Project

# Title Team Members TA Documents Sponsor
22 Smart Drone Delivery Improvement
Rahul Joshi
Raymond Hoagland
Sachin Weerasooriya
Luke Wendt appendix0.docx
design_document0.pdf
final_paper0.pdf
other0.pdf
presentation0.pptx
proposal0.pdf
When you order a package that is shipped via ground, it is either left at your door or you must be present to sign off on the package. Services like Amazon PrimeAir look to speed up delivery time with drone shipping, which claims to be able to come to your door in 30 minutes. If you look at Video 2 in this link, you will see that the shipment is loaded and the drone takes off, converts to a plane, flies to the vicinity of the landing local, converts back to a drone, and lands on a marker put out by the recipient. This drone then deposits the package and returns to the factory for its next package. Here lies a major flaw; in the event that something valuable is being shipped, it would be desirable for their to be a confirmation that someone is available to pickup the package that is being delivered.



This is where we step in. The problem we want to address is we will assume that the drone is in the area of the delivery spot. We will use image processing to ID the user specified landing spot. The key difference will be: instead of landing, the drone will notify the owner that the package is ready for pickup and hover above the landing spot for a fixed amount of time. The drone will then wait for a confirmation from the user that it is safe to drop off the package. If this message isn't received after a set amount of time, the drone will return to the warehouse with the package and will try to return the package later. While the drone waits, it will constantly scan the surroundings to see if any unidentified threats are approaching the drone. If it detects a threat is too close, the drone will take off and hover at a higher elevation to protect the package contents. It will stay there until either the recipient gives the okay for delivery or until the time limit is up and the drone will return to the factory.

Hardware needed:
- A drone
- A small camera
- Digital Signal Processor (DSP) Chip
- Proportional-Integral-Derivative (PID) Controller
- Raspberry Pi
- USB wifi dongle
- Smart phone

We will use image processing to ID our landing spot and the PID controller to send the necessary feedback to the motors in order to descend the drone and lookout for potential hazards. For our prototype, will then use the raspberry pi and dongle to connect to the resident's WiFi and send a message to a smartphone app indicating the package has arrived. The drone will then wait for confirmation from the app. The mechanical mechanism to physically lower the package will be out of our scope. Rather we will have an LED or some way to indicate that the package has been dropped.

Coffee Bean Freshness Tracker (CO2ffee)

Nathan Colunga, Joshua Meier, Abrar Murtaza

Coffee Bean Freshness Tracker (CO2ffee)

Featured Project

Team Members:

- Joshua Meier (joshua51)

- Abrar Murtaza (abraram2)

- Nathan Colunga (colunga4)

# Problem

Many coffee connoisseurs care about using freshly roasted beans, as it gives you the best coffee and depth of flavor! However, when you buy coffee from a roastery, they only give you an estimated date for when you should use them (typically within a month). This means those picky with their coffee quality don’t know exactly when their beans are no longer considered “fresh”. To solve this issue, we want to make a custom coffee container that detects how fresh beans are and tells the user when they need to replace their beans. This way, the user can always make sure they are using fresh beans to get good coffee!

# Solution

For our design, we plan to create a container to track the amount of CO2 remaining in the coffee beans as this directly correlates with the freshness of coffee beans. This is based on the weight of beans that were added as well as the detected concentration of CO2 that builds up in the container over time. This would work by when the beans are first added to the container the user would add them and utilize a mobile interface to indicate new beans were entered and specify the type. The container would then detect the weight of beans that were added and the original concentration of CO2 in the container which should be approximately 420 ppm (atmospheric). Every hour from then on the container would update the current CO2 concentration and utilize that as well as the calculated volume of the container and mass of the beans when first put into the container. The system will calculate the milligram of CO2 that was released per gram of beans. Using this calculated CO2 release and comparing it to the type of beans that were added to the container which would be inputted by the user, the system will calculate the approximate percentage of CO2 remaining in the beans at any given time. For reference, we plan to utilize the data collected in this study to determine the approximate CO2 content of each type of roast: https://pubs.acs.org/doi/10.1021/acs.jafc.7b03310. It is also worth noting that we will be assuming that 100% of the CO2 is still contained in the beans upon being placed in the container. We will be assuming this because the expected use case is beans will be added almost immediately after being bought making the time since the roasting is extremely short and the escaped CO2 negligible.

# Solution Components

## Subsystem 1 - Peripheral Devices (i.e. Sensors, Inputs, and Motors)

There will be three main sensors integrated into this subsystem. The weight sensor determines the amount of beans in the container by mass which will be used to calculate the carbon dioxide released per gram. The carbon dioxide sensor which determines the ppm of the carbon dioxide in the closed container is also used in the CO2 per gram calculation. There will also be a button to open and close the container as well as a motor that will be used to rotate the lid on a hinge to open and close it. The motor will also be engaged every time the concentration builds up too much so that the CO2 sensor is not overwhelmed by the concentration of CO2 within the container. For the CO2 sensor, we will most likely be using the Infineon PASCO2V15 sensor as it supports I2C and has a fairly reasonable CO2 concentration range. The weight sensor would most likely be made up of a few load cells and connected to the microcontroller via an HX711. For the motor, we plan to utilize the Miuzei Waterproof Servo Motor because of its small design and price.

## Subsystem 2 - Microcontroller

This subsystem consists of most likely an ESP32-WROOM-32E-H4 microcontroller with wireless communication capabilities and I2C for peripheral device connections. The microcontroller will read data from the CO2 and weight sensors to perform calculations for the percentage of CO2 remaining in the coffee beans. Based on this measurement, data will be output to the mobile interface via a wireless connection module, reporting as the freshness report of the coffee beans. The push button input and motor outputs are also connected, so on each press, the microcontroller can send data to the motor to begin opening or closing the lid, alternating.

## Subsystem 3 - Wireless Connection Module and Mobile Interface

The wireless connection module is built into the ESP32 microcontroller and this will allow data communication between the mobile interface and microcontroller. On this mobile interface, there will be an input to indicate which type of coffee beans have been entered into the container. Based on this input, our system will be able to estimate the initial amount of CO2 stored in the beans. Through the mobile interface, the freshness of the beans will be reported as the approximate percentage of CO2 remaining in the beans.

## Subsystem 4 - Power System

For power, we plan to utilize a couple of rechargeable batteries along with a power controller board. The power controller board will manage the power being taken in from a USB port to recharge the batteries and also manage the output power to all sensors and the microcontroller. We will most likely utilize double A rechargeable batteries and design our own power board in this subsystem.

## Materials

Most of the body will be made using 3D-printed PLA material with the coffee itself contained in a metal bin that can be removed. To create air-tight seals on the container the lid will be fitted with silicone edges to decrease gas escaping.

# Criterion For Success

There are a few goals we will try to meet for this project:

- Able to create a wireless connection to a phone for the user interface

- Able to create a rechargeable battery system that correctly powers the rest of the system

- A reasonably accurate measure of the CO2 lost by the beans while in the container which can be cross checked with manual measurements of weight

- Have the ability to adapt the calculation to various bean roast types that are inputted by the user

Project Videos