Utilizing Artificial Intelligence to Support the City of Miami Beach SSES & Biscayne Bay Water Quality Improvement Program

Abstract

This paper presents the City of Miami Beach’s transition to an innovative approach for assessing and rehabilitating its sanitary sewer system as part of its Sanitary Sewer Evaluation Survey (SSES) requirements. Traditionally, sewer condition assessments involved lengthy processes and redundant steps, which caused delays in implementing rehabilitation measures. In response, the City adopted a program that combined Automated Defect Recognition (ADR) system powered by Artificial Intelligence (AI) to streamline condition assessments with action insights which provide real-time, evidence-based recommendations for necessary actions. The ADR system, integrated with the National Association of Sewer Service Companies (NASSCO) Pipeline Assessment Certification Program (PACP), enables rapid, consistent, and accurate defect identification from CCTV inspections. The AI-driven platform enhances decision-making by providing immediate rehabilitation recommendations and cost estimates, drastically reducing the time between assessment and implementation. Use on the Miami Beach SSES program demonstrates that this innovative approach results in significant schedule and cost savings, improved resource management, and reduced community disruption. The use of ADR also facilitates a more efficient rehabilitation process by minimizing the risk of sewer deterioration and streamlining data management. This paper concludes that adopting ADR with embedded decision-making frameworks can substantially improve sewer system management, particularly in resource-constrained environments, by enabling faster, data-driven interventions that enhance infrastructure sustainability.