Using Sensor Data to Protect Communities

The Client

C-10 Research and Education Foundation logo

C-10 Research and Education Foundation

The C-10 Research & Education Foundation has been operating a real-time 24-hour airborne radiation monitoring network in the communities within a 10-mile radius of Seabrook Station nuclear power plant since 1991, soon after the 1,244 MW pressurized water reactor first became operational. Through a system of probes and computers, the Citizens Radiological Monitoring Network (CRMN) detects and records beta and gamma radiation as well as wind speed and direction.

The Problem

With minute-by-minute data from an array of sensors installed since 2009, C-10 needed to improve their ability to analyze and understand their data.

C-10 has been collecting data from monitoring stations dating back to 2009 and their pool of data is increasing each day. Each station adds approximately 1440 data points about beta and gamma radiation daily. In addition, if the sensor is equipped with an anemometer and wind vane, wind speed and direction data is also available.

C-10’s incumbent process required gathering time-series data from hundreds of separate log files to produce monthly traces of beta gamma radiation levels. Those plots were then assembled into a document distributed to key investigators to enable them to identify any trends or indications of an incident within the month of interest.

two people, one white man and one white woman, dressed in high-visibility construction gear check a paper

The Approach

Through a series of collaborative sessions, the Pro Bono Analytics (PBA) team worked with the C-10 Network Administrator to understand the meaning and application of the data collected from the sensors and further to understand the full range of data involved, and how the data was organized, stored, and prepared for analysis.

There are ~20 monitoring stations installed in communities within a 10-mile radius of the Seabrook Station nuclear power plant. The sensors capture readings of beta and gamma radiation levels, as well as wind speed and direction, at 1-minute intervals. The data is pushed to a central location in near real time and backed up by a daily log file. The data is retained in a series of daily folders containing the log files from reporting sensors.

The Solution

The core challenge expressed by C-10 was to enable better analysis of their existing data. Performing initial exploratory analysis, the volunteer team plotted the beta and gamma radiation time series and produced visualizations of the wind speed and direction data.

Through discussion with the team members and input from the user community (including C-10 board members and affiliated scientists) the team chose to create an interactive application using the Streamlit framework for Python applications. The application allows interested parties to access the data over the web and plot the radiation time series and related wind plots over the desired time frame. The radiation levels are shown as line charts, and wind speed and direction for the same time period are shown as radial scatterplots. The combination of charts allows interested parties to identify spikes and other anomalies in the radiation levels and see where those correlate with wind speed and direction. 

Early in the project, the PBA team explored several options for managing the existing data and understanding the completeness of the historical record. The daily log files generated by the sensor array are retained on C-10’s FTP servers for access by government and community partners if needed, but access to data from multiple servers over longer periods of time is a manual process. The team elected to use the file system to continue to organize and retain the log files and built some log file maintenance support into the application, to allow for simple maintenance of the sensor log data.

Project at a Glance

Sector

Scientific, Government, Regulatory

Non-profit Size

2 full time staff

Location

10-mile radius of Seabrook, NH

Volunteer Time

Approx. 10 hours per week

Analytics Area

Data management and visualization

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