Facial Recognition for Delivery Drones
Project Description
I need a facial-recognition module that lets each of my delivery drones confirm a recipient’s identity before a package is released. The goal is simple: the aircraft hovers, points its camera at the person waiting below, and—within a fraction of a second—decides whether it’s safe to drop the parcel.
Here’s what the system must do:
• Detect and recognise faces in real time from a moving drone, outdoors, in daylight or at night.
• Run on a light edge device carried by the drone (Jetson Xavier NX or similar) or stream efficiently to a ground server if you have a smarter approach.
• Expose a clean API that returns the recognised ID, confidence score, and a yes/no flag my flight-control software can act on.
• Allow me to enrol new authorised faces quickly—either by uploading images or shooting a short video clip.
Deliverables
1. Trained model (TensorFlow, PyTorch, or ONNX) with all weights and source code.
2. Companion-computer integration script and clear step-by-step setup guide.
3. Demo footage (or a live test, if you prefer) proving ≥95 % accuracy with latency under 300 ms.
4. Concise documentation covering hardware requirements, installation, and how to maintain or update the face database.
If you’ve already tackled drone vision, edge AI, or similar face-verification projects, I’d love to see examples. Let’s get this flying. Show More
Here’s what the system must do:
• Detect and recognise faces in real time from a moving drone, outdoors, in daylight or at night.
• Run on a light edge device carried by the drone (Jetson Xavier NX or similar) or stream efficiently to a ground server if you have a smarter approach.
• Expose a clean API that returns the recognised ID, confidence score, and a yes/no flag my flight-control software can act on.
• Allow me to enrol new authorised faces quickly—either by uploading images or shooting a short video clip.
Deliverables
1. Trained model (TensorFlow, PyTorch, or ONNX) with all weights and source code.
2. Companion-computer integration script and clear step-by-step setup guide.
3. Demo footage (or a live test, if you prefer) proving ≥95 % accuracy with latency under 300 ms.
4. Concise documentation covering hardware requirements, installation, and how to maintain or update the face database.
If you’ve already tackled drone vision, edge AI, or similar face-verification projects, I’d love to see examples. Let’s get this flying. Show More
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Budget
$3,000 - $4,500
Client Info
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Project Summary
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Status
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Category
Software Development
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Project Type
Fixed Price
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Budget
$3,000 - $4,500
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Date Posted
1 day ago
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Project ID
3489
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Project Views
534
