Detecting and tracking multiple mobile radioactive sources by data fusion of a surveillance camera and a sodium iodide (NaI) detector

Nowadays, the use of radioactive materials has increased due to recent progress in nuclear technology, but concerns about the missing or smuggling of radioactive materials have persisted. Nuclear threats such as terrorist attacks or the malicious use of radioactive materials out of regulatory control (MORC) are always severe problems that can result in adverse environmental, health, economic, and security effects. Applying new technologies to monitor and track MORC will prevent radioactive materials from being illegally transported across borders or from one place to another. In this research, we have constructed a detection system to automatically and remotely localize multiple mobile gamma-emitting radiation sources among other objects by combining an IP camera and a sodium iodide detector. An algorithm for the detection system has been developed to identify the objects’ paths from camera data and correlate radiation data with the paths to detect contaminated objects. We evaluated the system using two weak radioactive sources (Co-60, Cs-137), which were hidden on moving objects, and succeeded in finding harmful targets. The results have also shown that by increasing the number of contaminated sources from one to two, the detection accuracy decreases by about 2.5 times. However, by doubling the speed of mobile targets, the detection accuracy improved by about 30%. Detecting and tracking MORC with a single detection system is limited to small regions. By equipping many surveillance cameras in a city with relatively inexpensive radioactive detectors, a network sensing system is established to find radioactive hotspots in a smart city.