Design and implementation of a Raspberry PI based spectrum monitoring system
Abstract
The radio spectrum is a critical resource for a wide range of applications, including communication, navigation, remote sensing, military, and scientific research. Its importance continues to grow as new technologies and applications emerge. While radio spectrum allocation is well regulated, there is little knowledge about its actual utilisation. This limitation hinders taking effective actions in various applications including cognitive radios, electrosmog monitoring, and law enforcement
This project presents a Spectrum Monitoring System that implements the spectrum sensing operation based on a Software Defined Radio (SDR) and a Raspberry Pi. The system captures radio signals in the environment and processes them to produce a real-time graphical representation of the spectrum which is visualised on a web application.
To implement this spectrum monitoring system, the hardware components were set up with appropriate drivers and libraries installed on the raspberry pi, an API was created using Flask app to enable the end user to communicate with the hardware components through a web interface.
The developed Spectrum Monitoring System is highly portable and cost-effective and when its performance was evaluated and its cost of production was compared to that of a similar on-the-market spectrum analyser that is the RF explorer, the developed system was found to perform comparably well while achieving an overall reduction in the cost, making it an ideal solution for various applications, including education, hobbyist projects, law enforcement, and research.
The web-based dashboard provides an easy-to-understand interface for the user to visualise the spectrum and identify any unusual patterns or frequencies. The system’s ability to visualise the spectrum provides valuable insights into the usage of the radio spectrum, enabling users to optimise their wireless communication systems and avoid interference. The system can also help users identify unused frequencies, allowing for efficient use of the spectrum.