Project

# Title Team Members TA Documents Sponsor
72 Automatic Window/Blind Regulator
Austin Chong
Mahdi Almosa
Marco Oyarzun
Douglas Yu design_document1.pdf
final_paper1.pdf
presentation1.pptx
proposal1.pdf
proposal2.pdf
Automatic Window/Blind Regulator

Team Members:
- aichong2
- oyarzun2
- malmosa2


# Problem

Waking up in the morning could pose a difficult challenge, especially when the temperature is too hot/cold or there isn't enough natural light in the room. In order for most people to fall asleep, the thermostat mostly takes care of the regulating temperature and they keep the blinds shut, however, some people prefer natural air and lighting in their homes instead. This could be an annoyance when the windows and blinds need to be changed manually.


# Solution

Our solution is to make a fully automated window/blind regulating system that opens the window and blinds according to different environment conditions. The solution to wanted air could be an automated device that opens and closes the windows at the correct temperatures and interior air quality levels. There would also be an additional security component that uses an outside-facing camera that tells the system to close the window if a security threat is detected or if the weather is poor (rain/snow). Also, if the air quality is low (smoke/pollution), the window would close in accordance with that. Conversely, if the air quality is poor inside then the window would open to allow fresh air to enter. Air quality and weather conditions would be updated in real time via the internet. According to the reading of the thermostat, the windows could be opened/closed in order to have a good temperature regulation in the room. Additionally, the blinds could open at sunrise and close at sunset or do both as custom times.


# Solution Components

## Subsystem 1

# Power supply system
The system will need varying levels of voltage, so either a wall outlet or battery can provide power that is then converted to DC to power the digital components.

# Opening mechanism
The system will need servos to open the window and blinds. This subsystem will receive signals from the microcontroller unit to determine when and how much to open the window or blinds.

# Control unit
This is where the microcontroller will operate. It will take input data from the temperature, air quality, and weather conditions (as well as current time) and move the servos accordingly.


# Criterion For Success

The first goal for this project would be to be able to open/close certain windows and blinds. There are a variety of windows that have different manual functions, some having a pulling system where others have to pull and lock. This would be the first challenge and most likely the most difficult milestone.

The next goal would be to connect the window regulator to a thermostat, to the internet, and to temperature and air quality sensors, in order to detect when to open/close the windows appropriately.

Another goal would be to have the blinds open or close at specific times, mainly before and after dark.

Smart Glasses for the Blind

Siraj Khogeer, Abdul Maaieh, Ahmed Nahas

Smart Glasses for the Blind

Featured Project

# Team Members

- Ahmed Nahas (anahas2)

- Siraj Khogeer (khogeer2)

- Abdulrahman Maaieh (amaaieh2)

# Problem:

The underlying motive behind this project is the heart-wrenching fact that, with all the developments in science and technology, the visually impaired have been left with nothing but a simple white cane; a stick among today’s scientific novelties. Our overarching goal is to create a wearable assistive device for the visually impaired by giving them an alternative way of “seeing” through sound. The idea revolves around glasses/headset that allow the user to walk independently by detecting obstacles and notifying the user, creating a sense of vision through spatial awareness.

# Solution:

Our objective is to create smart glasses/headset that allow the visually impaired to ‘see’ through sound. The general idea is to map the user’s surroundings through depth maps and a normal camera, then map both to audio that allows the user to perceive their surroundings.

We’ll use two low-power I2C ToF imagers to build a depth map of the user’s surroundings, as well as an SPI camera for ML features such as object recognition. These cameras/imagers will be connected to our ESP32-S3 WROOM, which downsamples some of the input and offloads them to our phone app/webpage for heavier processing (for object recognition, as well as for the depth-map to sound algorithm, which will be quite complex and builds on research papers we’ve found).

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# Subsystems:

## Subsystem 1: Microcontroller Unit

We will use an ESP as an MCU, mainly for its WIFI capabilities as well as its sufficient processing power, suitable for us to connect

- ESP32-S3 WROOM : https://www.digikey.com/en/products/detail/espressif-systems/ESP32-S3-WROOM-1-N8/15200089

## Subsystem 2: Tof Depth Imagers/Cameras Subsystem

This subsystem is the main sensor subsystem for getting the depth map data. This data will be transformed into audio signals to allow a visually impaired person to perceive obstacles around them.

