Mock Presentation

Description

Similar to the Design Doc Check and the Mock Demo, the Mock Presentation is an informal, mandatory event designed to better prepare you for your Final Presentation. In these sessions, you will present a few of your slides (about 10-15 minutes), and get feedback from the course staff as well as a few invited Department of Communication TAs. You will also be able to see a few of your peers' Mock Presentations, as there are up to 3 teams per time slot.

Requirements and Grading

The Mock Presentation is meant to be an opportunity for you to get feedback on a subset of your final presentation. It is recommended that you choose some aspect of your project, and present the design, results, and conclusions from that aspect. In order to get relevant feedback on your presentation skills, your Mock Presentation should also have an introduction and conclusion. You will receive feedback on your delivery, the format of your slides, and the organization of your presentation. Your slides should generally include:

  1. Title slide: Names, group #, title.
  2. Introduction slide: What is the project?
  3. Objective slide: What problem does this solve?
  4. Design Slides: A few slides on design, requirements and verification (should include block diagram, math, graphs, figures, tables).
  5. Conclusion: Wrap things up, future work.

Mock presentation is graded credit/no credit based on attendance and apparent effort; showing up completely unprepared will earn no credit.

Submission and Deadlines

Sign-up is handled through PACE. Time slots are 1 hour long, and multiple groups will share a time slot. This will give you an opportunity to give and receive feedback from your peers. You will be required to stay until all groups have presented and received feedback.

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