An end-to-end IoT-based intelligent road safety monitoring platform designed to detect and visualize hazardous road conditions such as ice, snow, and dry asphalt in real time.
Traditional weather APIs provide atmospheric forecasts but do not directly measure real-time road surface conditions. This limitation can result in undetected ice or snow hazards, increasing accident risk.
This system integrates:
• Embedded spectral & thermal sensing
• Long-range LoRa communication
• ASP.NET Core Web API backend
• SQL Server database
• Real-time dashboard visualization
• Google Maps hazard alerts & route safety analysis
The platform detects surface type, assigns risk levels, and visually alerts users when hazardous conditions are present.
IoT Sensor Node
↓
LoRa (REYAX RYLR998)
↓
ASP.NET Core Web API
↓
SQL Server Database
↓
Web Dashboard + Google Maps API
• Raspberry Pi Pico 2 W – Main controller
• MLX90614 – Surface temperature sensor
• DHT22 – Air temperature & humidity sensor
• AS7343 – Spectral sensor (VIS Mean, NIR Ratio, Whiteness Index)
• REYAX RYLR998 – LoRa communication module
• UART-based AT command LoRa communication
• Long-range, low-power data transmission
• Reliable packet forwarding to backend API
• RESTful Web API
• Entity Framework Core
• SQL Server persistence
• Device registration & management
• Data filtering by location and duration
• Risk classification logic
• Real-time sensor data retrieval
• Surface classification display
• Risk indicator (Low / Medium / High)
• Trend analysis graphs (Air & Surface Temp)
• Snow prediction integration
• Historical data filtering
• Alerts log tracking
• Google Maps API integration
• Hazard marker placement
• Ice / Snow detection popups
• Re-route suggestion system
• Safe route visualization
👉 https://drive.google.com/file/d/1ZULd-0p43aBW0I14okI1I8ELuYCAlo_h/view?usp=sharing
Demonstrates real-time snow surface classification using spectral analysis and temperature thresholds. Sensor data is transmitted via LoRa to the ASP.NET Core backend, stored in SQL Server, and dynamically retrieved by the dashboard for visualization and risk evaluation.
👉 https://drive.google.com/file/d/1rHKsgJdqUam6YX8pnaBYdBoH8zzlfMwV/view?usp=sharing
Shows successful detection of dry asphalt conditions using VIS mean, NIR ratio, and surface temperature metrics. Data is processed server-side and rendered in the dashboard, confirming safe road classification.
👉 https://drive.google.com/file/d/1jodPWaOZ_VkF0dZx2FLKAaqb0sVeL8OQ/view?usp=sharing
Illustrates hazardous ice detection triggered by low surface temperature and spectral reflectivity characteristics. The detected condition is transmitted over LoRa, persisted in the database, and immediately reflected in the dashboard with updated risk indicators and route hazard alerts.
C#
ASP.NET Core
Entity Framework Core
SQL Server
Raspberry Pi Pico W
MicroPython
LoRa (REYAX RYLR998)
Google Maps API
WeatherAPI
RESTful APIs
Embedded Systems
✔ End-to-end IoT data pipeline
✔ Real-time hazard detection
✔ Embedded systems + full-stack integration
✔ Geospatial route safety analysis
✔ Database-driven dashboard
✔ Professional admin management interface
Developed in collaboration with Agamdeep Singh Sandhu.
Sandip Bohara Chhetri
Computer Engineering Technologist