Project

# Title Team Members TA Documents Sponsor
8 Backpack Buddy - Wearable Proximity/Incident Detection for Nighttime Safety
Emily Grob
Jeric Cuasay
Rahul Kajjam
 Zicheng Ma design_document1.pdf
final_paper1.pdf
photo1.PNG
photo2.png
presentation1.pdf
proposal1.pdf
video
# Backpack Buddy

Team Members:
- Student 1 (cuasay2)
- Student 2 (rkajjam2)
- Student 3 (eegrob2)

# Problem

The UIUC campus is relatively a safe place. We have emergency buttons throughout campus and security personnel available regularly. However, crime still occurs and affects students walking alone, especially at night. Staying up late at night working in a classroom or other building can lead to a long scary walk home. Especially when the weather is colder, the streets are generally less populated and walking home at night can feel more dangerous due to the isolation.

# Solution

A wearable system that uses night vision camera sensor and machine learning/intelligence image processing techniques to detect pedestrians approaching the user at an abnormal speed or angle that may be out of sight. The system would vibrate to alert them to look around and check their surroundings.

# Solution Components

## Subsystem 1 - Processing

Processing
Broadcom BCM2711 SoC with a 64-bit quad-core ARM Cortex-A72 processor or potentially an internal microprocessor such as the LPC15xx series for image processing and voltage step-down to various sensors and actuators

## Subsystem 2 - Power
Power
Converts external battery power to required voltage demands of on-system chips

## Subsystem 3 - Sensors
Sensors
Camera - Night Vision Camera Adjustable-Focus Module 5MP OV5647 to detect objects in the dark
Proximity sensor - detects obstacle distance before turning camera on, potentially ultrasonic or passive infrared sensors such as the HC-SR04
Haptic feedback - Vibrating Mini Motor Disc [ADA1201] to alert user something was identified


# Criterion For Success

The Backpack Buddy will provide an image based solution for identifying any imposing figure within the user's blind spots to help ensure the safety of our user. Our solution is unique as there currently no wearable visual monitoring solutions for night-time safety.


potential stuff:
Potentially: GNSS for location tracking, light sensor for outdoors identification, and heartbeat for user stress levels
camera stabilization
heat camera

Cloud-controlled quadcopter

Anuraag Vankayala, Amrutha Vasili

Cloud-controlled quadcopter

Featured Project

Idea:

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

Design/Build:

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