FY26 Monitoring
FF
Likely R&D

Sensor Calibration Algorithm

Sensor Calibration Algorithm

FY26 · 75 evidence items · 82% claim readiness

Project summary

FlowForge developed a new calibration algorithm to improve sensor accuracy in unstable industrial environments where temperature, vibration, and signal interference caused inconsistent readings.

Technical uncertainty

The team could not determine in advance whether a filtering and recalibration approach could maintain acceptable accuracy across variable field conditions without creating unacceptable latency or false readings.

Working hypothesis

If the sensor pipeline combined adaptive filtering with periodic recalibration against known reference points, the system may maintain reliable accuracy in noisy industrial environments.

Claim readiness

0%

Key figures

Est. eligible spend
$178K
Evidence items
75
Confidence
High
Documentation gaps
2

Evidence gaps

  • Final field test report
  • Team time allocation

Experimentation timeline

  1. Jul 2025

    Initial calibration issue identified

    Jira
  2. Aug 2025

    Prototype filtering approach developed

    GitHub
  3. Sep 2025

    Field test failed under vibration conditions

    Drive
  4. Oct 2025

    Algorithm revised using adaptive thresholding

    GitHub
  5. Nov 2025

    Second field test completed

    Jira
  6. Jan 2026

    Performance improved but latency issue detected

    Slack

Experimentation iterations

1

Static calibration table

Outcome

Failed under temperature variation

Evidence

Test Report TR-104

2

Adaptive filtering layer

Outcome

Improved signal stability but introduced latency

Evidence

GitHub commits, Jira ticket CAL-182

3

Hybrid recalibration model

Outcome

Improved field accuracy and reduced latency

Evidence

Field Test Report Q2

Supporting evidence (5 items)

View all evidence

Team involvement

  • Maya ChenML Engineer
    55% R&D time38 signals
  • Liam BrooksProduct Engineer
    42% R&D time31 signals
  • Daniel RossCTO
    18% R&D time18 signals
  • Priya SinghQA / Test Lead
    35% R&D time22 signals

Eligible cost breakdown

$178K

Total estimated eligible expenditure

Engineering salaries
$122K
medium
Contractor costs
$31K
high
Prototype materials
$14K
medium
Testing costs
$11K
high

Confidence breakdown

Technical uncertainty clarity88%
Experimentation history84%
Evidence completeness79%
Cost allocation68%
Documentation quality81%
Compliance confidence78%

Missing information

View all gaps
  • Confirm whether Project 1 activities were conducted in Australia
  • Upload final field test results
  • Confirm team member time allocation
  • Canopy specialist will confirm eligible vs non-eligible activities
  • Review contractor invoices for scope alignment

Suggested next steps

  • 1Submit Project 1 to Canopy for preparation
  • 2Confirm cost allocation
  • 3Upload missing field test report
  • 4Export evidence pack
  • 5Add this project to draft claim workspace

Figures update automatically as new evidence is connected. Your Canopy specialist will confirm all positions during claim preparation.