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lab-notes.aiPublic-service AI playbooks
Opportunity 16/17InfrastructureEnvironment, land and water

Wastewater Monitoring

Explore what a wastewater monitoring feed would need to tell an operator before an unusual reading warrants investigation.

Published sources
2
Starter data
18 synthetic records
Domain build partner
build-wastewater-monitoring
Last reviewed

From the draft strategy

Opportunity

The draft strategy names AI for wastewater management as a potential public-service application, pointing at abnormal flow, contamination, and spillovers, without saying which readings it means or what would count as an incident.

Where the draft says it

Table 2 — potential public-service applications

Read the draft strategy source (opens in a new tab)

Source register

Research already done

Real published source

We reviewed these published sources so you do not have to start from zero. Each source shows what it covers, how it can be accessed, and why it matters.

2 sources

  1. Department of Agriculture, Environment and Rural Affairs

    Open

    Regulating sewage discharges

    What it covers
    How discharges from Northern Ireland's wastewater treatment works are permitted and checked, including the measures a consent sets — oxygen demand, suspended solids, ammonia, and nutrients such as phosphorus — and how samples count towards annual compliance.
    Why it matters here
    It names the measures and the sampling arithmetic this playbook's synthetic records imitate, which is why the file holds ammonia and phosphorus by site and week rather than a raw sensor trace.

    Open the source (opens in a new tab)

  2. Northern Ireland Water

    Open

    Integrated annual report and accounts

    What it covers
    The yearly account of running water and sewerage services in Northern Ireland, including performance against environmental and customer measures, the scale of the network maintained, and where the money went.
    Why it matters here
    It is the fullest public description of how the wastewater network behaves, and it shows that performance reaches the public as yearly summaries rather than the reading-by-reading feed this example would work from.

    Open the source (opens in a new tab)

Starter data

Starter dataset

Synthetic working data

Use 18 synthetic weekly readings across six works to explore unusual-reading detection without operational network data.

AI-assisted research helped identify and interpret the published sources. We then created a small, non-sensitive synthetic dataset shaped by the information those sources expose. It is for exploration—not evidence, training, or operational decisions.

Records
18
Fields
6

Field preview

table view
  • id

    SYN-WW-01 · SYN-WW-02 · SYN-WW-03

  • site

    Works A · Works B · Works C

  • week

    2025-W18 · 2025-W19 · 2025-W20

  • flowBand

    10000-20000 m3/day · over 20000 m3/day · 5000-10000 m3/day

  • ammoniaMgPerL

    1.4 · 1.9 · 3.6

  • phosphorusMgPerL

    0.8 · 0.9 · 1.5

How it was prepared

AI authored fictional flow, ammonia, and phosphorus readings, including two weeks that differ from their site's pattern.

Limitations

  • The readings are invented and the works are letters, so nothing here describes any real site, network, or discharge.
  • Weekly figures per works hide the rainfall, hydraulics, and sensor faults that decide what an unusual reading actually means.
  • Two measures cannot identify what is in the water, and a real feed also carries the gaps, drift, and maintenance events this tidy file does not.

Clone and build

Domain build partner

Build with a domain-aware coding agent

Clone the repository, then ask your coding agent to load the skill that ships with it. The skill brings the opportunity, sources, starter data, known unknowns and constraints into the conversation before anything is proposed. It follows the open Agent Skills standard, so it works in Claude Code, Codex and any other agent that reads skills.

01 / Clone

git clone https://github.com/Hypership-Software/lab-notes.ai.git

02 / Invoke

Claude Code
/build-wastewater-monitoring
Codex
$build-wastewater-monitoring

Conditions, not a checklist

Before you build

These are not footnotes. They are conditions that any responsible prototype would need to address.

  • Alert errors waste time or delay response

    A missed or noisy alert either delays a response to something happening in the environment or sends a limited crew to the wrong place.

  • Network details carry their own risk

    Published detail about where a network runs and how it behaves carries its own risk, which is why the works in this file are letters rather than places.

  • An unusual reading is not a diagnosis

    An unusual reading is not a diagnosis: it cannot say what is in the water or what should be done, and a drifting sensor looks much the same as a real event.