Awards & Nominations
AttachEco has received the following awards and nominations. Way to go!
Sustaining Our Planet for Future Generations
AttachEco - Educate future generations on Climate Change, Air Pollution and Biodiversity
Summary
AttachEco is a small device that sends environmental data to a mobile app. AttachEco incorporates gas, temperature and humidity sensors and can be connected to the back of any mobile device. The AttachEco app collects sensor data from the device and displays it on a map view and graph view. As many users start using AttachEco, the map view will be populated with crowdsourced data which will inform future generations on Climate Change and Air Pollution trends. The AttachEco app also has integrated AI/ML organism detection algorithms that can be used with the mobile camera by children to learn about biodiversity. It also features NASA website data for educational purposes.
How We Addressed This Challenge
AttachEco
AttachEco is a combination of hardware and software that utilizes crowdsourced data to educate future generations on Climate Change, Air Pollution and Biodiversity.
AttachEco’s hardware component consists of a NodeMCU ESP8266 MicroController along with the MQ135 gas sensor and the DHT11 temperature and humidity sensor. We chose to use Carbon dioxide, temperature, and humidity data because these pieces of data can inform future generations on Climate Change and Air Pollution that are important environmental factors.
AttachEco’s software includes the MicroPython code and an iOS app. The MicroPython code runs on the NodeMCU and sends the data from the sensors to Firebase. The AttachEco iOS app was built using the Xcode IDE and Swift 5 programming language. The AttachEco app allows the user to create an account and register their AttachEco device. The user authentication and verification is done with Firebase and is integrated in the app. Once an AttachEco device is registered, the app collects the sensor data. The user will need to press the get data button on the iOS app and the data from the sensors will be stored in the Firebase Database.
AttachEco iOS app also incorporates the mapKit and uses this to display the AttachEco devices across the world. The purpose of this is for users, especially children to click on different AttachEco devices to see the trends of climate change as well as air pollution. As more people start using AttachEco, we will see the power of crowdsourced data and this will be a good source of data for future generations. The iOS app also uses Charts to graph the sensor data so users can visualize the data for any of the AttachEco devices across the world collected over a period of time.
We also wanted to inform future generations on the importance of Biodiversity. To inform future generations on this, we implemented a section of the AttachEco app that allows children to point the phone’s camera towards a living organism and identify it. The application utilizes Machine Learning Algorithms to detect organisms. We have used 30,000+ images to make the algorithm robust. The detection model was trained using IBM Cloud Annotations and CreateML. It can detect insects, flowers, birds and animals. This can be expanded further to include more organisms.
We hope to educate future generations on the importance of sustaining our planet by showing them data that can inform them on important environmental factors such as Climate Change, Air Pollution and Biodiversity. We hope that this app can teach kids about how important our planet is and the importance of keeping it healthy for the future generations.
How We Developed This Project
One of the greatest challenges of our times is to sustain the planet we all live in and this inspired us to pick this challenge. Informing the future generations on the importance of sustaining our planet is very important. Biodiversity loss and global environmental change, including Climate Change and Air Pollution, are the pressing issues of our time and we all need to do our share in educating future generations on the importance of these things.
Our approach was to create a user friendly device AttachEco to educate future generations on Climate Change, Air Pollution and Biodiversity.
We used the NodeMCU ESP8266 MicroController along with MQ135 gas sensor and DHT11 temperature and humidity sensor. We developed MicroPython code to read sensor data using the NodeMCU. We developed an iOS app using Xcode IDE and Swift 5. We used MapKit to draw the maps to display sensor data and Charts to graph sensor data. We also used Firebase Database to do user authentication and verification and store sensor data. We used IBM Cloud Annotations and Create-ML and used 30,000+ images to create robust machine learning models / algorithms to identify living organisms like flowers, insects, animals and birds.
We ran into some issues while accessing temperature and humidity data since the DHT11 sensor was defective and we fixed it by using another working DHT11 sensor. We also ran into some issues with using Charts to graph sensor data especially the date in swift had to be converted from String to double by formatting it first. It was a good learning experience. We had also planned to have a 3D printed enclosure for AttachEco so we could demonstrate it as an attachment to the mobile device but ran into some 3D printing issues.
We are happy that we were able to create a working AttachEco and the app is able to access sensor data. The AttachEco app is working and displaying the AttachEco data on the map as well as graph. We plan to expand on it to increase the Biodiversity section by incorporating more AI/ML models of living organisms.
How We Used Space Agency Data in This Project
The AttachEco app utilizes NASA website data to educate users on the environment and important environmental factors. NASA website data is being displayed in the AttachEco app via a web view to help educate users on sustaining our planet for future generations. We utilized a web view and two buttons so that users could switch between websites in the app. Using NASA Data made our app better because it was passing trustworthy and helpful information to the user on the environment and its importance.
Project Demo
Project Code
Data & Resources
IBM Cloud Annotations
Google's Firebase
2 NASA Websites
Kaggle Image Datasets (over 30,000 images)
CreateML (iOS Machine Learning Application)
Vision API (API for integration of ML Model's in iOS app)
Charts Cocoapod (for integration of chart views in iOS app)
Apple MapKit (for integration of map views in iOS app)
Arduino Libraries (MQ135, DHT11, FirebaseArduino, ESPWiFi)