View source for Autonomous Smart Watches: Toward an ultra low power microphone detector with events classification

[[File:Smartwatch.jpg|400px|right|thumb]]
==Short Description==
Today sensors and wearable technologies are gaining popularity, with people increasingly surrounded by “smart” objects. Machine learning is used with great success in wearable devices and sensors in several real-world applications. In this project we address the challenges of context recognition on low energy and self-sustainable wearable devices.

You will investigate the possibility to implement neural network in a ultra low power energy efficient micro-controller (Ambiq Apollo). The mail goal of the project will be implement and evaluate a complete neural network using already available framework to achieve context recognition. The idea behind this project would be to build a working prototype of a wearable multi-sensor devices which is able to collect and process data directly on board matching the requirements of long life time when supplied by a battery.

Depending on the applicant's profile and project type, his tasks may involve some of the following:

* Developing the context recognition algorithm with neural network and implement them on the Ambiq Apollo
* Design and develop a new version of the wearable device which include sensors and the new micrcoprocessor (Ambiq Apollo)
* lab. testing/characterization of the existing prototype: verification of the prototype's characteristics w.r. design specification (simulations), measuring power-consumption, and assessing detection performance in lab. conditions
* programming the circuit for specific application, field testing
* printed circuit-board design to make it suitable for long term monitoring. 

===Status: Available ===
* Looking for Semester and Master Project Students
: Supervisors: [[:User:magnom|Michele Magno]]
: Supervisors: [[:User:Lukasc|Lukas Cavigelli]]

===Prerequisites===
(''not all need to be met'' by the single candidate)
* analog electronics and signal conditioning with operational amplifiers: amplifiers, filters, integrators etc.
* knowledge of micro-controller programming (C)
* basic knowledge on signal processing is a plus.
* plus is knowledge on printed circuit board (PCB) using Altium. 

===Character===
: 30% Theory
: 50% Implementation
: 20% Testing

===Professor===
: [http://www.iis.ee.ethz.ch/portrait/staff/lbenini.en.html Luca Benini]
<!-- : [http://www.iis.ee.ethz.ch/portrait/staff/huang.en.html Qiuting Huang] --->
<!-- : [http://lne.ee.ethz.ch/en/general-information/people/professor.html Vanessa Wood] --->
<!-- : [http://www.iis.ee.ethz.ch/portrait/staff/mluisier.en.html Mathieu Luisier] --->
<!-- : [http://www.iis.ee.ethz.ch/portrait/staff/schenk.en.html Andreas Schenk] --->
<!-- : [http://www.dz.ee.ethz.ch/en/general-information/about/staff/uid/364.html Hubert Kaeslin] --->
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==Detailed Task Description==

===Goals===
===Practical Details===
* '''[[Project Plan]]'''
* '''[[Project Meetings]]'''
* '''[[Design Review]]'''
* '''[[Coding Guidelines]]'''
* '''[[Final Report]]'''
* '''[[Final Presentation]]'''

==Results== 


[[Category:Digital]]
[[Category:Available]]
[[Category:Semester Thesis]]
[[Category:Master Thesis]]
[[Category:System Design]]

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GROUP
[[Category:Digital]]
[[Category:Analog]]
[[Category:Nano-TCAD]]
[[Category:Nano Electronics]]

STATUS
[[Category:Available]]
[[Category:In progress]]
[[Category:Completed]]
[[Category:Hot]]

TYPE OF WORK
[[Category:Semester Thesis]]
[[Category:Master Thesis]]
[[Category:PhD Thesis]]
[[Category:Research]]

NAMES OF EU/CTI/NT PROJECTS
[[Category:UltrasoundToGo]]
[[Category:IcySoC]]
[[Category:PSocrates]]
[[Category:UlpSoC]]
[[Category:Qcrypt]]

YEAR (IF FINISHED)
[[Category:2010]]
[[Category:2011]]
[[Category:2012]]
[[Category:2013]]
[[Category:2014]]

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