33 Buckets Internet of Things
The issue at hand is in the small Peruvian communities, Occopata and Mayrasco. There is currently not an efficient method in place to track the amount of chlorine in the local water reservoirs, and because of this, their water is often contaminated. This is a serious concern for these communities because contaminated water can transmit many different diseases and even cause death. Currently, there is a worker who injects the chlorine into the reservoir, then measures and records the data. This process is unreliable because it allows for human error and limits the data to only a small scope of people, making it difficult to monitor.
In order to solve this problem, we are going to create an autonomous process of tracking and storing the data regarding the chlorine levels in the water reservoirs. We plan to pull the data directly from the chlorine sensor, parse the data and store it in a database, and then display the data and trends on a website so it can be viewed by anyone at any time. In previous semesters, we have completed lots of research and worked with 33 Buckets to decide what tools and frameworks we’re going to use to create both the database and the website. Moving forward, by the end of this semester we intend to have a basic and functional version of both the database and the website. “Our goal is to build a database to read and hold data provided from RedCAP software and a website to display said data. After those are built, our goal is to build an API to allow the website to display the data stored in the database as well as an API to allow the database to interact with RedCAP data.