← back
Automated Tote Counting Camera System

Automated Tote Counting Camera System

Pending
💰 USD 5000–10000 👤 Unknown 🕒 14d ago status: new
Data Processing Embedded Systems Computer Vision Deep Learning Edge Computing API Development Image Recognition
I need a turnkey, camera-based solution that automatically counts plastic totes as they move through the rear door of each of my 100 refrigerated trucks. The goal is simple: every tote that goes in or out must be logged accurately without asking the driver to press a button, scan a tag, or slow down the loading process. Miscounts today cost real money; the new system must work in the messy, unpredictable environment of an active loading dock, not in a lab. Environment & constraints • Lighting varies from bright daylight to total darkness inside the trailer, and weather changes constantly when the door is open. • Drivers may step in front of the lens, so brief occlusion is inevitable. • Totes often travel in stacks of two to five, so the software has to identify and separate them visually. • The driver’s workflow takes priority: mounting hardware must be completely passive and leave the doorway unobstructed. Technical expectations • Counting will rely on image-recognition software. You are free to recommend the specific camera technology—standard optical with night vision, infrared, or another approach—as long as it produces stable, high-resolution frames that let the algorithm distinguish individual totes under the conditions above. • On-device or edge processing is preferred to minimize data usage, but I’m open to a small in-cab server or a cloud pipeline if you can justify it. • I will supply power from the truck’s 12/24 V system; detail any additional power conditioning you need. • Each truck must push its counts (IN, OUT, timestamp, truck ID) to our existing SQL back-end over cellular. An API endpoint already exists; you just need to format the payload. Deliverables 1. Hardware bill of materials with part numbers and sourcing info for 100 units. 2. Camera-mount design (CAD or detailed drawings) that tolerates vibration and wash-downs. 3. Image-recognition software, trained and packaged for repeat deployment. 4. Installer’s guide and user manual for fleet maintenance staff. 5. A pilot installation on one truck, proven over two weeks of live operation with ≤1 % counting error, before authorizing full-fleet roll-out. Acceptance will be based on the pilot accuracy report and a walk-through of the complete installation procedure. If you have experience with vision systems in logistics, please explain how you handled low light, occlusion, and rapid item movement before, and include a brief timeline for prototype, pilot, and scale-up phases.
↗ View on Freelancer