Blog Posts

oblu @ Zest, HBTU

(1-Mar-2017) Visitors were quite fascinated by seeing such products being developed in their own town. Many of the engineering students want to carry out their projects using "oblu". It feels glad to make such a niche technology affordable and accessible for STEM education. Technology Democratized !

Talk on Demystifying Wearable Embedded Systems

(31-Jan-2017) Thanks KIT for inviting Amit and Subhojyoti of team oblu to deliver a talk over Demystifying Wearable Embedded Systems. The students were introduced to MEMS, inertial sensors, indoor positioning systems, pedestrian dead reckoning (PDR) and a lot more. As a case study, role of oblu as a PDR sensor in tracking firefighters during rescue operation and indoor navigation of robots were demoed.

Thesis by Aaditya Verma on Analysis of Foot-Mounted Navigation System for Surveying

Foot mounted inertial navigation systems, which can be used for personnel tracking, also have potential application in surveying where the satellite signals are not easily available. Aaditya Verma of Geoinformatics, Dept of Civil Engg, IIT Kanpur successfully defends his M.Tech. thesis titled "Analysis of Foot-Mounted Navigation System for Surveying". His work investigates the possibility of using such foot mounted inertial navigation systems in the field of surveying. Thank you Aaditya Verma and Prof Bharat Lohani for your contribution in the advancement of technology !

PDR with Foot-Mounted Sensors

(20-Jan-2016) PDR gets simplified with our foot sensor- oblu. In simple words, the sensor detects steps, computes displacement and heading of each detected step w.r.t the previous one and transmit it over Bluetooth to the application platform (Phone/Tab/Radio) for construction of the tracked path.

Warehouse management, first responders' tracking, augmented reality, indoor navigation, gait analysis, geo-survey etc are some of the applications of such sensors. 

Positioning Using Ultra Low-cost Sensors

(10-Jun-2016) Isaac Skog (Researcher, Signal Processing Department, KTH, Sweden) explains how the combination of motion model (the zero-velocity-update approach) and sensor fusion (the multi-IMU approach) improve performance and thus enable indoor positioning and motion sensing applications with the help of ultra low cost inertial sensors.

 

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