A container-based solution designed to minimize manual effort and deliver quick, real-time detection of human presence in specified restricted areas, ensuring faster response and enhanced security.
The Weboccult Spot Intrusion Detection System provides real-time monitoring and alerts for restricted zones. It supports multiple camera streams, integrates with existing setups, and is built on Advantech's EdgeSync containerized environment, ensuring scalable, reliable AI inference across supported edge devices.
| Field | Details |
|---|---|
| ID / Name | 123 |
| Container Spec Brief | Nvidia Jetson Series + AI Library and Utilities (3 β 1) |
| Supported HW Devices | EPC-R7300, ICAM-540 |
| Chip Vendor / SoC | Nvidia Orin NX |
| Host OS / Container OS | Ubuntu 20.04 |
| BSP | JetPack 5.1.* |
| Pre-installed Software (Container) | CUDA 11.4.315, cuDNN 8.6.0.166, TensorRT 8.5.2.2, ONNX Runtime 1.16.3, OpenCV 4.5 |
| Supported AI Capabilities | Object detection |
| AI Model Formats | Engine, ONNX |
| Acceleration | GPU / CUDA / TensorRT |
| Precision | FP16, FP32 |
| Customer Benefit | Run optimized AI containers on supported hardware with no installation conflicts or dependency mismatches |
| Acceptance Criteria / Quick Validation | GPU visible via top |
- β Real-time human intrusion detection
- πΉ Multi-stream camera handling
- π¨ Instant alerts for detected intrusions
- β‘ Optimized AI inference using GPU/CUDA
- π§ Supports TensorRT and ONNX model formats
- π― FP16 and FP32 precision for flexible performance
- π Easy integration with existing camera setups
This application is designed to monitor restricted areas and provide instant alerts to security teams in case of unauthorized access.
- Objective: Ensure the safety and security of sensitive or restricted areas
- Functionality:
- Continuously monitors designated areas using video feeds
- Detects unauthorized entry or suspicious activity in real-time
- Sends immediate alerts to the security team for quick action
- Users: Security personnel, facility managers, or monitoring staff
This system helps organizations enhance security, reduce response time, and prevent unauthorized access to sensitive areas.
You can see the architecture diagram 
To use the Gotilo Spot Intrusion Detection system, you need a user account and an authentication token. Follow these steps:
Access the document here: Click Here
Fill in the required details.
Send the completed document to the support email: sales@weboccult.com
Our support team will help you create your account and generate a unique token to connect your system with the Gotilo Spot platform.
Once your account and token are set up, you can start using the intrusion detection system.
- OS: Linux
Ensure Docker is installed on your Jetson device. The following versions are recommended:
- Docker Engine: v20.10.x or later
- docker-compose: v1.28.x or later
Run the following command to verify Docker installation:
sudo docker --version- Set Up Docker's APT Repository
sudo apt-get update
sudo apt-get install ca-certificates curl
sudo install -m 0755 -d /etc/apt/keyrings
sudo curl -fsSL https://download.docker.com/linux/ubuntu/gpg -o /etc/apt/keyrings/docker.asc
sudo chmod a+r /etc/apt/keyrings/docker.ascAdd the Docker repository to your APT sources:
echo "deb [arch=$(dpkg --print-architecture) signed-by=/etc/apt/keyrings/docker.asc] https://download.docker.com/linux/ubuntu \
$(. /etc/os-release && echo "${UBUNTU_CODENAME:-$VERSION_CODENAME}") stable" | \
sudo tee /etc/apt/sources.list.d/docker.list > /dev/null
sudo apt-get update- Install Docker Packages
sudo apt-get install docker-ce docker-ce-cli containerd.io docker-buildx-plugin docker-compose-plugin- Verify Docker Service Check if Docker is running:
sudo systemctl status dockerTo allow the current user to execute Docker commands without using sudo:
- Add User to Docker Group
sudo groupadd docker # Create the docker group if it doesn't exist
sudo usermod -aG docker $USER- Apply Group Changes
newgrp docker- Verify User
echo $USER- Update Docker Socket Permissions
sudo chmod 666 /var/run/docker.sockAfter this, you should be able to run Docker commands without sudo. You may need to log out and log back in for the changes to take effect.
- Nvidia Jetson Orin or higher series Edge Devices
This System is designed to run on edge devices and work with existing camera infrastructure.
- Edge Devices: NVIDIA Jetson Orin or Higher series
- Supported Advantech Devices: EPC-R7300, ICAM-540 (IIoT & EIoT series)
- GPU Acceleration: NVIDIA GPU with CUDA support
.
βββ resources/
β βββ HLD-diagram.png
β βββ ACCA_How_to_run.mp4
β βββ ...
βββ docker-compose.yaml # Docker Compose configuration for service setup
βββ run.sh # Shell script to run or deploy the project
βββ README.md # Project documentation (you are here)
Follow these steps to set up and run the project:
- Clone the repository
git clone https://github.com/Advantech-EdgeSync-Containers/WebOccult-Intrusion-Detection.git- Navigate to the project directory
cd WebOccult-Intrusion-Detection- Make the run script executable
chmod +x run.sh- Run the project
./run.shThe run.sh script will automatically start the necessary services using Docker Compose as defined in docker-compose.yaml.
After running this, the project will be up and ready to use.
Watch the short demo video:
- Direct link: resources/ACCA_How_to_run.mp4
- Continuously monitors designated areas using live video feeds
- Difference between two levels of intrusion zones:
- Critical ROI (Danger Zone): Alerts are sent more frequently and faster, as this region represents a high-risk or dangerous area
- Normal ROI (Warning Zone): Alerts are sent less frequently, indicating a potential but non-critical intrusion
For common issues and solutions, please refer to the troubleshooting section or contact support at sales@weboccult.com.
The system can be further enhanced to improve video compatibility, detection accuracy, performance, and monitoring capabilities:
- π₯ Enable broader video format compatibility and streaming using FFmpeg support
- π― Improve model accuracy and reliability through enhanced person detection
- β‘ Optimize performance by implementing multiprocessing for parallel detection and processing
- β° Introduce timed intrusion detection to monitor intrusions within specific time intervals
- π― Support multiple regions of interest (ROIs) for more granular alert management
- π§ Refine code and processing pipeline for faster and more efficient operation
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