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🔧 Sensor Side

Factors affecting data reliability and accuracy that originate at the sensor itself — selection, installation, damage, and configuration. See the 📘 Monitoring Tools Reference for details on each tool referenced below, and the 🧩 Diagnostic Funnel for the general triage flow.

Selection of right sensor​

Wrong sensor choice for the application (e.g. wrong range, type, or accuracy class for the meter type) leads to systematically unreliable readings.

How to verify:

  1. Check the unit's meter type/spec in the admin app against the site's flow/level requirements.
  2. Check 🚨 Data Integrity Alerts history for recurring no_flow or out-of-range readings since installation — a pattern from day one (rather than starting later) points to a sensor selection mismatch rather than damage.
Status: partial

Verification process defined; standardized sensor selection guidelines are not yet documented.

Follow the right installation practices​

Incorrect installation (orientation, placement, mounting) causes inaccurate or unstable readings even when the sensor itself is healthy.

How to verify:

  1. Check 🚨 Data Integrity Alerts for no_flow or no_level_variation shortly after a known install date — check 📝 User Logs (unit level) for the install timestamp.
  2. Compare readings against a manual/reference measurement on-site to confirm a physical installation issue versus a data pipeline issue.
Status: partial

Verification process defined; a documented installation checklist is not yet in place.

Sensor gets damaged and stops measuring in between​

How to verify:

  1. Check the 🌐 Offline Dashboard — a damaged sensor typically shows as offline or stalled.
  2. Check 📈 Uptime Metrics for the device to confirm when it stopped sending data and whether uptime dropped to 0% from a specific point (versus intermittent).
  3. Check 🚨 Data Integrity Alerts for a device_status alert (no data received from the meter).
Mitigation in place
  • 📈 Uptime Metrics
  • 🚨 Data Integrity Alerts (device_status)
  • 🌐 Offline Dashboard alerting

Junk values posted from the sensor get introduced into the database​

How to verify:

  1. Check 🚨 Data Integrity Alerts — junk values that fall outside configured bounds should be caught by the min/max range check for that unit.
  2. If a junk value made it into the database anyway, check the unit's configured min/max range in the admin app to confirm it's actually set for that meter type.
Mitigation in place

Max and min values are set for applicable units to reject/flag out-of-range values before they're treated as valid data.

Flow meter starts counting false water flow without actual flow​

How to verify:

  1. Check 🚨 Data Integrity Alerts for water_balance_leakage — a false-flow meter will typically create an unaccounted water discrepancy across the zone balance.
  2. Cross-check the flow reading against 📶 IoT Telemetry live values and, if possible, a physical/manual check of actual flow at the meter.
  3. Check 📝 User Logs (unit level) for any recent replacement/service that could have disturbed the meter (e.g. debris, vibration, incorrect flow factor).
Status: partial

Verification process defined via water_balance_leakage alert; no dedicated false-flow detection yet.

Data outside the permissible range enters and affects system performance​

How to verify:

  1. Check 🚨 Data Integrity Alerts for the affected unit to see whether the out-of-range reading was flagged.
  2. Confirm the unit's min/max configuration in the admin app matches the expected range for its meter type.
Mitigation in place

Max and min values are set for applicable units. This can also be applied by meter type with default values across all units of that type, but requires meter configs to be defined per type first.

Reverse flow conditions come and data does not register in the dashboard​

How to verify:

  1. Check 📶 IoT Telemetry — data is arriving from the device, but the dashboard doesn't reflect it, which is the signature of a reverse-flow condition.
  2. Check 🗄️ Data Validation for the unit — look at the recent raw data received into the database and confirm the reverse flow flag is set on those records.
  3. Check the daily reverse-flow alert in Google Chat for the unit.
Mitigation in place

A daily alert for reverse-flow conditions is enabled in Google Chat. The reverse flow flag can also be confirmed directly in Data Validation. On confirmation, resolve it from the 🔄 Unit Reset tab.

Improper re-configuration during replacement/service activities​

How to verify:

  1. Check 📝 User Logs (unit level) for the most recent replacement/service entry and the configs applied.
  2. Check 🚨 Data Integrity Alerts for anomalies starting immediately after that service timestamp.
  3. Validate the new configuration (flow factor, meter type, min/max range, device ID) against the correct values for that unit.
Mitigation in place
  • Log the service/replacement activity in the admin app and reset the unit via the 🔄 Unit Reset tab.
  • Validate that new configs — flow factor and all other parameters — are set correctly before closing out the activity.

Communication cable gets damaged​

How to verify:

  1. Check 🚨 Data Integrity Alerts for a device_status alert (no data received) — a damaged communication cable (e.g. RS485) typically presents this way even if the device itself has power.
  2. Check 📶 IoT Telemetry to see if the device is attempting to connect at all (power present) versus fully silent (power also lost).
Mitigation in place

🚨 Data Integrity Alerts (device_status)

Power supply failure and stops measuring​

How to verify:

  1. Check the 🌐 Offline Dashboard to confirm the device is offline.
  2. Check 📈 Uptime Metrics for a hard drop to 0% starting at a specific time.
  3. Check 🚨 Data Integrity Alerts for a device_status alert.
Mitigation in place
  • 🚨 Data Integrity Alerts (device_status)
  • 📈 Uptime Metrics
  • 🌐 Offline Dashboard