Artificial Intelligence Trash Amendment Surveying

To address conditions in effectuating the 2017 California state-wide Trash Amendment, which requires all municipalities to reduce water pollution by mitigating trash from entering waterways, the team of students has partnered with Fuscoe Engineering to research and implement artificial intelligence (AI) technologies. On-land visual assessments (OVTAs) are utilized to establish the expected trash loads on streets and sidewalks to compare to the level of trash once controls are imposed. These traditional OVTAs are very timely and expensive as they consist of having two staff or consultants walk the roadways and count the amount of trash while grading sections of the streets. The research instead aims to input images captured via camera mounted on a vehicle to the the AI which will quantitatively and objectively analyze the roadways for trash load grading. The ultimate goal  is to decrease the cost and time of traditional required assessments as well as improve the quality of the analysis. A secondary goal of the project is to design a regional trash capture best management practice (BMP) that aligns with streets that are identified as typically having high loads of trash.