Project

# Title Team Members TA Documents Sponsor
46 Snooze-Cruiser
Alex Wang
Jiachen Hu
Jizhen Chen
Jiaming Xu design_document1.pdf
proposal1.pdf
#Snooze-Cruiser
Team Members:

Jiachen Hu (hu86)

Jizhen Chen (jizhenc2)

Alex Wang (zw71)

#Problem

Many people suffer from sleep inertia, a condition where individuals instinctively silence alarms without fully waking up. Traditional alarm clocks and smartphone alarms rely solely on audio, which can be easily ignored or dismissed while half asleep. Existing alternative solutions such as puzzle-based alarms or flying alarms are often ineffective, unsafe, or impractical in confined environments like dorm rooms and bedrooms.

The fundamental issue is that current alarm systems fail to reliably force physical engagement, allowing users to return to sleep without becoming fully alert. A more effective alarm must require the user to physically interact with the system in order to disable it.

#Solution

We propose Snooze-Cruiser, a two-wheeled differential-drive robotic alarm system that physically moves away from the user when the alarm time is reached. Instead of simply producing sound, the robot navigates around the room, forcing the user to get out of bed and chase it in order to silence the alarm.

The robot operates autonomously in a confined indoor space, using onboard sensors for obstacle avoidance and odometry-based localization to remain within a defined area. The alarm is disabled not by pressing a button, but by detecting when the robot has been picked up using inertial sensor data. This interaction ensures that the user must physically wake up and engage with the device.

The system is divided into motion control, sensing, alarm/audio, localization, and power management subsystems.

#Solution Components

##Subsystem 1: Motion Control and Navigation

Function:
This subsystem enables the robot to move autonomously, wander unpredictably, and avoid obstacles while remaining within a confined area.

Components:

Microcontroller: STM32F446RCT6

Motor Driver: DRV8833PWP dual H-bridge motor driver

Motors: N20 micro gear motors with quadrature encoders (x2)

Inertial Measurement Unit: MPU6050

Obstacle Sensors: VL53L1X Time-of-Flight distance sensors (multiple)

Description:
The STM32 generates PWM signals to control the motors through the DRV8833 motor driver. Wheel encoders provide feedback for estimating speed and displacement. During alarm operation, the robot drives forward at a base speed and periodically introduces random heading changes. Obstacle avoidance is triggered when distance sensors detect nearby obstacles, causing the robot to turn away and resume wandering motion. Encoder and IMU data are fused to estimate the robot’s position relative to its starting point.

##Subsystem 2: Localization and Soft Geofencing

Function:
This subsystem prevents the robot from leaving the intended operating area (e.g., a bedroom).

Components:

Wheel Encoders (from Subsystem 1)

IMU: MPU6050

Description:
Wheel encoder data and IMU measurements are fused using a Kalman Filter (or equivalent sensor fusion approach) to estimate the robot’s displacement from its starting location. A soft geofence is defined as a radius around this starting point. If the robot exceeds this radius, it enters a return-to-center behavior by rotating toward the estimated origin and driving inward until it re-enters the allowed area.

##Subsystem 3: Alarm Timing and Audio Output

Function:
This subsystem handles timekeeping and audible alarm generation.

Components:

Microcontroller: STM32F446RCT6

Audio Amplifier: PAM8301AAF

Speaker

Description:
The STM32 maintains a real-time counter for alarm scheduling. When the preset alarm time is reached, the microcontroller simultaneously enables the audio amplifier and activates the motion subsystem. The alarm sound continues until a valid caught event is detected.

##Subsystem 4: Caught Detection (User Interaction)

Function:
This subsystem detects when the robot has been picked up by the user and disables the alarm.

Components:

IMU: MPU6050

Wheel Encoders

Description:
Caught detection is performed by analyzing IMU acceleration and vibration data in combination with wheel encoder feedback. A caught event is identified by sudden changes in acceleration magnitude, high-frequency vibrations from human handling, and inconsistencies between wheel motion and measured acceleration (indicating loss of ground contact). Once confirmed, the system immediately stops motor output and silences the alarm.

##Subsystem 5: Power Management

Function:
This subsystem supplies and regulates power for the robot.

Components:

Battery Charger IC: MCP73844

Rechargeable Battery

Voltage Regulation Circuitry

Description:
The battery supplies power to the MCU, sensors, motor driver, and audio system. The MCP73844 manages battery charging. Voltage regulation ensures stable operation during high current events such as motor startup.

#Criterion For Success

The project will be considered successful if the following objective criteria are met:

Timed Activation:
The alarm triggers within ±X seconds of the programmed time.

Synchronized Operation:
Robot motion and alarm audio start simultaneously upon alarm activation.

Autonomous Motion:
The robot moves continuously without user intervention during alarm operation.

Obstacle Avoidance:
The robot avoids obstacles placed in its path without repeated collisions.

Confined Operation:
The robot remains within a predefined operating radius and returns toward the starting location when the boundary is exceeded.

Caught Detection:
When picked up by a user, the robot reliably stops motion and audio within a short time window.

BusPlan

Aashish Kapur, Connor Lake, Scott Liu

BusPlan

Featured Project

# People

Scott Liu - sliu125

Connor Lake - crlake2

Aashish Kapur - askapur2

# Problem

Buses are scheduled inefficiently. Traditionally buses are scheduled in 10-30 minute intervals with no regard the the actual load of people at any given stop at a given time. This results in some buses being packed, and others empty.

# Solution Overview

Introducing the _BusPlan_: A network of smart detectors that actively survey the amount of people waiting at a bus stop to determine the ideal amount of buses at any given time and location.

To technically achieve this, the device will use a wifi chip to listen for probe requests from nearby wifi-devices (we assume to be closely correlated with the number of people). It will use a radio chip to mesh network with other nearby devices at other bus stops. For power the device will use a solar cell and Li-Ion battery.

With the existing mesh network, we also are considering hosting wifi at each deployed location. This might include media, advertisements, localized wifi (restricted to bus stops), weather forecasts, and much more.

# Solution Components

## Wifi Chip

- esp8266 to wake periodically and listen for wifi probe requests.

## Radio chip

- NRF24L01 chip to connect to nearby devices and send/receive data.

## Microcontroller

- Microcontroller (Atmel atmega328) to control the RF chip and the wifi chip. It also manages the caching and sending of data. After further research we may not need this microcontroller. We will attempt to use just the ens86606 chip and if we cannot successfully use the SPI interface, we will use the atmega as a middleman.

## Power Subsystem

- Solar panel that will convert solar power to electrical power

- Power regulator chip in charge of taking the power from the solar panel and charging a small battery with it

- Small Li-Ion battery to act as a buffer for shady moments and rainy days

## Software and Server

- Backend api to receive and store data in mongodb or mysql database

- Data visualization frontend

- Machine learning predictions (using LSTM model)

# Criteria for Success

- Successfully collect an accurate measurement of number of people at bus stops

- Use data to determine optimized bus deployment schedules.

- Use data to provide useful visualizations.

# Ethics and Safety

It is important to take into consideration the privacy aspect of users when collecting unique device tokens. We will make sure to follow the existing ethics guidelines established by IEEE and ACM.

There are several potential issues that might arise under very specific conditions: High temperature and harsh environment factors may make the Li-Ion batteries explode. Rainy or moist environments may lead to short-circuiting of the device.

We plan to address all these issues upon our project proposal.

# Competitors

https://www.accuware.com/products/locate-wifi-devices/

Accuware currently has a device that helps locate wifi devices. However our devices will be tailored for bus stops and the data will be formatted in a the most productive ways from the perspective of bus companies.