What we learned from this project
This project is very different from those data analytic projects we conducted before. In the past, all the data we used for analyzing came from internet source like bank, company website, or Kaggle. While in this IoT project, we collected data on our own and made a deep insight into it.
These physical data are ubiquitous around our daily life, its attributes like dust concentration and temperature deeply affect the quality of our lives. After fining this project, we just felt like we kind of realizing more about the environment we stayed everyday. Even though we are still too weak to effectively improve air quality, we believe in the future, it is possible to apply the same techniques we acquired from this IoT project in other fields and make a change for the world
These physical data are ubiquitous around our daily life, its attributes like dust concentration and temperature deeply affect the quality of our lives. After fining this project, we just felt like we kind of realizing more about the environment we stayed everyday. Even though we are still too weak to effectively improve air quality, we believe in the future, it is possible to apply the same techniques we acquired from this IoT project in other fields and make a change for the world
Difficulties we met :
The very first problem is that our team is short-handed, we only got two members so the workload was kind of heavy. Besides, the part we spent the most time on are choosing an effective machine learning algorithm and the visualization of data. It is because the machine learning analysis itself is not easy to practice, as for data visualization, both of us didn't know much about it before, so it took us a lot of hard work to realize it. If we could have another member, I think it would be easier for us, even though we really learned a lot from this project.