# Title Team Members TA Documents Sponsor
24 Machine Learning Enabled Wearable Stethoscope
Erlis Kllogjri
Natalia Migdal
Samuel Felder
Hershel Rege design_review
There have been many recent advances around using several machine learning methods to detect and identify abnormalities in heart beat and lung breath audio. We are proposing a wearable system (to be worn around the chest) which will record audio, and analyze it, looking for abnormalities in the heart beats or lung sounds. This would provide a significant improvement in care for people at risk of issues with heart or lungs because it would be equivalent to having the attention of a doctor at all times. Use cases include examples such as firefighters (who have high rates of heart defects, and are also at risk of smoke inhalation on the job), hospital patients coming out of heart or lung surgery, or people who have history of issues with heart or lungs.

The sensor would comprise of a sensitive microphone (and associated DSP circuitry), which would pick up the sounds from the heart or lungs. This would then get sent to the next sub-unit, which would process the audio. Depending on the complexity of either implementation (and the time and resource limitations) we could either use a microprocessor to implement a k-NN or a CNN algorithm to identify the sounds, or process through a hardware implementation of the k-NN or CNN.

Once a worrisome sound is identified, it is communicated to the relevant party. In the case of hospital patients, it would be communicated to the doctor and nurses station. In the case of at home care, it would be communicated to doctor and emergency services. Finally in the case of emergency personnel (firefighters) it would be communicated to the captain and other emergency personnel. The communication would be implemented through RF. This has many advantages; it can be integrated with existing medical pager system, and since it only communicates when there is an issue it does not always need to be activated (and in the use cases it would only need to activate a handful of times), saving in power requirements.

Cloud-controlled quadcopter

Anuraag Vankayala, Amrutha Vasili

Cloud-controlled quadcopter

Featured Project


To build a GPS-assisted, cloud-controlled quadcopter, for consumer-friendly aerial photography.


We will be building a quad from the frame up. The four motors will each have electronic speed controllers,to balance and handle control inputs received from an 8-bit microcontroller(AP),required for its flight. The firmware will be tweaked slightly to allow flight modes that our project specifically requires. A companion computer such as the Erle Brain will be connected to the AP and to the cloud(EC2). We will build a codebase for the flight controller to navigate the quad. This would involve sending messages as per the MAVLink spec for sUAS between the companion computer and the AP to poll sensor data , voltage information , etc. The companion computer will also talk to the cloud via a UDP port to receive requests and process them via our code. Users make requests for media capture via a phone app that talks to the cloud via an internet connection.

Why is it worth doing:

There is currently no consumer-friendly solution that provides or lets anyone capture aerial photographs of them/their family/a nearby event via a simple tap on a phone. In fact, present day off-the-shelf alternatives offer relatively expensive solutions that require owning and carrying bulky equipment such as the quads/remotes. Our idea allows for safe and responsible use of drones as our proposed solution is autonomous, has several safety features, is context aware(terrain information , no fly zones , NOTAMs , etc.) and integrates with the federal airspace seamlessly.

End Product:

Quads that are ready for the connected world and are capable to fly autonomously, from the user standpoint, and can perform maneuvers safely with a very simplistic UI for the common user. Specifically, quads which are deployed on user's demand, without the hassle of ownership.

Similar products and comparison:

Current solutions include RTF (ready to fly) quads such as the DJI Phantom and the Kickstarter project, Lily,that are heavily user-dependent or user-centric.The Phantom requires you to carry a bulky remote with multiple antennas. Moreover,the flight radius could be reduced by interference from nearby conditions.Lily requires the user to carry a tracking device on them. You can not have Lily shoot a subject that is not you. Lily can have a maximum altitude of 15 m above you and that is below the tree line,prone to crashes.

Our solution differs in several ways.Our solution intends to be location and/or event-centric. We propose that the users need not own quads and user can capture a moment with a phone.As long as any of the users are in the service area and the weather conditions are permissible, safety and knowledge of controlling the quad are all abstracted. The only question left to the user is what should be in the picture at a given time.

Project Videos