Short biography

Sanjha Khan received a BE degree in Electronic Engineering and Master’s degree in Mechatronics Engineering from Mehran University of Engineering and Technology Jamshoro. During post graduation she also served as Laboratory Assistant at Communication and Robotics lab, where she worked on several communication and robotic related research projects, secure top position for project competition and published the results in a Research Journal and in ASYU IEEE international conference 2019 at Turkey. Soon after postgrad she joined multinational industry named “GlaxoSmithKline” as a GPS Practitioner, where along with the management related tasks, she worked on ‘Digital Management Board’ for the site and received the INNOVATION award on successful completion of the project. Later she also served as lecturer for three years in Dawood University of Engineering and Technology. Currently she is pursuing Ph.D. degree in Network Engineering from Universitat Politècnica de Catalunya (UPC) and working on the `Application of Visible Light Communication´ at Fundació i2CAT (Barcelona, Spain) as a part of the 5GsmartFact project of European Union's Horizon 2020.

Short description of project objectives

This research aims to design and validate applications of visual light.

• Design and validate new energy self-sufficient IoT motes tailored to industrial environments. These motes will integrate a processing unit, and will leverage VLC for communications and energy harvesting. VLC-only and hybrid RF-VLC designs will be considered.

• Design novel transmission and access techniques to enhance availability and reliability focusing on distributed deployments of active and passive radiating elements, as well as the hybridization with VLC.

• Development of cm-level tracking and positioning algorithms that use VLC emitting devices as reference markers in a 3D environment.

• Characterization of mmWave technology to achieve high precision localization through AoA and ToF in industrial environments.

• Investigate energy-efficiency technologies and the use of hybrid VLC-RF solutions to improve indoor positioning.

• Algorithms to fuse localization data coming from RF and VLC systems, robust to non-LoS situations, that will be used for assisting robot navigation, and tools tracking