There will be two Tof sensors to provide a wide FOV which will be connected to the ESP-32 MCU through two I2C connections. Each sensor provides a 8x8 pixel array at a 63 degree FOV.

- x2 SparkFun Qwiic Mini ToF Imager - VL53L5CX: https://www.sparkfun.com/products/19013

## Subsystem 3: SPI Camera Subsystem

This subsystem will allow us to capture a colored image of the user’s surroundings. A captured image will allow us to implement egocentric computer vision, processed on the app. We will implement one ML feature as a baseline for this project (one of: scene description, object recognition, etc). This will only be given as feedback to the user once prompted by a button on the PCB: when the user clicks the button on the glasses/headset, they will hear a description of their surroundings (hence, we don’t need real time object recognition, as opposed to a higher frame rate for the depth maps which do need lower latency. So as low as 1fps is what we need). This is exciting as having such an input will allow for other ML features/integrations that can be scaled drastically beyond this course.

- x1 Mega 3MP SPI Camera Module: https://www.arducam.com/product/presale-mega-3mp-color-rolling-shutter-camera-module-with-solid-camera-case-for-any-microcontroller/

## Subsystem 4: Stereo Audio Circuit

This subsystem is in charge of converting the digital audio from the ESP-32 and APP into stereo output to be used with earphones or speakers. This included digital to audio conversion and voltage clamping/regulation. Potentially add an adjustable audio option through a potentiometer.

- DAC Circuit

- 2*Op-Amp for Stereo Output, TLC27L1ACP:https://www.ti.com/product/TLC27L1A/part-details/TLC27L1ACP

- SJ1-3554NG (AUX)

- Connection to speakers/earphones https://www.digikey.com/en/products/detail/cui-devices/SJ1-3554NG/738709

- Bone conduction Transducer (optional, to be tested)

- Will allow for a bone conduction audio output, easily integrated around the ear in place of earphones, to be tested for effectiveness. Replaced with earphones otherwise. https://www.adafruit.com/product/1674

## Subsystem 5: App Subsystem

- React Native App/webpage, connects directly to ESP

- Does the heavy processing for the spatial awareness algorithm as well as object recognition or scene description algorithms (using libraries such as yolo, opencv, tflite)

- Sends audio output back to ESP to be outputted to stereo audio circuit

## Subsystem 6: Battery and Power Management

This subsystem is in charge of Power delivery, voltage regulation, and battery management to the rest of the circuit and devices. Takes in the unregulated battery voltage and steps up or down according to each components needs

- Main Power Supply

- Lithium Ion Battery Pack

- Voltage Regulators

- Linear, Buck, Boost regulators for the MCU, Sensors, and DAC

- Enclosure and Routing

- Plastic enclosure for the battery pack

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# Criterion for Success

**Obstacle Detection:**

- Be able to identify the difference between an obstacle that is 1 meter away vs an obstacle that is 3 meters away.

- Be able to differentiate between obstacles on the right vs the left side of the user

- Be able to perceive an object moving from left to right or right to left in front of the user

**MCU:**

- Offload data from sensor subsystems onto application through a wifi connection.

- Control and receive data from sensors (ToF imagers and SPI camera) using SPI and I2C

- Receive audio from application and pass onto DAC for stereo out.

**App/Webpage:**

- Successfully connects to ESP through WIFI or BLE

- Processes data (ML and depth map algorithms)

- Process image using ML for object recognition

- Transforms depth map into spatial audio

- Sends audio back to ESP for audio output

**Audio:**

- Have working stereo output on the PCB for use in wired earphones or built in speakers

- Have bluetooth working on the app if a user wants to use wireless audio

- Potentially add hardware volume control

**Power:**

- Be able to operate the device using battery power. Safe voltage levels and regulation are needed.

- 5.5V Max

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