Project

# Title Team Members TA Documents Sponsor
55 HydroFlora ( A Context-Aware Watering Can )
 Delilah Dzulkafli
Idris Ispandi
 Mingrui Liu photo1.png
proposal1.pdf
# Team Members:

Idris Ispandi (mm120) Delilah Dzulkafli (delilah5)

# Problem:

Many people care for multiple houseplants with different watering needs, but watering is typically done by intuition and inconsistent habits. Because plant type, pot size, soil type, and moisture all affect how much water a plant actually needs, manual watering often results in overwatering or underwatering. Overwatering can lead to root rot, fungus gnats, and wasted water, while underwatering causes plant stress, slowed growth, and wilting. Existing reminders or generic schedules don’t adapt to real-time soil conditions, and fully automated irrigation systems can be too expensive, complex, or impractical for small indoor plant collections. There is a need for a simple, low-effort tool that helps users deliver the correct amount of water per plant based on measured soil dryness and plant/pot-specific requirements, without requiring a permanent installed system.

# Solution:

In order to maintain optimal conditions for plants, we propose a smart watering can. The watering can will have two working parts: the MCU connected to a water pump (on the watering can), and the modular sensing unit (on the plants pot). The idea is that when you get a new plant, you input to the MCU the type of the plant, and the recommended amount of water the plant will be stored. The sensor unit will constantly broadcast the readings so when you pick up the watering can it will tell you which plant is in need of water based on the previous watering logs. You select the plant and go to the respective pot and press dispense and the MCU will tell the pump to dispense the needed amount of water = Recommended moisture level - current moisture level. This way, we can ensure that each plant has the most optimal amount of water needed to grow.

# Solution Components:

- ## Subsystem 1 (Water Dispensing Unit):
Components: Peristaltic Liquid Pump with Silicone Tubing

Driven by the MCU, this unit is responsible for dispensing the required amount of water. This will be placed in the watering can.
[https://www.digikey.com/en/products/detail/adafruit-industries-llc/1150/5638299](url)


- ## Subsystem 2 (Sensor Node):
Components: Capacitive Soil Moisture Sensor SKU:SEN0193, ESP32-C3-WROOM-02, battery and regulator

This unit will have a sensor that will be attached to the plant to measure the soil moisture, and the readings will be transmitted to the main control unit periodically via WiFi/Bluetooth (tradeoffs are still being weighed).
[https://www.digikey.com/en/products/detail/dfrobot/SEN0193/6588605](url)


- ## Subsystem 3 (Main Control Unit):
Components: ESP32-C3-WROOM-02, LCD display, buttons

This acts as the device's main control unit. When the user chooses a plant by clicking the buttons (pre-defined for prototype), the LCD will display what plant the user has selected. It is then responsible for determining the amount of water to be pumped out based on the readings received from the plant’s moisture sensor.

- ## Subsystem 4 (Physical Build):

Components: A watering can

The MCU will be attached at the top of the watering can with a waterproof enclosure. This will be discussed with the machine shop for further opinions.

- ## Subsystem 5 (Power Management):
Components: Rechargeable Battery for MCU and LiPo battery for sensor unit

This subsystem provides rechargeable power and stable 3.3 V for our electronics. The pump, sensor node, and the control unit will have separate power systems.


# Criterion For Success:
This project will be considered successful if the system can reliably receive soil moisture data from multiple sensor nodes (sensor readings are stable under fixed conditions), accurately determine which plant needs watering, and dispense water within 10% of the target volume while maintaining a stable operation:


- Sensor nodes have a stable, repeatable moisture value where moisture reading increases after watering and decreases over time

- Sensor nodes can successfully broadcast soil moisture readings to the main control unit.

- Accurately determine which plant needs watering based on moisture level

- Pump dispenses water within 10% of target volume

- Different plants result in different dispense volume

- Sensor node operates continuously for >24 hours on battery without recharge

- Electronics remain functional after watering

Cloud-controlled quadcopter

Anuraag Vankayala, Amrutha Vasili

Cloud-controlled quadcopter

Featured Project

Idea:

To build a GPS-assisted, cloud-controlled quadcopter, for consumer-friendly aerial photography.

Design/Build:

We will be building a quad from the frame up. The four motors will each have electronic speed controllers,to balance and handle control inputs received from an 8-bit microcontroller(AP),required for its flight. The firmware will be tweaked slightly to allow flight modes that our project specifically requires. A companion computer such as the Erle Brain will be connected to the AP and to the cloud(EC2). We will build a codebase for the flight controller to navigate the quad. This would involve sending messages as per the MAVLink spec for sUAS between the companion computer and the AP to poll sensor data , voltage information , etc. The companion computer will also talk to the cloud via a UDP port to receive requests and process them via our code. Users make requests for media capture via a phone app that talks to the cloud via an internet connection.

Why is it worth doing:

There is currently no consumer-friendly solution that provides or lets anyone capture aerial photographs of them/their family/a nearby event via a simple tap on a phone. In fact, present day off-the-shelf alternatives offer relatively expensive solutions that require owning and carrying bulky equipment such as the quads/remotes. Our idea allows for safe and responsible use of drones as our proposed solution is autonomous, has several safety features, is context aware(terrain information , no fly zones , NOTAMs , etc.) and integrates with the federal airspace seamlessly.

End Product:

Quads that are ready for the connected world and are capable to fly autonomously, from the user standpoint, and can perform maneuvers safely with a very simplistic UI for the common user. Specifically, quads which are deployed on user's demand, without the hassle of ownership.

Similar products and comparison:

Current solutions include RTF (ready to fly) quads such as the DJI Phantom and the Kickstarter project, Lily,that are heavily user-dependent or user-centric.The Phantom requires you to carry a bulky remote with multiple antennas. Moreover,the flight radius could be reduced by interference from nearby conditions.Lily requires the user to carry a tracking device on them. You can not have Lily shoot a subject that is not you. Lily can have a maximum altitude of 15 m above you and that is below the tree line,prone to crashes.

Our solution differs in several ways.Our solution intends to be location and/or event-centric. We propose that the users need not own quads and user can capture a moment with a phone.As long as any of the users are in the service area and the weather conditions are permissible, safety and knowledge of controlling the quad are all abstracted. The only question left to the user is what should be in the picture at a given time.

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