NYC selects eight companies to help solve water, wastewater challenges

The New York City Department of Environmental Protection (DEP) has selected eight companies to help solve challenges facing the city’s water and wastewater network as part of the Environmental Tech Lab (ETL).

The companies have been selected to collaborate with DEP to test technologies designed to enhance operational efficiency and data utilization at the nation’s largest municipal water and wastewater utility.

The ETL, launched earlier this year by DEP and Partnership Fund for New York City, leverages the global tech sector to help solve both present and future challenges facing the city’s water and wastewater network.

The ETL works with senior stakeholders across all DEP bureaus to identify their top organizational challenges. Then, the ETL facilitates accelerated, iterative tests to determine how new technologies can best address agency needs. This streamlined testing process, with distinct go/no-go decision points, fosters an understanding of which tools can best position DEP to operationally respond to the impacts of climate change and other twenty-first century challenges.

This year’s Operational Efficiency Challenge and Data Utilization Challenge garnered nearly 100 applications from over twenty countries. A team of DEP decision makers and private sector experts assessed applicants based on their technology’s potential impact, product, team, and overall value proposition.

Through this rigorous review process, eight companies were selected to deploy their technologies over an eight-week “proof of concept” period starting in October 2023. Six companies were selected from the Operational Efficiency Challenge, and two companies were selected from the Data Utilization Challenge.

Successful companies may be invited to deploy their work on a larger scale in a yearlong pilot.

The six Operational Efficiency Challenge proof of concept winners are:

• Gybe (Portland, United States) — Automatically monitors a variety of water quality parameters across entire Watersheds, Lakes, Rivers and Coastal areas, using data from satellites and non-contact hyperspectral sensors, artificial intelligence, and machine learning.
• Knaq (New York City, United States) — Uses non-invasive hardware installed on industrial equipment coupled with a software platform to provide real time data, alerting, and predictive maintenance recommendations.
• Near Space Labs (Brooklyn, United States) — Flies proprietary zero-emission robots to the stratosphere to capture, process, and deliver high-quality earth imagery to augment infrastructure resiliency initiatives.
• SENTRY (Charlottetown, Canada) — Utilizes a bio-electrode sensor platform to provide real-time, reliable wastewater quality data. These sensors accurately monitor the strength of incoming wastewater and allow operations to save costs by reducing energy and chemical use.
• SewerAI (Walnut Creek, United States) — Streamlines workflows using artificial intelligence to review CCTV videos of pipes, modelling utility maintenance holes with 3D technology, and automating data quality control (QC). This frees up talented engineers to spend less time on tedious manual tasks and more time on what matters most—prioritizing fixes and ensuring a healthy future for the community.
• VAPAR (Sydney, Australia) — Creating the fastest way to the right sewer pipe repair decision—using deep learning to find defects in sewer pipes inspection videos and standardizing follow on repair decisions.
  
  

The two Data Challenge proof of concept winners are:

• InPipe Energy (San Francisco, United States)—Has developed the HydroXS, a first-of-its-kind product line that uses micro-hydropower to create reliable renewable energy from water pipelines.
• Transcend Software Inc. (Princeton, United States)—Integrates process, mechanical, electrical, and civil engineering calculations and decisions in a cloud-based generative design software to automatically generate complete and accurate preliminary engineering designs for critical infrastructure.

The ETL is modeled after the successful Transit Tech Lab (TTL)—a collaboration between the Partnership for New York City and the Metropolitan Transportation Authority (MTA)—which enables regional transportation agencies to test new technologies that modernize public transit and improve the customer experience.

Winners from the Transit Tech Lab program have helped the regional transportation network improve subway signaling, curb management, transit accessibility, and enhance operational efficiencies. Since 2018, the TTL has fielded over 750 applicants, tested 51 technologies, and facilitated seven commercial engagements.