
Contesters must submit an abstract describing their approach and deployment requirements by the contest registration deadline. Submissions are treated as confidential until the competition. Submissions must be at most one (1) single-spaced 8.5" x 11" pages, including figures, tables, and references. Submission should follow the exact same format as regular, full IPSN 2014 papers. Templates can be found here: http://ipsn.acm.org/2014/submissions.html
Submission and Registration Deadline:
- Contest Registration and Abstract Deadline: January 10, 2014, 11:59 pm EST.
- To register for the competition, please email your abstract to firstname.lastname@example.org with the following subject line: Indoor Localization Competition Submission.
For more information and clarification, you can contact Dimitrios Lymberopoulos (email@example.com)
Dimitrios Lymberopoulos (Microsoft Research)
Romit Roy Choudhury (UIUC)
Xue Yang (Intel Labs)
Souvik Sen (HP Labs)