Overview

The Weboccult Spot Intrusion Detection System is a container-based AI solution designed to provide real-time monitoring and instant alerts for restricted zones. Built on Advantech’s WEDA environment, it minimizes manual oversight while maximizing security through automated human presence detection.

Container Description

Field	Details
ID / Name	123
Container Spec Brief	Nvidia Jetson Series + AI Library and Utilities (3 → 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

Features

✅ Real-time human intrusion detection
📹 Multi-stream camera handling
🚨 Instant alerts for detected intrusions
⚡ Optimized AI inference using GPU/CUDA
🔧 Supports TensorRT and ONNX model formats
🎯 FP16 and FP32 precision for flexible performance
🔌 Easy integration with existing camera setups

Application Includes

This application is designed to monitor restricted areas and provide instant alerts to security teams in case of unauthorized access.

Key Use Case

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.

Architecture

You can see the architecture diagram

User Account Setup & Document Submission

To use the Gotilo Spot Intrusion Detection system, you need a user account and an authentication token. Follow these steps:

Step 1: Download & Fill the Document

Access the document here: Click Here
Fill in the required details.

Step 2: Submit the Document

Send the completed document to the support email: sales@weboccult.com

Step 3: Account Setup & Token

Our support team will help you create your account and generate a unique token to connect your system with the Gotilo Spot platform.

Step 4: Start Using the System

Once your account and token are set up, you can start using the intrusion detection system.

Environment Requirements

Host Environment

OS: Linux

Docker Setup

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

Check if Docker is Installed

Run the following command to verify Docker installation:

sudo docker --version

If Docker is not installed, follow these steps:

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.asc

Add 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 docker

Run Docker Without sudo

To 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.sock

After 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.

Installation Requirements

L1-01 Container Requirements

Nvidia Jetson Orin or higher series Edge Devices

Supported Device

This System is designed to run on edge devices and work with existing camera infrastructure.

Hardware Requirements

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

Repository Structure

.
├── resources/
│   ├── HLD-diagram.png
│   ├── ACCA_How_to_run.mp4
│   └── ...
├── docker-compose.yaml         # Docker Compose configuration for service setup
├── run.sh                      # Shell script to run or deploy the project
└── README.md                   # Project documentation (you are here)

Quick Start / Installation

Follow these steps to set up and run the project: Github Repository for Quick Start

Application Usage

Example to run

Watch the short demo video:

Direct link: resources/ACCA_How_to_run.mp4 ▶️

Functionality:

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

Troubleshooting

For common issues and solutions, please refer to the troubleshooting section or contact support at sales@weboccult.com.

Future Work

The system can be further enhanced to improve video compatibility, detection accuracy, performance, and monitoring capabilities:

🎥 Enable broader video format compatibility and streaming using FFmpeg support
🎯 Improve model accuracy and reliability through enhanced person detection
⚡ Optimize performance by implementing multiprocessing for parallel detection and processing
⏰ Introduce timed intrusion detection to monitor intrusions within specific time intervals
🎯 Support multiple regions of interest (ROIs) for more granular alert management
🔧 Refine code and processing pipeline for faster and more efficient operation