## Inspiration

In an unprecedented time of fear, isolation, and *can everyone see my screen?*, no ones life has been the same since COVID.
We saw people come together to protect others, but also those who refused to wear cloth over their noses. We’ve come up with cutting edge, wearable technology to protect ourselves against the latter, because in 2022, no one wants anyone invading their personal space.

Introducing the anti anti-masker mask, the solution to all your pandemic related worries.

## What it does

The anti anti-masker mask is a wearable defense mechanism to protect yourself from COVID-19 mandate breakers. It detects if someone within 6 feet of you is wearing a mask or not, and if they dare be mask-less in your vicinity, the shooter mechanism will fire darts at them until they leave.

Never worry about anti-maskers invading your personal space again!

## How we built it

The mask can be split into 3 main subsystems.

**The shooter/launcher**
The frame and mechanisms are entirely custom modeled and built using SolidWorks and FDM 3D Printing Technology. We also bought a NERF Gun, and the NERF launcher is powered by a small lipo battery and uses 2 brushless drone motors as flywheels.
The darts are automatically loaded into the launcher by a rack and pinion mechanism driven by a servo, and the entire launcher is controlled by an Arduino Nano which receives serial communications from the laptop.

**Sensors and Vision**
We used a single point lidar to detect whether a non mask wearer is within 6 ft of the user. For the mask detection system, we use a downloadable app to take live video stream to a web server where the processing takes place. Finally, for the vision processing, our OpenCV pipeline reads the data from the webserver.

**Code**
Other than spending 9 hours trying to install OpenCV on a raspberry pi 🤡 the software was one of the most fun parts. To program the lidar, we used an open source library that has premade methods that can return the distance from the lidar to the next closest object. By checking if the lidar is within 500 and 1500mm, we can ensure that a target that is not wearing a mask is within cough range (6ft) before punishing them.
The mask detection with OpenCV allowed us to find those public anti-maskers and then send a signal to the serial port. The Arduino then takes the signals and runs the motors to shoot the darts until the offender is gone.

## Challenges we ran into

The biggest challenge was working with the Pi Zero.
Installing OpenCV was a struggle, the camera FPS was a struggle, the lidar was a struggle, you get the point.
Because of this, we changed the project from Raspi to Arduino, but neither the Arduino Uno or the Arduino Nano ran supported dual serial communication, so we had to downgrade to a VL53L0X lidar, which supported I2C, a protocol that the nano supported. After downloading DFRobot’s VL53L0X’s lidar library, we used their sample code to gather the distance measurement which was used in the final project.

Another challenges we faced was designing the feeding mechanism for our darts, we originally wanted to use a slider crank mechanism, however it was designed to be quite compact and as a result the crank caused too much friction with the servo mount and the printed piece cracked. In our second iteration we used a rack and pinion design which significantly reduced the lateral forces and very accurately linearly actuated, this was ultimately used in our final design.

## Accomplishments that we're proud of

We have an awesome working product that's super fun to play with / terrorize your friends with. The shooter, albiet many painful hours of getting it working, worked SO WELL and the fact we adapted and ended up with robust and consistently working software was a huge W as well.

## What we learned

Install ur python libraries before the hackathon starts 😢 but also interfacing with lidars, making wearables, all that good stuff.

## What's next for Anti Anti-Masker Mask

We would want to add dart targeting and a turret to track victims.
During our prototyping process we explored running the separate flywheels at different speeds to try to curve the dart, this would have ensured more accurate shots at our 2 meter range. Ultimately we did not have time to finish this process however we would love to explore it in the future.

Improve wearablility → reduce the laptop by using something like jetson or a Pi, maybe try to reduce the dart shooter or create a more compact “punishment” device. Try to mount it all to one clothing item instead of 2.5.
## Inspiration

On a night in January 2018, at least 7 students reported symptoms of being drugged after attending a fraternity party at Stanford [link](https://abc7news.com/2957171/). Although we are only halfway into this academic year, Stanford has already issued seven campus-wide reports about possible aggravated assault/drugging. This is not just a problem within Stanford, drug-facilitated sexual assault (DFSA) is a serious problem among teens and college students nationwide. Our project is deeply motivated by this saddening situation that people around us at Stanford, and the uneasiness caused by the possibility of experiencing such crimes. This project delivers SafeCup, a sensor-embedded smart cup that warns owners if their drink has been tampered with.

## What it does

SafeCup is embedded with a simple yet highly sensitive electrical conductivity (EC) sensor which detects concentration of total dissolved solids (TDS). Using an auto-ranging resistance measurement system, designed to measure the conductivity of various liquids, the cup takes several measurements within a certain timeframe and warns the owner by pushing a notification to their phone if it senses a drastic change in the concentration of TDS. This change signifies a change in the content of the drink, which can be caused by the addition of chemicals such as drugs.

## How we built it

We used a high surface area electrodes, a set of resistors to build the EC sensor and an Arduino microprocessor to collect the data. The microprocessor then sends the data to a computer, which analyzes the measurements and performs the computation, which then notifies the owner through "pushed", an API that sends push notifications to Android or IOS devices.

