AI-Enabled Computer Vision Condominium Security System Development
Budget: $250 – $750 USD
I'm in need of a dedicated Computer Vision/AI developer who can build a comprehensive security system for a condominium. The scope of this project includes:
1. Implementing Object Detection: The system should be capable of identifying objects within the condominium premises in real-time.
2. Facial Recognition: It has to recognize residents from guests, aiding in the identification of unauthorized individuals.
3. Activity Monitoring: The system should be smart enough to monitor activities within the common and specific areas round-the-clock.
This project will be implemented from scratch; we don't have any existing surveillance cameras or access control systems at the moment.
Ideal candidates should have a proven track record with Computer Vision/AI technologies, such as TensorFlow or OpenCV, and experience with hardware integration. Prior experience in security surveillance software development will be a plus.
A developer with expertise in computer vision, artificial intelligence, and deep learning is needed to create a functional MVP (Minimum Viable Product) prototype of a security monitoring system based on real-time video analytics.
The goal is to develop a pilot system that demonstrates the following key capabilities:
Facial recognition and detection of authorized/unauthorized identities
Detection of dangerous objects (weapons, suspicious packages, etc.)
Identification of abnormal behaviors, theft, vandalism, altercations
Vehicle license plate reading for access control
Real-time visual/audible alert generation
Ability to record video and images as evidence
Basic integration with access control systems
Dashboard visualization and reporting for administrators
The system must leverage computer vision techniques such as object detection, facial recognition, motion analysis, etc. It should be able to process multiple simultaneous video streams.
Proven experience in development with OpenCV, TensorFlow/PyTorch, and other computer vision libraries is required. Knowledge of cloud systems and serverless architectures is a plus.
The project will be conducted remotely, and a functional MVP must be delivered for pilot testing with real clients within a 3-month timeline.
Key Skills:
Computer Vision/AI
Deep Learning
Python, C++ development
Cloud computing knowledge (AWS, Azure, GCP)
1. Implementing Object Detection: The system should be capable of identifying objects within the condominium premises in real-time.
2. Facial Recognition: It has to recognize residents from guests, aiding in the identification of unauthorized individuals.
3. Activity Monitoring: The system should be smart enough to monitor activities within the common and specific areas round-the-clock.
This project will be implemented from scratch; we don't have any existing surveillance cameras or access control systems at the moment.
Ideal candidates should have a proven track record with Computer Vision/AI technologies, such as TensorFlow or OpenCV, and experience with hardware integration. Prior experience in security surveillance software development will be a plus.
A developer with expertise in computer vision, artificial intelligence, and deep learning is needed to create a functional MVP (Minimum Viable Product) prototype of a security monitoring system based on real-time video analytics.
The goal is to develop a pilot system that demonstrates the following key capabilities:
Facial recognition and detection of authorized/unauthorized identities
Detection of dangerous objects (weapons, suspicious packages, etc.)
Identification of abnormal behaviors, theft, vandalism, altercations
Vehicle license plate reading for access control
Real-time visual/audible alert generation
Ability to record video and images as evidence
Basic integration with access control systems
Dashboard visualization and reporting for administrators
The system must leverage computer vision techniques such as object detection, facial recognition, motion analysis, etc. It should be able to process multiple simultaneous video streams.
Proven experience in development with OpenCV, TensorFlow/PyTorch, and other computer vision libraries is required. Knowledge of cloud systems and serverless architectures is a plus.
The project will be conducted remotely, and a functional MVP must be delivered for pilot testing with real clients within a 3-month timeline.
Key Skills:
Computer Vision/AI
Deep Learning
Python, C++ development
Cloud computing knowledge (AWS, Azure, GCP)