This project page is currently a high-level overview. Full technical documentation coming soon.

Overview

ReveloTube is an end-to-end environmental monitoring system designed for the London Underground network. Built during my Embedded Systems module at Imperial, the system collects real-time environmental data from station and train-mounted Raspberry Pi Zero modules, transmitting it over the Underground’s 5G network.

The Concept

Different passenger groups have different environmental needs:

  • Neurodiverse passengers can check noise levels before travelling
  • Asthma sufferers can monitor air quality conditions
  • Heat-sensitive passengers can avoid particularly hot lines or carriages

The system envisions integration with TfL Go, allowing passengers to make informed journey decisions based on their specific requirements.

Technical Overview

Hardware:

  • Raspberry Pi Zero W modules mounted in stations and on trains
  • Sensors for noise, temperature, humidity, and air quality (VOC detection)

Architecture:

  • Data transmission via London Underground’s 5G network
  • NoSQL database for real-time data storage
  • Web-based visualisation showing conditions line-by-line and station-by-station

Software:

  • C++ for sensor interfacing and data collection
  • HTTP/JSON for data transmission
  • Real-time web dashboard

Key Learning

This project demonstrated how existing infrastructure (5G rollout on the Underground) could enable passenger-facing accessibility services with relatively modest hardware investment, whilst strengthening my understanding of end-to-end IoT system design and real-time data handling.

Team Members: Yiru Chen, Monika Koppuravuri, Robin A Masih, Madhushree Manjunatha Technologies: C++, Raspberry Pi, HTTP, JSON, NoSQL, Web Development
Repository: github.com/pb1n/EmbeddedCW1
Status: Placeholder - full documentation in progress
Date: December 2025