AEJIM: A Real-Time AI Framework for Crowdsourced, Transparent, and Ethical Environmental Hazard Detection and Reporting

Environmental journalism is vital for raising awareness of ecological crises and driving evidence-based policy, yet traditional methods falter under delays, inaccuracies, and scalability limits, especially in under-monitored regions critical to the United Nations Sustainable Development Goals. To bridge these gaps, this paper introduces the AI-Environmental Journalism Integration Model (AEJIM), an innovative framework combining real-time hazard detection, crowdsourced validation, and AI-driven reporting.

@article{tiltack2025_2503.17401,
  title={ AIJIM: A Scalable Model for Real-Time AI in Environmental Journalism },
  author={ Torsten Tiltack },
  journal={arXiv preprint arXiv:2503.17401},
  year={ 2025 }
}