Our team developed a machine-learning algorithm based on neural networks to efficiently detect and predict defined air quality parameters using satellite remote sensing image data, with the primary motivation of helping individuals, communities, and necessary authorities to take action at their levels. Output visualization is implemented using a GUI and a mobile application.