Confidentiality Notice: This document provides a high-level summary of skills and technologies used in a professional project. In accordance with employer confidentiality policies, proprietary details including system architecture, implementation specifics, client information, and internal methodologies have been omitted.

Over-Height Vehicle Detection System

Real-Time Infrastructure Protection for Transportation Agencies

Sole Developer & System Architect

Multi-Process Architecture Real-Time Sensor Fusion Docker Containerization 24/7 Field Deployment

Project Overview

A production-grade vehicle detection system deployed at multiple field locations to protect bridge infrastructure from over-height vehicle collisions. The system integrates multiple sensor types into a unified detection and alerting platform with real-time response capabilities.

~12,700 Lines of Python
63 Source Files
<1s Detection Latency
24/7 Uptime Target
Role: Sole developer responsible for full system design, implementation, deployment automation, and ongoing maintenance across all field sites.

System Architecture

Containerized multi-process application deployed on industrial hardware at roadside detection sites. The architecture emphasizes fault tolerance, automatic recovery, and minimal operator intervention.

flowchart TB subgraph SENSORS["Sensor Layer"] LIDAR["LiDAR Sensor
Height Detection"] VCA["Video Analytics Camera
VCA Metadata via MQTT"] PTZ["PTZ Camera
RCP+ Protocol"] end subgraph PROCESSING["Processing Layer - Docker Container"] IPC["MQTT Message Bus"] PROC["Event Processing
Correlation · Deduplication"] DB[(PostgreSQL)] WEB["Flask Web Interface"] WATCHDOG["Watchdog Supervisor"] end subgraph OUTPUT["Output Layer"] RELAY["Relay Controllers
TCP/Telnet"] VMS["VMS Warning Signs"] FEED["Data Feeds
SFTP · NiFi"] DVS["Video Streaming Service
RTSP Relay"] UI["End-User Dashboard"] RTSP_OUT["Video Recording
RTSP Capture"] RELAY --> VMS FEED --> UI DVS --> UI RTSP_OUT --> UI end PTZ -->|"RTSP"| DVS VCA -->|"RTSP"| DVS LIDAR -->|"XML/TCP"| IPC VCA -->|"MQTT"| IPC PTZ -->|"RCP+ · RTSP"| PROC IPC --> PROC PROC --> DB PROC --> WEB WATCHDOG -.->|"monitors"| PROC PROC --> RELAY PROC --> FEED PROC --> RTSP_OUT

System Capabilities

Sensor Integration

Real-time data acquisition from multiple sensor types including LiDAR height detection and video analytics cameras.

Event Processing

Detection event handling with deduplication, correlation, and database persistence for audit trails.

Automated Response

Trigger-based activation of warning systems and video recording upon detection events.

System Reliability

Multi-tier health monitoring with automatic recovery mechanisms for continuous operation.

Technology Stack

Backend

Python 3.x Flask SQLAlchemy PostgreSQL MQTT

Frontend

JavaScript (ES6+) jQuery Axios WebSocket

Infrastructure

Docker Docker Compose Ubuntu Linux Gunicorn Express.js

Protocols

RCP+ (Bosch) RTSP MQTT SNMP HTTP/REST TCP Sockets Telnet

Hardware Integration & Protocols

Direct integration with industrial sensors and cameras required implementing multiple vendor-specific and standard protocols:

LiDAR Integration

Real-time height measurement data acquisition via TCP socket connections. XML-based event parsing with configurable detection thresholds and zone definitions.

Bosch RCP+ Protocol

Implementation of Bosch's proprietary Remote Control Protocol for PTZ camera control. Includes preset positioning, continuous movement commands, and camera status monitoring.

Video Analytics (VCA)

MQTT-based subscription to camera metadata streams. Real-time parsing of detection events with object classification and tracking data extraction.

RTSP Stream Management

Video stream capture and recording triggered by detection events. FFmpeg-based processing with automatic cleanup and FTP upload of evidence footage.

Relay Controller Interface

TCP/Telnet communication with industrial relay boards for VMS warning sign activation. Includes connection pooling and automatic reconnection logic.

SNMP Monitoring

Network device health monitoring via SNMP queries. Status polling for cameras and network infrastructure with alerting on failures.

Engineering Scope

The project required addressing challenges across multiple engineering domains:

Deployment & Operations

Automated Installation

Custom installer with dependency management and system configuration for field deployment.

Configuration Management

Web-based settings interface with validation and secure credential storage.

Remote Updates

SSH-based deployment automation with rollback capability.

External Integration

Data feeds to centralized traffic management systems via standard formats.

Project Outcomes

Successfully deployed and operational across multiple field sites with continuous uptime requirements met.

Production Deployment Status
Multiple Field Sites
24/7 Operation
Active Maintenance