Go Green Initiative (GGI) Intern Hiya Shah has won the 2020 Congressional App Challenge (CAC) for California’s fifteenth congressional district.
Hiya created Maji, an app that calculates water quality.
Hiya told the CAC, “[Maji is] a mobile application that harnesses the power of deep learning to computationally determine real-time water quality, and provide personalized suggestions to people residing in the United States.” Hiya told us that “the app uses both a smartphone picture of the water and field testing data to calculate a real-time water quality estimate and to provide filtration options.”
To determine their area’s water quality, users simply take a photo of a water sample, and Maji does the rest.
- First, Maji classifies the sample as high, medium, or low contamination
- Next, Maji determines the closest water testing site to the sample and considers data from the site, such as pH, fluoride, and chlorine levels.
- Finally, Maji cross-checks this information with city and county water data.
Hiya created Maji using the programming language Swift, which she had experience using in her computer science class at Amador Valley High School.
Hiya entered the CAC to spread awareness about water contamination and make water quality information more accessible.
“I joined this contest because I’m really passionate about community education,” Hiya said. “I wanted to make water quality more accessible and I thought this contest could be the perfect way to do so.” In her CAC video, Hiya explains that “according to the WHO, over 3.4 million people die due to water contamination diseases, making it globally the leading cause of death.” She adds that although chemical kits can test for bacteria in water, they are expensive and infrequently used. “Having worked with water conservation at [the Go Green Initiative] and been alerted to this issue, I decided to build Maji.”
Last summer’s water-focused GGI internship inspired Hiya to create her app.
GGI’s 2020 summer internship for Pleasanton students focused on water usage and conservation efforts. “Researching water contamination and the need for water conservation at the Go Green Initiative inspired me to combine my concern for the environment with my interest in technology,” Hiya said. “I am grateful to Mrs. Jill Buck for supporting and encouraging me throughout the process.”
In the future, Hiya plans to expand Maji to include data outside of Pleasanton.
As Maji expands its scope, it could become the future of water quality calculation. “Maji’s novel ability to determine real-time water quality using machine learning methods and providing personalized suggestions to [users]… is efficient and low cost,” Hiya explains in her video. “It makes water quality data and education more accessible without [the] need for expensive equipment like water loggers, potentially saving millions of lives from water contamination diseases.” Hiya’s long term goal for Maji is “to make updated water quality information more accessible to people anywhere, anytime.”