4th Annual Biometric "Hits of the Year"


2019 Biometric Identification Hit of the Year Award Nomination-Latent/Palm/Finger Print

On Monday, June 10,2019, Los Angeles County Sheriff Deputy Joseph Solano walked into the fast-food restaurant, "Jack-in-the Box," to order food. He was off-duty at the time and was wearing plain clothes. Deputy Solano was shot and killed by a man inside the restaurant. According to Sheriff Villanueva, "Deputy Solano was alerted in the restaurant that someone was following him and that's when he turned around to confront it. In a split second he lost his life." The suspect is also suspected of murdering another man in the Los Angeles area, just an hour prior to this incident. Several Forensic Identification Specialists (FIS) from the LASD Crime Lab, responded to process the crime scene at the "Jack in the Box" in the city of Alhambra. Several latent prints were lifted from various locations and transported back to the Crime Lab for entry into the Multimodal Biometric Identification System. Forensic Identification Specialist Scott Purcell was assigned the case. FIS Purcell input various latent prints in the local (LASD), state (DOJ), and federal (FBI NGI) databases. The local and state databases did not yield a hit. However, soon after, FIS Purcell received a hit in the FBI database. He entered additional prints in the case and received additional hits to the same subject, Rhett Nelson. These hits came from three different locations and areas which magnifies the strength and corroboration of the evidence. While FIS Purcell was running the various latent prints, LASD detectives arrested the suspect, Rhett Nelson, after he called his father in Utah and confessed to having killed someone in Southern California. A resident of St. George, Utah, Nelson left his Utah home in May and told his family that he planned to "make it on his own or die."

FIS Purcell, a seasoned AFIS examiner, is being nominated for the Biometric Identification Hit of the Year Award for his dedication to this case, for his knowledge of NEC's MBIS system, and for his technical ability in marking minutiae and conducting on-screen comparisons. Thank you, FIS Purcell and NEC’s IBW-5 Multimodal Biometric Identification System!!

2019 Biometric Identification Hit of the Year Award Nomination-Facial Recognition

Forensic Identification Services of the Toronto Police Service, after completing extensive research and a year-long pilot project, purchased an NEC Facial Recognition System in March of 2018. Through the utilization of our system, we have achieved tremendous success in identifying 'potential candidates', leading to the positive identification of criminal offenders, responsible for multiple and major criminal offences, including homicides, sexual assaults, robberies, firearm offences, human trafficking, and largescale financial crimes. We have also achieved significant success in assisting other police services in identifying 'potential candidates' responsible for other major criminal offences including homicides. This has all been accomplished while keeping strict adherence to our lawful Service procedures, and addressing all privacy concerns. The only images that are contained in our comparison database, are those of individuals that have been arrested for indictable (more major) criminal offences.

Our NEC system has not only been successful in identifying 'potential candidates' leading to the positive identification of major criminal offenders, it has also assisted us in identifying previously unknown crime victims. One such case is particularly noteworthy.

Between 2010 and 2017, a number of men, who were known to frequent the downtown area of Toronto, disappeared. Over time, the majority of these men were reported as missing to the Toronto Police Service, and a number of police investigations, including two major projects were conducted. In January 2018, these investigations concluded with the arrest of a 66-year-old male on multiple first-degree murder charges. At the time of his arrest, the accused male was found to have forcibly confined another male, another highly potential homicide victim, in his residence. This male was saved from further indignities and harm.

During the continuing police homicide investigation, the individual details of these homicides were learned to be particularly gruesome, and involved indignities to, dismemberment of, and hiding of the human remains. In addition, the accused kept photographs of some of his victims, on his computer, as trophies. One such photograph, an apparent post-mortem photograph of another Victim, was of an unknown and not previously reported missing male. Unfortunately, this photograph was not of sufficient quality to lead to a 'potential candidate' through our facial recognition system.

With the assistance of our Toronto Police Service forensic artist, components of this photograph were utilized to create a restorative drawing. This drawing was subsequently searched through our NEC Facial Recognition System, and a good quality 'potential candidate' was selected. Through follow up investigations, this 'potential candidate' was positively identified, and added to the list of homicide victims. In January 2019, the accused serial killer was convicted of eight counts of first-degree murder, including the most recently identified homicide victim, and was sentenced to life in prison.

The identity of the previously unidentified homicide victim, and his inclusion as one of the serial killer's convictions, was of great assistance in bringing closure to the victim's family. It also clearly demonstrated to us not only the highly successful benefits of our NEC Facial Recognition System in identifying 'potential candidate' criminal offenders, but that it also has other significant importance, such as selecting 'potential candidates' of previously unidentified crime victims. We cannot imagine conducting a criminal investigation without the benefits of conducting facial recognition system searches when required, any more than we can imagine not conducting fingerprint or DNA searches of crime scenes.