Towards Sustainable Development: A Novel Integrated Machine Learning
  Model for Holistic Environmental Health Monitoring
Anirudh Mazumder Sarthak Engala Aditya Nallaparaju
Urbanization enables economic growth but also harms the environment through
degradation. Traditional methods of detecting environmental issues have proven
inefficient. Machine learning has emerged as a promising tool for tracking
environmental deterioration by identifying key predictive features. Recent
research focused on developing a predictive model using pollutant levels and
particulate matter as indicators of environmental state in order to outline
challenges. Machine learning was employed to identify patterns linking areas
with worse conditions. This research aims to assist governments in identifying
intervention points, improving planning and conservation efforts, and
ultimately contributing to sustainable development.