RADEAGLE (RE-Cx) Detection unit


The RADEAGLE Cx (RECx) utilises a large volume NaI(Tl) scintillation crystal with 2''x4''x8'' or 2''x4''x10'' geometries. These ultra-sensitive units provide optimum detection capabilities and are the backbone of innoRIIDs mobile search applications and portal solutions. The RECx can also be used as backpack system. It can be operated either with our mobile applications or via the GammaStudio software suite.

RADEAGLE Cx Product Flyer
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Industrial internet of things (IIot)

RADEAGLE Cx is an Industrial Internet of Things (IIoT) device. It features outbound data streaming with a 100ms update rate for the radiologic variables like H*(10) equivalent dose rate (in µSv/h and in µrem/h) and the count rate. Spectra with 2048 channels can be obtained at a rate of 4 spectra / s. 

Message queueing telemetry transport (MQTT)

Data streams are provided via an onboard MQTT broker. Alternatively, the system can publish to any other external broker as well. Once subscribed to the channels of the system, the data objects that are published by the system are JSON documents that can be easily parsed by applications.


The system can be additionally operated via a REST API. Current spectrum, nuclide identification results, status of artificial source identification and administrative variables can be read and set over this interface.


The system can be operated in backpack mode. We offer a ruggedised case backpack and a common use backpack as variants. While the common backpack has the advantage inconspicuous, the rugged case variant (picture below) offers stable and endurable handling in difficult terrains. Depending on your type of mission, innoRIID will help you to find the best suited casing for the RECx. Especially for the the autonomous operation of a backpack, we provide a smart lithium power unit with digital lifetime processing provides autonomous in-field runtimes of more than 12 hours for RECx. Users can check visually the battery status via the inbuilt indicator display. RECx is compatible with innoRIIDs standard battery type for the RADEAGLET-R.

Autocalibration on natural radiation

The RECx does not use any internal source. It does not contain any radiating material. Instead, we use the natural background radiation. See the tiny little peak in the spectrum? This is a peak of 40K. It is nearly always there. This is one of many peaks the RTR grabs to keep the calibration in place. And because our detector is supported by quite algorithmic techniques, it sees the tiny peak very quickly. The software also applies machine learning techniques for storing the complicated dependencies of the peak position and temperature.


Each individual instrument is virtually "trained" at innoRIIDs production facilities, not only with respect to temperature values but especially to different temperature change rates (shocks). Should you still require a unit with internal source, we can optionally equip the  with a small calibrations sources.

Unique bayesian shapelet detection algorithm based on machine learning for dynamic background compensation

Utilising a novel machine learning algorithm for source detection, the system is stabilised against background variation which occur if the unit is operated on vehicle. The shapelet detection is combined with a Bayesian network to determine conditional probabilities for the presence of a source and to call out the alarm. Details about this technique have been published by the team of innoRIID at the IEEE Nuclear Science Symposium and Medical Imaging Conference (NSS-MIC) in Milano, 2023.

GPS Positioning (Optional)

Spectroscopic and radiologic data measured with RADEAGLE RECx can be optionally equipped with a GPS positioning system. This tags the RECx data with geographical information, once the optional GPS module is installed. 

Nuclide identification powered by artificial intelligence

The identification of nuclides is based on the spectrum. On the computer system of RADEAGLE Cx, a powerful mathematical algorithm identifies radioactive sources based on this spectrum. It can also find the right composition, if multiple of these sources are present. Using combinations of different machine learning methods, semantic strategies and an expert knowledge database, the algorithm is a good example about artificial intelligence powering modern sensorial equipment.


Specifically adapted to the properties of large volume detectors, the instrument was equipped with capabilities that help to find shielded sources in vehicle applications. Special strength of the methods applied by RECx is an extraordinary good separation of SNM like Uranium, Plutonium or Neptunium against potential masking sources from medical, industrial or naturally occurring sources. The algorithm is available as standalone Replay-Tool for Windows 8/10/11 and for macOS. It allows to compare different algorithm versions, as well, as it helps organisations in their evaluation of the result quality. 

Technical Specifications of the RADEAGLE Cx unit