# Title Team Members TA Documents Sponsor
56 Smart AC Units
Kevin Zhang
Vineeth Kalister
Xavier Oliva
Douglas Yu design_document1.docx

Kevin Zhang - kevinhz2
Vineeth Kalister - vkalis2
Xavier Oliva - xoliva2

# **PROBLEM:**
In the United States, about a third of homes lack a central air conditioning system. While some homes are in climates where they do not need an air conditioning solution, the vast majority of other homes rely on window units for their air conditioning. This is especially true in communities with older homes, such as New York City and Boston. Many older homes use “dumb” wall-mounted AC units that are inefficient and manually set. We want to target these homes and make them more efficient through “smart” AC control units. Although there exist “smart” wall-mounted units, these are often equipped with proprietary solutions that work with few systems, or are expensive devices to modulate the voltage going inside the AC unit without changing the settings of the unit. With our Smart AC Unit system, we believe that we can accomplish a more efficient and equitable experience for those with window unit ACs and ensure optimal ease of access as well as a lower power bill. As the central air conditioning market advances in the technology available to make the air conditioning experience easier, such advances and improvements are lacking in homes that do not have central air conditioning. While there are systems in the market that allow you to have your central air conditioning system interact with voice assistants or other AI services, window unit users are stuck with simple knobs and switches. The few smart devices that do interface with window units are typically proprietary designs that work with specific higher priced designs or are devices that simply modulate voltage going into the AC system.

Our proposal is a multi-part system combining temperature sensors, servo motors, and central control units to allow for wall-mount ACs to be automatically controlled through an application on one’s smart device. The device will be able to latch on top of the knobs of a window unit AC and, with the help of the User Application available on their mobile device, be able to adjust the knobs remotely to the settings of the user’s choosing.
The main system relies on sensor units, control units, and mobile devices. The prototype device will be tested on a 5000 BTU Arctic King window air conditioner.

Air Conditioner System (Smart AC device)
## Power Unit
The Smart AC itself will need to be powered with enough voltage to be able to power the two motors responsible for turning the knobs on an 5,000 BTU Arctic King window air conditioner as well the temperature and air quality sensors.

## Sensor Unit

The Smart AC device will be equipped with a temperature sensor in order to read the temperature of the room, and thus, regulate the temperature to the temperature selected by the User Application. The Smart AC device will also be equipped with an air quality sensor which enables the air quality of the room to be read and communicated to the user through the User Application.

## Control Unit

The control unit of the Smart AC device system will be capable of changing the settings of both the temperature and cooling knobs of the Arctic King window air conditioner. If the temperature set by the User Application is higher or lower than that measured by the Sensor Unit, the Control Unit is responsible for adjusting the air conditioner settings to ensure that the room temperature stays constant.

** Mobile Device System (User Application)**
## UI Unit
The user applications contain all the necessary features to read the current room temperature, turn on/off the AC system, change and schedule temperatures, change fan speeds, etc.
## Control Unit
The user application will be able to communicate with the Smart AC device via bluetooth and/or Wi-Fi.

- The AC Unit can be controlled and changed
- The sensor unit can accurately read the current room temperature
- Mobile Devices able to communicate with the AC System
- Change AC temperature whenever and wherever via one’s smart device
- Automatically set time ranges for AC use to increase the efficiency of the unit

Decentralized Systems for Ground & Arial Vehicles (DSGAV)

Mingda Ma, Alvin Sun, Jialiang Zhang

Featured Project

# Team Members

* Yixiao Sun (yixiaos3)

* Mingda Ma (mingdam2)

* Jialiang Zhang (jz23)

# Problem Statement

Autonomous delivery over drone networks has become one of the new trends which can save a tremendous amount of labor. However, it is very difficult to scale things up due to the inefficiency of multi-rotors collaboration especially when they are carrying payload. In order to actually have it deployed in big cities, we could take advantage of the large ground vehicle network which already exists with rideshare companies like Uber and Lyft. The roof of an automobile has plenty of spaces to hold regular size packages with magnets, and the drone network can then optimize for flight time and efficiency while factoring in ground vehicle plans. While dramatically increasing delivery coverage and efficiency, such strategy raises a challenging problem of drone docking onto moving ground vehicles.

# Solution

We aim at tackling a particular component of this project given the scope and time limitation. We will implement a decentralized multi-agent control system that involves synchronizing a ground vehicle and a drone when in close proximity. Assumptions such as knowledge of vehicle states will be made, as this project is aiming towards a proof of concepts of a core challenge to this project. However, as we progress, we aim at lifting as many of those assumptions as possible. The infrastructure of the lab, drone and ground vehicle will be provided by our kind sponsor Professor Naira Hovakimyan. When the drone approaches the target and starts to have visuals on the ground vehicle, it will automatically send a docking request through an RF module. The RF receiver on the vehicle will then automatically turn on its assistant devices such as specific LED light patterns which aids motion synchronization between ground and areo vehicles. The ground vehicle will also periodically send out locally planned paths to the drone for it to predict the ground vehicle’s trajectory a couple of seconds into the future. This prediction can help the drone to stay within close proximity to the ground vehicle by optimizing with a reference trajectory.

### The hardware components include:

Provided by Research Platforms

* A drone

* A ground vehicle

* A camera

Developed by our team

* An LED based docking indicator

* RF communication modules (xbee)

* Onboard compute and communication microprocessor (STM32F4)

* Standalone power source for RF module and processor

# Required Circuit Design

We will integrate the power source, RF communication module and the LED tracking assistant together with our microcontroller within our PCB. The circuit will also automatically trigger the tracking assistant to facilitate its further operations. This special circuit is designed particularly to demonstrate the ability for the drone to precisely track and dock onto the ground vehicle.

# Criterion for Success -- Stages

1. When the ground vehicle is moving slowly in a straight line, the drone can autonomously take off from an arbitrary location and end up following it within close proximity.

2. Drones remains in close proximity when the ground vehicle is slowly turning (or navigating arbitrarily in slow speed)

3. Drone can dock autonomously onto the ground vehicle that is moving slowly in straight line

4. Drone can dock autonomously onto the ground vehicle that is slowly turning

5. Increase the speed of the ground vehicle and successfully perform tracking and / or docking

6. Drone can pick up packages while flying synchronously to the ground vehicle

We consider project completion on stage 3. The stages after that are considered advanced features depending on actual progress.

Project Videos