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MyEcoReporter: a prototype for artificial intelligence-facilitated pollution reporting.

Weihsueh A Chiu¹, Galen Newman², Garett Sansom³

¹Department of Veterinary Physiology & Pharmacology, Texas A&M University, College Station, TX, USA. wchiu@tamu.edu.

Journal of Exposure Science & Environmental Epidemiology

|January 20, 2025

Summary

This summary is machine-generated.

Community members can now easily report pollution incidents using a new AI-powered chatbot. This tool simplifies environmental reporting by using text messages, making it easier to share concerns with authorities.

Keywords:

Artificial intelligence ChatGPT Community health Environmental justice Large language models Pollution

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Area of Science:

Environmental Science
Computer Science
Public Health

Background:

Community members often face challenges reporting environmental concerns.
Artificial Intelligence (AI) and large language models (LLMs) offer potential solutions to reduce reporting barriers.

Purpose of the Study:

To test the hypothesis that AI-powered chatbots can simplify pollution incident reporting via text messaging.
To develop and evaluate a user-friendly tool for community environmental reporting.

Main Methods:

Developed
MyEcoReporter,
an AI-powered chatbot using LLMs and text messaging (SMS).
The application was built with Python, AWS Lambda, DynamoDB, and Twilio, deployed via Serverless.
Users interact conversationally to provide incident details, bypassing traditional forms.

Main Results:

The AI chatbot architecture enabled rapid customization for diverse environmental reporting needs.
Facilitated natural language conversations for data collection.
Successfully stored structured data for formal submission to authorities.

Conclusions:

AI and LLMs can create intuitive tools for environmental reporting.
MyEcoReporter demonstrates the potential to translate community concerns into actionable data for government agencies.
This approach enhances community engagement in environmental monitoring and protection.