## Challenges we ran into

The main challenge is getting a stable and accurate EC reading from the home-made sensor. EC is depended on the surface area and the distance between the electrodes, thus we had to designed an electrode where the distance does between the electrod does not vary due to movements. Liquids can have a large range of conductivity, from 0.005 mS/cm to 5000 mS/cm. In order to measure the conductivity at the lower range, we increased the surface area of our electrodes significantly, around 80 cm^2, while typical commercial TDS sensors are less than 0.5 cm^2. In order to measure such a large range of values, we had to design a dynamic auto-ranging system with a range of reference resistors.

Another challenge is that we are unable to make our cup look more beautiful, or normal/party-like... This is mainly because of the size of the Arduino UNO microprocessor, which is hard to disguise under the size of a normal party solo cup. This is why after several failed cup designs, we decided to make the cup simple and transparent, and focus on demonstrating the technology instead of the aesthetics.

## Accomplishments that we're proud of

We're most proud of the simplicity of the device. The device is made from commonly found items. This also means the device can be very cheap to manufacture. Typical commercial TDS measuring pen can be found for as low as $5 and this device is even simpler than a typical TDS sensor. We are also proud of the auto-ranging resistance measurement. Our cup is able to automatically calibrate to the new drink being poured in, to adjust to its level of resistance (note that different drinks have different chemical compositions and therefore has different resistance). This allows us to make our cup accommodate a wide range of different drinks. We are also proud of finding a simple solution to notify users - developing an app would have take away too much time that we could otherwise put into furthering the cup's hardware design, given a small team of just two first-time hackers.

## What we learned

We learned a lot about Arduino development, circuits, and refreshed our knowledge of Ohm's law.

## What's next for SafeCup

The prototype we've delivered for this project is definitely not a finished product that is ready to be used. We have not performed any test on whether liquids from the cup are actually consumable since the liquids had been in touch with non-food-grade metal and may undergo electrochemical transformation due to the applied potential on the liquid. Our next step would be to ensure consumer safety. TDS sensor also might not be sensitive enough alone for liquids with already high amount of TDS. Adding other simple complementary sensors can greatly increase the sensitive of the device. Other simple sensors may include dielectric constant sensor, turbidity sensor, simple UV-Vis light absorption sensor, or even making simple electrochemical mesurements. Other sensors such as water level sensor can even be used to keep track of amount of drink you have had throughout the night. We would also use a smaller footprint microprocessor, which can greatly compact the device. In addition, we would like to incorporate wireless features that would eliminate the need to wire to a computer.

## Ethical Implications For "Most Ethically Engaged Hack"

We believe that our project could mean a lot to young people facing the risk of DFSA. These people, statistically, mostly consist of college students and teenagers who surround us all the time, and are especially vulnerable to such type of crimes. We have come a long way to show that the idea of using simple TDS sensor for illegal drugging works. With future improvements in its beauty and safety, we believe it could be a viable product that improves safety of many people around us in colleges and parties.
## Inspiration

The inspiration for our project came from, first and foremost, the global situation – namely, the COVID-19 pandemic. These days, most people need to be washing their hands as quickly and as often as possible, and they need to be reminded to do so. Making sure that supplies of hand sanitizer do not run out quickly, given this increased quantity of users, is therefore of paramount importance. Thus, our idea here was born.

## What it does

This project is an amalgam of two sectors. Primarily, it functions as an ordinary automatic hand-sanitizing machine: once a user’s hands are detected in the vicinity of the machine, a small quantity of hand sanitizer lands on their hands. However, it also functions as an automatically refillable one: once a weight sensor detects that there is little hand sanitizer, a pre-inserted bottle can automatically refill the dispenser. Finally, this machine serves as a reminder machine: if someone walks past without using the dispenser, a small tone rings out, and the person is reminded to sanitize their hands.

## How we built it

This project was built in three sectors: modelling, programming, and prototyping. We first began with models in Solidworks, to ensure that the mechanical components of the prototype would work, as well as TinkerCad, to ensure that the electrical components of the prototype would not cause problems. We then moved on to programming, through TinkerCad. Finally, with the help of one team member’s 3D Printer, we printed the model and used an Arduino Uno, breadboard, and wiring to construct the rough prototype.

## Challenges we ran into

As usual, the challenges that we ran into were primarily related to the fact that we could not instantly access materials. Normally, we could simply walk to a store, or walk to a student shop, and access materials there; however, for evident reasons, that is not an option this year. Another challenge we ran into was parsing which equipment, precisely, to use: to use a basic example, we needed to make sure that not only did we use *a* transistor, but rather the *correct* transistor.

## Accomplishments that we’re proud of

We are proud that we managed to use a 3D printer for the first time, meaning that we could have a very compact project that would be relatively easy to print.

## What we learned

We made ourselves more familiar with Github, and each of its properties. With some of us having experience in only using software in a hackathon, we also learned how to run and come as far as possible in a hackathon that combined software and hardware. Finally, we further reinforced our abilities to use multiple disparate sensors to accomplish one central task.

## What’s next for this

In the future, we will attempt to make this more responsive to a user’s touch. For example, currently, our alarm rings indiscriminately whenever a person walks past. It could be possible, one day, to use a more advanced camera that relies on facial recognition to determine whether someone has already used the machine, and could therefore walk past, for the purpose of conserving resources. We could also experiment with using some sort of Bluetooth to notify a principal that sanitizer quantities are running low, and to add a new bottle to the dispenser.