Calendar

Week Monday Tuesday Wednesday Thursday Friday
1/20
First class meeting 4:00p - 5:50p ECEB 1002
1/27
Second class meeting 4:00p - 5:50p ECEB 1002
CAD assignment due 11:59p
2/3
Add/Drop Deadline due 11:59p
Third class meeting 4:00p - 5:50p ECEB 1002
Project approval due 11:59p
2/10
First team meetings with TAs 4:00p ECEB 3081
Proposals due 11:59p
Initial Conversation With Machine Shop (required if using the shop) due 4:00p ECEB 1047
Team Contract due 11:59p
Proposal Review Sign-up due 11:59p
2/17
Proposal Review 8:00a - 6:00p With Instructor and TAs
Proposal Review 8:00a - 6:00p With Instructor and TAs
Proposal Review 8:00a - 6:00p With Instructor and TAs
2/24
PCB Review 3:00p - 5:00p ECEB 3081
3/3
Design Document due 11:59p
3/10
Breadboard Demo 8:00a - 6:00p WIth Instructor and TA
Breadboarrd Demo 8:00a - 6:00p With Instructor and TA
Breadboard Demo 8:00a - 6:00p With Instructor and TA
Last day for revisions to the machine shop due ECEB 1048
3/17
Spring Break
Spring Break
Spring Break
Spring Break
Spring Break
3/24
3/31
4/7
4/14
4/21
Mock demo During weekly TA mtg
Mock demo During weekly TA mtg
Mock demo During weekly TA mtg
Mock demo During weekly TA mtg
Mock demo During weekly TA mtg
4/28
Final Demo With Instructor and TAs
Final Demo With Instructor and TAs
Final Demo With Instructor and TAs
Mock Presentation With Comm and ECE TAs
Mock Presentation With Comm and ECE TAs
Extra Credit Video Assignment due 11:59p
5/5
Final Presentation With instructor and TAs
Final Presentation With Instructor and TAs
Final papers due 11:59p
Lab checkout 3:00p - 4:30p With TA
Award Ceremony 4:30p - 5:30p ECEB 3002
Lab Notebook Due due 11:59p

Backpack Buddy - Wearable Proximity/Incident Detection for Nighttime Safety

Jeric Cuasay, Emily Grob, Rahul Kajjam

Backpack Buddy - Wearable Proximity/Incident Detection for Nighttime Safety

Featured Project

# 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

Project Videos