NoorCity
Smart Street Lighting
February 2025 – May 2025 · Team project · ESPRIT
A Symfony web platform to supervise the street lighting of a connected city: geolocated street lights on a map, IoT sensors, traffic cameras, energy, citizen complaints and interventions, with new locations suggested by machine learning (K-Means).
By the numbers
0
routes (approx.)
0
Doctrine entities
0
Twig views (approx.)
0
external APIs integrated
Case study
The challenge
A city's lighting network is often managed with separate tools: a plan, consumption readings, breakdown reports and interventions. The goal was to bring it all onto a map, link each street light to its sensors and cameras, and automate the alerts.
Architecture
Interfaces
- MaterialPro back office (Twig, Bootstrap)
- SmartLamp citizen front office
- Leaflet + OpenStreetMap maps
Symfony 6.4
- 12 controllers, ~75 routes
- 17 Doctrine entities
- Role-based dynamic forms
- SMS, e-mail and assistant services
Data & scripts
- MySQL (17 tables)
- Python: K-Means, QR codes
- HTTP IoT gateway (JSON)
External services
- Twilio (SMS)
- Mailjet (e-mail)
- OpenCage (geocoding)
- OpenStreetMap
Interfaces
- MaterialPro back office (Twig, Bootstrap)
- SmartLamp citizen front office
- Leaflet + OpenStreetMap maps
Symfony 6.4
- 12 controllers, ~75 routes
- 17 Doctrine entities
- Role-based dynamic forms
- SMS, e-mail and assistant services
Data & scripts
- MySQL (17 tables)
- Python: K-Means, QR codes
- HTTP IoT gateway (JSON)
External services
- Twilio (SMS)
- Mailjet (e-mail)
- OpenCage (geocoding)
- OpenStreetMap
Technical choices
01
Machine learning in a PHP app
Symfony writes the data as JSON, runs the Python K-Means script and reads the result back: new street light locations are suggested right on the map.
02
Decision support
The energy profile comparator normalizes consumption, cost and active time, then computes a weighted score from the chosen weights (100 % in total).
03
Automatic alerts
A temperature above 50 °C triggers a Twilio SMS, so does a new energy source, and every new profile sends an e-mail through Mailjet.
04
Reliable data
Validation constraints on the entities (IP address, stream URL, measurement ranges), PHP 8.1 enums mapped to Doctrine and CSRF protection on deletions.
Key features
- Interactive Leaflet map of zones and street lights (green when working, red when broken), placing a light by clicking the map with OpenCage geocoding
- New street light locations suggested by K-Means (scikit-learn), run from Symfony
- IoT sensors (temperature, light, motion, consumption): dashboard, multi-criteria search, Excel export and a QR code per sensor
- Automatic SMS alert (Twilio) above 50 °C, e-mail notifications (Mailjet) when a profile is created
- A “Sensors Pro” assistant that queries the database: broken sensors, averages by type, anomaly detection
- Multi-criteria energy profile comparator: a weight per criterion, normalized values and a weighted score
- IP cameras: live stream from a street light and traffic analysis by a Python script
- Citizen complaints on a public front office, then interventions assigned to technicians; PDF, Excel and CSV exports
Screenshots (20)
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