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Journey to Clean Water: Embracing Safety, Alerting the Community
Following the recent LCRI finalization, the blog shares a few ways utilities can up their comms game, simplifying their job and contributing to overall public health and wellbeing.
Building Public Trust with Customer Communication Touchpoint Tracking
Utilities tackle communication challenges amid shifting regulations, seeking solutions for tracking, compliance, and engagement needs. Trinnex has a solution. Read more to explore.
Decoding LCRI: Exploring How Technology can Help with Compliance
EPA’s proposed LCRI requires 100% lead pipe replacement within 10 years, and Trinnex is up to the challenge. Read to know how Trinnex can help water utilities comply with LCRR/LCRI
Digital Master Plans for Water Utilities: A Conversation with Steve and Travis
Digital water master plans are growing in importance for water and wastewater utilities. Read and listen as Trinnex's digital experts discuss best practices.
FAQs: What is a Digital Water Platform, and How it will Shape the Future
As Trinnex brings digital water platforms to solve utilities' daily challenges, we discuss FAQs about digital water platforms — what they are, and how they will shape our future.
Artificial Intelligence or Artificially Intelligent?
In the light of EPA-mandated LCRR and EPA's conversations about AI, we explore what qualifies as being artificial intelligent as against having just the appearance of intelligence.
Does Your State Accept Predictive Modeling for Inventory Development?
Predictive modeling (including machine learning) can help with inventory development through iterative, data-driven processes. But does your state accept it? Find out in this blog.
SOC 2 compliant Digital Water Solutions are Critical, Here’s Why
The smallest of the vulnerabilities in digital platforms can be exploited. But being SOC 2® compliant is a major step towards improving your security posture.
Bootstrapping: A Key to Reliable Service Line Material Predictions in Water Systems
Explore the possibility of using predictive models, like machine learning (ML), to predict service line materials, build service line inventories, and thus comply with LCRR.
Understanding Random vs. Representative Verification Sets for Predictive Modeling
To be reliable, predictive models that estimate service line material should be built using field verification samples. But how do you ensure that the sample is representative?
Pedaling towards efficiency: Trinnex partners with IDOT to develop their Bicycle Facility Inventory System
Deployed by the Trinnex and CDM Smith teams, IDOT's BFIS will serve as a definitive source of bicycle data and guide the prioritization of future bike facility projects. Read on.
Digital Twins for Water Utilities: Myths and Realities
Explore how digital twins help water utilities proactively manage their systems. Read on as we debunk myths and feature facts on digital twins for water utilities.
Unbiasing your Service Line Material Prediction Model
It is essential for water systems to construct predictive models using unbiased representative data to harness the potential of predictive modeling as a potent tool.
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