You will get a Real-Time Edge AI Computer Vision System
Project details
Overview
I will build a complete real-time computer vision system that converts your camera feeds into actionable business insights using edge AI.
What I build
1. Camera feed ingestion (CCTV / RTSP streams)
2. Real-time object detection and tracking (YOLOv8/11 + ByteTrack)
3. Dashboard-ready structured outputs (JSON)
4. Edge deployment (Raspberry Pi/Jetson Orin Nano)
Use cases
1. Retail/QSR: customer count and wait / dining time analysis, peak hours, footfall detection (Tracking + ReID)
2. Security: intrusion detection, restricted zone alerts, unauthorized parking, Theft detection
3. Manufacturing: defect detection, quality monitoring, employee productivity monitoring
What you get
1. Fully working pipeline (code + deployment)
2. Custom-trained or fine-tuned model (if needed)
3. Integration with Video Management Systems (VMS)
4. API or JSON outputs for dashboard integration
5. Deployment guide + documentation
I will build a complete real-time computer vision system that converts your camera feeds into actionable business insights using edge AI.
What I build
1. Camera feed ingestion (CCTV / RTSP streams)
2. Real-time object detection and tracking (YOLOv8/11 + ByteTrack)
3. Dashboard-ready structured outputs (JSON)
4. Edge deployment (Raspberry Pi/Jetson Orin Nano)
Use cases
1. Retail/QSR: customer count and wait / dining time analysis, peak hours, footfall detection (Tracking + ReID)
2. Security: intrusion detection, restricted zone alerts, unauthorized parking, Theft detection
3. Manufacturing: defect detection, quality monitoring, employee productivity monitoring
What you get
1. Fully working pipeline (code + deployment)
2. Custom-trained or fine-tuned model (if needed)
3. Integration with Video Management Systems (VMS)
4. API or JSON outputs for dashboard integration
5. Deployment guide + documentation
AI Development Type
Deep Learning, Model TuningAI Tools
NVIDIA AI Platform, Open Neural Network Exchange, OpenCV, PyTorchAI Development Language
PythonWhat's included
| Service Tiers |
Starter
$53
|
Standard
$100
|
Advanced
$250
|
|---|---|---|---|
| Delivery Time | 4 days | 7 days | 20 days |
Number of Revisions | 1 | 2 | 5 |
AI Model Integration | - | ||
Detailed Code Comments | - | ||
Knowledge Graph | - | - | - |
Model Documentation | - | ||
Ontology | - | - | - |
Source Code | - | - | |
Taxonomy | - | - | - |
Optional add-ons
You can add these on the next page.
Post-deployment support
(+ 5 Days)
+$20About Subadarshini
AI ML Engineer | Computer Vision | Generative AI
Chennai, India - 4:38 am local time
Computer Vision Systems
1. Object detection and tracking with YOLOv8/v11, ByteTrack, SORT, and DeepSORT.
2. Extensive experience with semantic / instance segmentation models (UNet, Mask RCNN, Detectron2, and SAM3).
3. Design and deploy models for pose estimation (OpenPose, YOLO-Pose).
LLM Engineering & AI Automation
1. Design AI agents and automation workflows using CrewAI, LangGraph, and LangChain.
2. Build scalable RAG pipelines using LangChain, ChromaDB/FAISS/Pinecone.
3. Integrate LLMs / AI assistants into your workflows or website.
Additional Capabilities
1. Dataset preparation and image annotation - LabelImg, LabelME
2. Performance optimization using LoRA, QLoRA, TensorRT, ONNX, CUDA
3. Integration of machine learning models into production applications
If you're looking to build practical AI solutions — not just experiments — I can design, train, fine-tune, and deploy the entire system end-to-end.
Steps for completing your project
After purchasing the project, send requirements so Subadarshini can start the project.
Delivery time starts when Subadarshini receives requirements from you.
Subadarshini works on your project following the steps below.
Revisions may occur after the delivery date.
Requirement Analysis and Project Scope
1. Analyse requirements and communicate ideas, delivery date, and project scope.
Project commencement
1. Design architecture, workflow, and modules in the pipeline 2. Gather data and start fine-tuning (if needed)