{"id":23445,"name":"PFAS Sentinel","purpose":"A web application utilizing machine learning to predict the presence and concentration of PFAS ('forever chemicals') in water sources and soil based on geographical data, industrial activity, and historical records, providing early warning systems and remediation planning tools.","profitable":0,"date_generated":"Wednesday October 2026 13:00","reference":"project-pfas-sentinel-2026","technology_advise":["Python","Medium","PostgreSQL"],"development_time_estimation_mvp_in_hours":150,"grade":6.7,"category":"data","view_count":2,"similar_ideas":[{"id":1590,"name":"PFAS Tracker","grade":7.2,"category":null},{"id":9003,"name":"PFAS Water Quality Tracker","grade":6.9,"category":"mobile"},{"id":19682,"name":"Farmland Data Sentinel","grade":7.8,"category":"data"},{"id":18409,"name":"ForeverChem Soil Analyzer","grade":7.2,"category":"agriculture"},{"id":2031,"name":"Coastal Sentinel","grade":7.8,"category":null}],"source_headline":"Cleaning up PFAS"}