MEng Opening in IoT Sensor Fusion for Indoor Mapping


Fadel Adib and Mergen Nachin

Mergen Nachin

IoT Sensor Fusion for Indoor Mapping (Computer Vision + Micro-Location)

Micro-location is one of the most important building blocks for the IoT (Internet-of-Things). The Signal Kinetics group has developed a new technology capable of locating billions of IoT devices with applications to smart environments, robotic perception, factory automation, and virtual reality.

We have a Masters of Engineering (MEng) opportunity (RAship+thesis) to work on this technology. The MEng project is focused on Sensor Fusion for Indoor Mapping. The project involves fusing data from mobile cameras with our technology to create IoT-annotated 3D indoor maps. The MEng student will be working with a team of researchers and interacting with various industry sponsors. The final prototype will be deployed in the real world. 

More information about the technology can be found in the RFind paper and the MIT article on RF-Grasp.

Interested applicants can send an email with CV, transcript, and interests to: 

Required Background:

* C/C++ and/or Python Programming

* Background in Computer Vision

* Aptitude and interest in hacking and rapid prototyping

Desirable (but not required) Background in any of the following:

* Experience in Computer Vision libraries

* Experience in mobile programming (iOS/iPadOS/Android)

The following can also be helpful (but not required):

* Experience in real-time signal processing

* Experience in cloud programming

* Experience in FPGA programming

* Experience with software-define radios (e.g., USRP, BladeRF)

* Background in RF, PCB Design, or Antenna Design

Courses that are helpful (but not pre-requisites):

* Most relevant: 6.808, 6.819/6.869, 6.046

* Also relevant: 6.02, 6.08, 6.011, 6.033, 6.341

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