{"id":70,"date":"2025-02-08T21:42:06","date_gmt":"2025-02-08T21:42:06","guid":{"rendered":"http:\/\/course.ece.cmu.edu\/~ece500\/projects\/s25-teamb3\/?p=70"},"modified":"2025-02-10T17:09:02","modified_gmt":"2025-02-10T17:09:02","slug":"janas-status-report-for-02-08-2025","status":"publish","type":"post","link":"http:\/\/course.ece.cmu.edu\/~ece500\/projects\/s25-teamb3\/2025\/02\/08\/janas-status-report-for-02-08-2025\/","title":{"rendered":"Jana\u2019s Status Report for 02\/08\/2025"},"content":{"rendered":"

This week, I worked on the proposal presentation, including use cases, use case requirements, testing, task division, and schedule (Gantt chart). Since I was responsible for presenting, I dedicated additional time to practicing and refining the presentation.<\/span><\/p>\n

I researched existing products to build a well-informed feature set, identifying their strengths and limitations. I conducted informal surveys with friends, both plant owners and non-owners, to understand what features they would find most useful. Based on this feedback, I determined key use case requirements. Furthermore, I investigated the quantitative specifications these features should meet. For instance, I analyzed how much water capacity is required for a plant to remain self-sufficient for up to two weeks.<\/span><\/p>\n

Additionally, I worked on defining testing and verification requirements with my teammates. I researched various sensors and methods for measuring their accuracy and precision in real-world conditions. I also spent significant time structuring the project schedule. I broke down tasks and submission deadlines into manageable phases, ensuring sufficient integration time and allocating buffer periods for unexpected events such as spring break and potential unforeseen challenges before the final demo.<\/span><\/p>\n

I also began exploring suitable datasets for the machine learning application. I searched for publicly available plant sensor data and identified a Kaggle dataset that aligns well with our objectives. This dataset includes sensor data that we plan on measuring, along with ground truth labels for plant health status. Moreover, I looked into image datasets for plant health detection and found that most of them focus on leaf analysis. This insight led me to conclude that we will need to preprocess plant images using OpenCV to detect leaves before passing them into the model.<\/span><\/p>\n

We are currently on schedule.<\/span><\/p>\n

Next Week\u2019s Deliverables:<\/span><\/p>\n