AI-Influenced Condition Assessment Analyses for Toronto Trunk Sewers

Jacobs was competitively contracted by the City of Toronto to execute the condition assessment and detailed rehabilitation design and construction administration project for approximately 8 km of sanitary trunk sewers in Toronto, Ontario. These sewers, which traverse bustling urban areas, recreational zones, and environmentally sensitive lands, presented a unique challenge due to their diverse configurations and sizes. This paper delves into how artificial intelligence (AI) was harnessed as an innovative approach to support the recommended scoping of data-driven investigations and determine condition assessment recommendations for rehabilitation design and construction implementation. This approach ultimately led to a 95% reduction in cost of sewer investigations required to confidently recommend this asset management strategy. Through precise and consistent machine coding and advanced analytical asset management tools, risks were comprehensively evaluated, facilitating proactive intervention and cost-effective planning. The primary project objectives included restoring the remaining useful life (RUL) and serviceability of the sewer system while minimizing public and environmental impact, thereby leaving the client and all stakeholders satisfied.