Project

# Title Team Members TA Documents Sponsor
6 E-Bike Crash Detection and Safety
Adam Arabik
Ayman Reza
Muhammad Daniyal Amir
Shengkun Cui design_document1.pdf
final_paper1.pdf
presentation1.pdf
proposal1.pdf
# Title

Team Members:
- Ayman Reza (areza6)
- Muhammad Amir (mamir6)
- Adam Arabik (aarabik2)

#Problem
E-bikes are gaining popularity as a sustainable and convenient mode of transportation. The main issue with the growing number of e-bikes is the safety of the rider and those around them. If a rider gets into a crash, there is no automatic shutoff for the electrical systems on an e-bike. This means that the bike's motor can remain on, potentially causing more harm to the rider or the surrounding environment. Current safety systems installed on electronic devices typically focus only on post-crash communication, such as sending alerts to contacts or calling emergency services. There is currently no system that can detect a crash in real time and instantly cut power to the bike’s electrical systems to improve safety.

#Solution
My group's solution is a crash detection system with a motor shutoff that can integrate with e-bike systems. This device will use its own sensors and electrical measurements to recognize when a crash occurs. Once a crash is detected, the system will cut all power to the motor, ensuring that the bike can no longer accelerate even if the throttle is still engaged. To reduce false positives, the system will use a module that combines data from multiple sensors to provide a more accurate assessment of whether a cutoff is needed. In addition, the design will include a manual override that allows the rider to turn the motor back on and continue operating the bike normally. The goal of this project is to create a crash protection system that reacts quickly to its environment to prevent further harm during a crash.

#Solution Components

##Subsystem 1: Crash Detection Sensors

This subsystem is responsible for detecting sudden deceleration, impacts, or abnormal electrical behavior that indicates a crash. The design will use an accelerometer and gyroscope, like the MPU-6050, to monitor motion and angular velocity. A current sensor like the ACS712 will be used to detect sudden changes in motor current that occur during impact. An optional vibration or impact sensor may be added to confirm collision events and improve reliability.

##Subsystem 2: Control and Processing Unit

This subsystem will process the inputs from the sensors, run the crash-detection algorithm, and issue the motor cutoff command. The system will be built around a microcontroller, such as an STM32 or ESP32, which has the processing capability to fuse sensor data and apply threshold-based decision making. The microcontroller will also handle input from the manual reset and override switch to allow the rider to re-enable the system if a false detection occurs.

##Subsystem 3: Motor Cutoff Circuit

The subsystem physically disconnects the motor power when a crash is detected. A MOSFET-based switch will be used to cut power from the e-bike motor controller. The cutoff circuit will be designed to handle the motor’s current and respond within milliseconds. Once triggered, the motor will remain disabled until the system is reset by the rider.


##Subsystem5: Testing and Validation Setup

The subsystem is focused on verifying the accuracy and timing of the system under controlled and real-world conditions. The initial bench testing will involve tapping the sensor and measuring how quickly the motor cutoff occurs using the oscilloscope. The controlled crash simulation will be performed by stopping the spinning wheel or using drop tests to mimic the impact. Field tests will involve riding the e-bike over curbs, bumps, and rough pavement to ensure the system doesn’t false trigger during normal use. Once a crash has been detected, the motor can be re enabled using the reset button.

#Criterion for Success

The rider must be able to manually cut and enable power to the motor at any time using switches on the electrical systems. If the bike tips over onto its side, the motor must turn off automatically. If the bike comes to an immediate stop that indicates a crash, the motor must turn off automatically. The system needs to be able to work with e-bike motors.

STRE&M: Automated Urinalysis (Pitched Project)

Gage Gulley, Adrian Jimenez, Yichi Zhang

STRE&M: Automated Urinalysis (Pitched Project)

Featured Project

Team Members:

- Gage Gulley (ggulley2)

- Adrian Jimenez (adrianj2)

- Yichi Zhang (yichi7)

The STRE&M: Automated Urinalysis project was pitched by Mukul Govande and Ryan Monjazeb in conjunction with the Carle Illinois College of Medicine.

#Problem:

Urine tests are critical tools used in medicine to detect and manage chronic diseases. These tests are often over the span of 24 hours and require a patient to collect their own sample and return it to a lab. With this inconvenience in current procedures, many patients do not get tested often, which makes it difficult for care providers to catch illnesses quickly.

The tedious process of going to a lab for urinalysis creates a demand for an “all-in-one” automated system capable of performing this urinalysis, and this is where the STRE&M device comes in. The current prototype is capable of collecting a sample and pushing it to a viewing window. However, once it gets to the viewing window there is currently not an automated way to analyze the sample without manually looking through a microscope, which greatly reduces throughput. Our challenge is to find a way to automate the data collection from a sample and provide an interface for a medical professional to view the results.

# Solution

Our solution is to build an imaging system with integrated microscopy and absorption spectroscopy that is capable of transferring the captured images to a server. When the sample is collected through the initial prototype our device will magnify and capture the sample as well as utilize an absorbance sensor to identify and quantify the casts, bacteria, and cells that are in the sample. These images will then be transferred and uploaded to a server for analysis. We will then integrate our device into the existing prototype.

# Solution Components

## Subsystem1 (Light Source)

We will use a light source that can vary its wavelengths from 190-400 nm with a sampling interval of 5 nm to allow for spectroscopy analysis of the urine sample.

## Subsystem2 (Digital Microscope)

This subsystem will consist of a compact microscope with auto-focus, at least 100x magnification, and have a digital shutter trigger.

## Subsystem3 (Absorbance Sensor)

To get the spectroscopy analysis, we also need to have an absorbance sensor to collect the light that passes through the urine sample. Therefore, an absorbance sensor is installed right behind the light source to get the spectrum of the urine sample.

## Subsystem4 (Control Unit)

The control system will consist of a microcontroller. The microcontroller will be able to get data from the microscope and the absorbance sensor and send data to the server. We will also write code for the microcontroller to control the light source. ESP32-S3-WROOM-1 will be used as our microcontroller since it has a built-in WIFI module.

## Subsystem5 (Power system)

The power system is mainly used to power the microcontroller. A 9-V battery will be used to power the microcontroller.

# Criterion For Success

- The overall project can be integrated into the existing STRE&M prototype.

- There should be wireless transfer of images and data to a user-interface (either phone or computer) for interpretation

- The system should be housed in a water-resistant covering with dimensions less than 6 x 4 x 4 inches

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