Idea Details

Team and Contact Details

SNo Student Name School Degree Year Email
1Muhammad SulaimanSEECSUndergraduateFourthmsulaiman.bee15seecs@seecs.edu.pk
1Bilal Isa KhanSEECSUndergraduateFourthbkhan.bee15seecs@seecs.edu.pk
1Muhammad Shaheer RazaSEECSUndergraduateFourthmreza.bee15seecs@seecs.edu.pk

Inter School Idea ? No
Do you need expertises from another area: No
If Yes please provide details of expertises you need:

Idea Details

Idea Name: True Detect
Slogan: Intelligence at Work
Supervisor Name: Dr. Syed Ali Hassan
Supervisor Designation: Associate Professor
Supervisor School: School of Electrical Engneering and Computer Science
Supervisor Department: Department of Electrical Engineering
Contact number: 03365892041
Email ID: ali.hassan@seecs.edu.pk
Abstract:
    With the increasing usage of WiFi for data transfer, we exploit IoT to build smart networks. Our idea makes use of these WiFi signals for gesture recognition without the use of wearable devices.
What is the unmet need in society that your idea will fulfill ?
    Gesture Recognition is fast becoming one of the most interesting aspects of smart-devices. Gestures can be used for controlling UI or giving commands. Conventionally, this required the use of active devices (camera) but with the help of WiFi signals, this can be done without any wearable device.
Who needs it ? How many would benefit ?
   Companies interested in smart devices can really benefit from this. Smart TV's and game console UI control, control of personal assistants like Alexa are a few application areas of this product. For example, Kinect - which is used for tracking user movements sold 24 million units in its lifetime.
How will the solution works
    WiFi waves can pass through walls and bodies and any information about the environment is embedded in the CSI (Channel State Information). We extract this information using off-the-shelf commodity NIC (Network Interface Card) and leverage pattern recognition abilities of machine learning to detect gesture.
Who are your competitors ? How is your solution different
    The current solutions to gesture recognition require expensive hardware to be installed in homes, our solution aims to provide better results using less equipment. By using WiFi for something other than connectivity, we are recognizing gestures without generating more radio frequency noise.
Status: Approved
Entry Date & Time: 2019-01-14 (1347)