The most significant risk this week was potential plant loss during model training or system adjustments, which could disrupt data collection. We are managing this by scaling up the system to support three plants instead of one, ensuring a larger dataset and providing backup in case any plants die. Additionally, we are mitigating this risk by setting up the sensors as quickly as possible to begin data collection early. This was the most significant change to the design.
Challenges & Mitigation:
- Conflicting sensor data: To ensure uniform readings, we placed all plants in a single large pot, allowing us to use one set of sensors and actuators for all plants.
- Limited Raspberry Pi pins: We selected multi-function sensors (e.g., a 3-in-1 soil pH, nutrient, moisture sensor, and a 2-in-1 temperature/humidity sensor) to reduce the number of connections needed.
- Increased costs: A larger greenhouse ($103.99) and increased water capacity were necessary to support three plants. To offset this, we are minimizing additional costs by reducing the number of sensors and opting for cost-effective components.
Progress:
- Finalized and ordered all system components.
- Worked on the design presentation.
- Began planning the software, including machine learning integration and the web application.
Next steps:
- Set up the Raspberry Pi 5, sensors, and camera once the components arrive.
- Finalize the data collection pipeline for ML training.
- Develop the web app framework and user interface.
We will include photos of the system setup once the components arrive.
Part A: Our automated greenhouse system enhances public health, safety, and welfare by providing an efficient, low-maintenance way to grow fresh produce, improving food security and reducing reliance on commercially farmed crops with chemical treatments. Safety is a top priority, and we are implementing physical dividers to separate water-sensitive electrical components from wet areas like the water tank, minimizing the risk of short circuits or electrical hazards. Additionally, the system automates irrigation and nutrient delivery, preventing overwatering, mold growth, and manual handling risks. With live monitoring and an intuitive control interface, the system reduces the need for constant supervision, making it safer and more accessible for users with limited mobility or time constraints. By offering an affordable and sustainable way to grow plants, our solution supports self-sufficiency and environmental sustainability while ensuring a safer, healthier growing environment.
Part B: In terms of social factors, our project is significant in that it promotes sustainable urban living by allowing easy indoor plant care. People who cannot be physically present at home to take care of the plants can take advantage of our solution. It is also especially impactful in communities that have limited access to green spaces, as people can grow their plants and form their personal gardens inside their houses. People that share the same sustainability goals regarding plant care can connect more, and educate each other with the plant information that our solution provides. Sproutly contributes to achieving more green-friendly and socially connected society.
Part C: Our goal is to create a mid-range product that balances affordability and advanced features. High-end competitors like AC Infinity ($699 for a 3 plant system) and Plant Hive ($984 for 1 plant) offer advanced sensing and automation but at a steep price. Our system provides similar capabilities at a more accessible cost of $385. This is comparable to Koru ($400), a lower-cost option that offers basic sensors and watering schedules but lacks control over external conditions. Unlike cheaper alternatives that support only one plant in an open environment, our system accommodates three or more plants in an enclosed space with real-time sensing, monitoring, camera feed, and ML-based plant health analysis. This makes our system a cost-effective alternative with premium features at a lower price point.
Part A was written by Zara, B was written by Yuna, and C was written by Jana.