Engineers Clinic
IntermediateEngineering trackFP-MR-10

In-line parcel dimensioning station with a depth camera

Measure parcel length, width and height on a moving belt from an overhead depth camera to within 5 mm, integrate it with a photo-eye and scale, and show the revenue it recovers.

Core EngineeringMechatronics
6 Guided Steps45h Internship TierSubmit: Measurement and timing budget + synthetic depth data generator + dimensioning pipeline + accuracy and repeatability study + station logic with WMS messages + report with revenue estimateVerified CertificateAI Rubric Graded
Program Overview

Industry project · for Maple Freight Hub, a parcel sortation centre in Brampton, Ontario, with a sister hub in Buffalo, New York, handling about 1,800 parcels an hour per induction line

Maple Freight Hub charges e-commerce shippers by dimensional weight: length × width × height divided by a carrier divisor, or actual weight if that is higher. Shippers declare dimensions when they book. An audit of 2,000 parcels last month found that 23% were declared smaller than they really were, and the hub loses roughly CA$41,000 a month in under-billing at Brampton alone.

The operations manager wants an automatic dimensioning station on each induction line, before parcels are sorted. Commercial units are expensive, so the engineering team wants to understand the problem properly before choosing one, and possibly build a first unit in-house.

The proposed station: - an overhead depth camera 2.2 m above a belt running at 1.5 m/s; - a photo-eye that triggers a measurement as each parcel enters; - an in-line scale; - a message to the warehouse management system (WMS) with parcel ID, dimensions, weight and a confidence flag.

Parcels range from 100 × 100 × 20 mm envelopes to 1,200 × 800 × 800 mm boxes. Some are soft poly bags, and some arrive touching each other. The target is ±5 mm on boxes, which is close to what legal-for-trade dimensioners must meet in Canada and the US, and a clear "cannot measure" flag rather than a wrong number when the station is unsure.

You will: - set a measurement and timing budget; - generate synthetic depth frames of parcels with realistic noise, since you may not own a depth camera; - write point-cloud processing that removes the belt, separates parcels and fits a box; - measure accuracy and repeatability against ground truth; - write the station logic for trigger, scale and WMS message at 1,800 parcels an hour; - estimate recovered revenue for both hubs.

Done looks like a processing pipeline that meets ±5 mm on rigid boxes in your tests, flags what it cannot measure, keeps up with the line, and a report the operations manager can use to decide between building and buying.

Measurement system designDepth sensing and noisePoint-cloud processingPlane fitting and segmentationOriented bounding boxesAccuracy and repeatability testingStation integration and messaging
What you submit

Measurement and timing budget + synthetic depth data generator + dimensioning pipeline + accuracy and repeatability study + station logic with WMS messages + report with revenue estimate

Stack: Python, NumPy, Open3D, OpenCV, pandas, Depth camera (optional)

How it is graded
  • Sound budget15

    The accuracy and timing budget links camera resolution, depth noise, belt speed and processing time to the ±5 mm and 1,800 parcels an hour targets.

  • Realistic test data20

    Synthetic frames include depth noise, edge effects, soft bags and touching parcels, with exact ground truth stored.

  • Accurate pipeline30

    The pipeline removes the belt, separates parcels and fits boxes, meeting ±5 mm on rigid boxes in at least 95% of test cases.

  • Honest limits15

    Repeatability is measured, cases outside spec are flagged rather than reported wrong, and failure types are analysed.

  • Integration and value20

    Station logic handles trigger, scale and WMS messages within cycle time, and revenue recovered is estimated for both hubs.

Pass 60% · Merit 75% · Distinction 90%

Learning Outcomes
Budget a measurement system for accuracy and speed
simulate depth sensor data with noise
segment parcels and fit boxes in point clouds
test accuracy and repeatability against ground truth
integrate triggers, scale and messages
Target Audience

Engineering Students

Diploma, B.Tech, B.E., BCA, MCA, or M.Tech students seeking practical experience.

Aspiring Developers

Developers who want to build proof-of-work capstone projects for tech resumes.

Job Seekers

Graduates looking for AI-evaluated code review & verified industry credentials.