## Inspiration

Kabeer and I (Simran!) care deeply about impact, and building cool sh\*t.

He has a background in IoT and my background is in computational bio/health technologies. When thinking about what we want to create during HTN, we decided it would be most fun to find an intersection between hardware and healthcare.

We perceive up to 80% of all impressions by means of our sight, but there are 43 million people living with blindness and 295 million people living with moderate-to-severe visual impairment. O ur team wanted to build a product that could assist blind people in navigating their world with the most ease possible. Building a tool that could scan and alert the person of their surroundings was most important to us. Thus project ABEL began.

## What it does

When there is an object within 50 cm of the cane, the buzzer buzzes, alerting the user of obstacles in the way of their movement.

## How we built it

We connected the arduino to ultrasonic sensors which measure the distance to an object by measuring the time between the emission and reception. Once the arduino and ultrasonic sensors were connected, we coded it so that if the distance in cm is < 50cm, a buzzer would ring, alerting the person that there is a object nearby.

## Challenges we ran into

Time was the biggest time constraint that we had this entire weekend. The matter of a couple hours could've changed our entire next steps only if we had access to the right hardware (wifi modules!) and time to practice and run our software.

## Accomplishments that we're proud of

We are proud of ourselves for learning to use Arduino and hardware involved with it, in a short amount of time. We tought ourselves to run the IDE and worked through many small examples before we dove into our main idea.

## What we learned

Kabeer has worked with hardware, IoT and software for a couple projects in the past, but the entire hackathon this weekend was an incredible learning experience for the both of us. From using arduinos, breadboards, learning to use the mini arduino with wifi (the particle photon), hard coding our solution to failing multiple times and getting to know more on how wiring works between breadboards, this entire weekend was an amzing learning experience and we are both glad to spend time together and work on something that we were both interested in, but also was the middle of our interests

## What's next for ABEL

As we brainstormed multiple ideas days before the actual hackathon, our final idea was to take two that make sense and put them together; so in this case, it would be fall detection linked directly to an SMS/email integration to let an emergency contact of the victim know that they have fallen.
## Inspiration

Ecoleafy was inspired by the desire to create a sustainable and energy-efficient future. With the increasing need for smart homes, the team saw an opportunity to build a system that could help households reduce and be more aware of their carbon footprint and save on energy costs. The members of our team, being all in Computer Engineering and wanting to specialize in the Hardware field, we were particularly motivated to take on this challenge.

## What it does

Ecoleafy is a comprehensive IOT ecosystem that includes smart nodes for each room in the house. These nodes contain sensors such as presence sensors, humidity sensors, and temperature sensors, as well as switches and relays to control various devices such as the AC, heater, lights, and more. The system connects to a central back-end server that manages each nodes. This back-end server can automatically take decisions such as shutting off the lights, or the heater if no activity was recorded in the room for more than 30 minutes for example.

## How we built it

We built Ecoleafy as a comprehensive IOT ecosystem that includes smart nodes for each room in the house, connected to a central back-end server using Java, Spring, WebSockets, and MongoDB. The frontend was built using Flutter and Dart, providing a seamless user experience for web, mobile or desktop. The hardware nodes, which include presence sensors, humidity sensors, temperature sensors, switches, and relays, were developed using ESP32 microcontrollers and coded in C++. We aimed to beat the price of a Google Learning Nest Thermostat (329$ CAD) and its non-learning version (179$ CAD). Our final price per node is estimated to be at 11.60$ CAD before adding an enclosure (which could be 3D printed). This includes the MCU (ESP32), LCD screen, 4 relays, presence/motion, temperature and humidity sensors. You also need one Hub to host the server which could use a raspberry pi (45$ CAD) and the alternative would be a cloud subscription service.

## Challenges we ran into

One of the biggest challenges we faced was ensuring that the system would be plug-n-play if you wanted to add new nodes to your network. The other biggest challenge was the front-end development since most of us had no front-end dev experience prior to this project. We also had to ensure that the system was scalable and could handle a large number of connected devices.

## Accomplishments that we're proud of

We are proud of this being our first Hackaton devpost. The seamless integration of hardware and software components is another achievement that we're proud of.

## What we learned

We learned that building an IOT ecosystem is a complex and challenging process, but with the right team, it is possible to create a functional and innovative system. We also gained valuable experience in developing secure and scalable systems, as well as in using various technologies such as Java, Spring, Flutter, and C++. We also now understand the importance of having a front-end developer.

## What's next for Ecoleafy

We will be seeking ways to improve Ecoleafy and make it even more effective in reducing energy consumption. In the future, we could plan to expand the system to include new features and functionalities, such as integration with other smart home devices and **machine learning algorithms for more efficient energy management**. We are also exploring ways to make Ecoleafy more accessible to a wider audience with its low cost of entry.
## Inspiration

Retinal degeneration affects 1 in 3000 people, slowly robbing them of vision over the course of their mid-life. The need to adjust to life without vision, often after decades of relying on it for daily life, presents a unique challenge to individuals facing genetic disease or ocular injury, one which our teammate saw firsthand in his family, and inspired our group to work on a modular, affordable solution. Current technologies which provide similar proximity awareness often cost many thousands of dollars, and require a niche replacement in the user's environment; (shoes with active proximity sensing similar to our system often cost $3-4k for a single pair of shoes). Instead, our group has worked to create a versatile module which can be attached to any shoe, walker, or wheelchair, to provide situational awareness to the thousands of people adjusting to their loss of vision.

