What it does
For our project we are going to create an application that suggests to the user what clothes to wear given the weather conditions outside. We will use the temperature sensor to find temperature and based off this suggest what types of clothes the user should wear (so if its really hot, shorts and a t shirt, and if it’s in the 50s, jeans, a sweater and a light jacket). The light sensor will be used to tell the user if they need to wear sunglasses, a hat, or sunscreen. We will track weather trends over time, and use user feedback about whether our suggestions were appropriate to improve future recommendations.
In our project, we will be using a temperature sensor, push button, light sensors, an Arduino MKR1000, and the Blynk app downloaded through a smart phone.
Final Project Write-up
Our project is a weather application that gives recommendations as to what the user should wear that day. We chose this idea primarily because Philadelphia has been experiencing very fluctuating weather forecasts the past few weeks. One day it is 80 and sunny, the next day it is 60 and rainy, making it difficult to predict what the right outfit might be for that particular day. In terms of the timeline for our project, we were able to develop our finished product after two meetings. Because our schedules did not line up as well as we would have hoped, most of the code was written beforehand. When we did first meet, we focused on debugging the code and connecting the corresponding breadboard and Blynk app interfaces. After, our second meeting consisted of mostly refining the code and the designs for the user interface to get it ready for the final demo day. We used an MKR1000 in order to link our circuit to the Blynk app on our phones. The phone application contains two tabs, one of which is labeled “Weather” and will display the current temperature in real time. The second tab, labeled recommendations, has two text boxes, one containing a description of what to wear based on the outside temperature and the other a description of what to wear based on the light intensity that day. We were able to make our idea come to life using an MKR1000, a light sensor, and a temperature sensor. We connected our circuit to the Blynk application through code that we wrote in Arduino consisting of helper functions that take in the light intensity and the temperature as parameters and return an outfit suggestion. If we were to continue to work on this project in the future, we could improve it by making the experience more personalized to the user. We could do this by adding a feature that allows users to rate how satisfied they were with the app’s recommendation for the day.