## What it does (Higher quality demo on google drive link!: <https://drive.google.com/file/d/1o2mxJXDgxnnhsT8eL4pCnbk_yFVVWiNM/view?usp=share_link> )

The module is constantly pinging its surroundings through a combination of IR and ultrasonic sensors. These are readily visible on the prototype, with the ultrasound device looking forward, and the IR sensor looking to the outward flank. These readings are referenced, alongside measurements from an Inertial Measurement Unit (IMU), to tell when the user is nearing an obstacle. The combination of sensors allows detection of a wide gamut of materials, including those of room walls, furniture, and people. The device is powered by a 7.4v LiPo cell, which displays a charging port on the front of the module. The device has a three hour battery life, but with more compact PCB-based electronics, it could easily be doubled. While the primary use case is envisioned to be clipped onto the top surface of a shoe, the device, roughly the size of a wallet, can be attached to a wide range of mobility devices.

The internal logic uses IMU data to determine when the shoe is on the bottom of a step 'cycle', and touching the ground. The Arduino Nano MCU polls the IMU's gyroscope to check that the shoe's angular speed is close to zero, and that the module is not accelerating significantly. After the MCU has established that the shoe is on the ground, it will then compare ultrasonic and IR proximity sensor readings to see if an obstacle is within a configurable range (in our case, 75cm front, 10cm side).

If the shoe detects an obstacle, it will activate a pager motor which vibrates the wearer's shoe (or other device). The pager motor will continue vibrating until the wearer takes a step which encounters no obstacles, thus acting as a toggle flip-flop.

An RGB LED is added for our debugging of the prototype:
RED - Shoe is moving - In the middle of a step
GREEN - Shoe is at bottom of step and sees an obstacle
BLUE - Shoe is at bottom of step and sees no obstacles

While our group's concept is to package these electronics into a sleek, clip-on plastic case, for now the electronics have simply been folded into a wearable form factor for demonstration.

## How we built it

Our group used an Arduino Nano, batteries, voltage regulators, and proximity sensors from the venue, and supplied our own IMU, kapton tape, and zip ties. (yay zip ties!)

I2C code for basic communication and calibration was taken from a user's guide of the IMU sensor. Code used for logic, sensor polling, and all other functions of the shoe was custom.
All electronics were custom.

Testing was done on the circuits by first assembling the Arduino Microcontroller Unit (MCU) and sensors on a breadboard, powered by laptop. We used this setup to test our code and fine tune our sensors, so that the module would behave how we wanted. We tested and wrote the code for the ultrasonic sensor, the IR sensor, and the gyro separately, before integrating as a system.

Next, we assembled a second breadboard with LiPo cells and a 5v regulator. The two 3.7v cells are wired in series to produce a single 7.4v 2S battery, which is then regulated back down to 5v by an LM7805 regulator chip. One by one, we switched all the MCU/sensor components off of laptop power, and onto our power supply unit. Unfortunately, this took a few tries, and resulted in a lot of debugging.

. After a circuit was finalized, we moved all of the breadboard circuitry to harnessing only, then folded the harnessing and PCB components into a wearable shape for the user.

## Challenges we ran into

The largest challenge we ran into was designing the power supply circuitry, as the combined load of the sensor DAQ package exceeds amp limits on the MCU. This took a few tries (and smoked components) to get right. The rest of the build went fairly smoothly, with the other main pain points being the calibration and stabilization of the IMU readings (this simply necessitated more trials) and the complex folding of the harnessing, which took many hours to arrange into its final shape.

## Accomplishments that we're proud of

We're proud to find a good solution to balance the sensibility of the sensors. We're also proud of integrating all the parts together, supplying them with appropriate power, and assembling the final product as small as possible all in one day.

## What we learned

Power was the largest challenge, both in terms of the electrical engineering, and the product design- ensuring that enough power can be supplied for long enough, while not compromising on the wearability of the product, as it is designed to be a versatile solution for many different shoes. Currently the design has a 3 hour battery life, and is easily rechargeable through a pair of front ports. The challenges with the power system really taught us firsthand how picking the right power source for a product can determine its usability. We were also forced to consider hard questions about our product, such as if there was really a need for such a solution, and what kind of form factor would be needed for a real impact to be made. Likely the biggest thing we learned from our hackathon project was the importance of the end user, and of the impact that engineering decisions have on the daily life of people who use your solution. For example, one of our primary goals was making our solution modular and affordable. Solutions in this space already exist, but their high price and uni-functional design mean that they are unable to have the impact they could. Our modular design hopes to allow for greater flexibility, acting as a more general tool for situational awareness.

## What's next for Smart Shoe Module

Our original idea was to use a combination of miniaturized LiDAR and ultrasound, so our next steps would likely involve the integration of these higher quality sensors, as well as a switch to custom PCBs, allowing for a much more compact sensing package, which could better fit into the sleek, usable clip on design our group envisions.

Additional features might include the use of different vibration modes to signal directional obstacles and paths, and indeed expanding our group's concept of modular assistive devices to other solution types.

We would also look forward to making a more professional demo video
Current example clip of the prototype module taking measurements:(<https://youtube.com/shorts/ECUF5daD5pU?feature=share>)