"We have found no interest on the part of gun manufacturers in commercializing any aspect of user-authenticating weapons," Sebastian said.
For Dynamic Grip Recognition to work, the gun's processor is first placed in learning mode. Then, the user must shoot about 50 rounds to train the weapon to recognize a specific grip. (Multiple users can be saved in the system's memory.)
The Dynamic Grip Recognition software algorithms can also be tuned to be more or less sensitive. For example, a gun could be tuned to only accept an adult's hand profile or one similar to the owner's, while preventing children from being able to use it, Sebastian said.
"If it's a kid, it will probably never be recognized as an authorized user because the physical geometry will never be a match," he said.
One problem with the current prototypes, which use a Beretta 92F 9mm semi-automatic pistol, is that besides the microprocessor, the battery and I/O interface technology used for programing the gun is a decade old and is too cumbersome for mass-market production. For example, the current battery is a 9-volt and the cable is based on either a USB cable or 25-pin RS232 connector that's years behind current technology. If upgraded, guns could be programmed using smart-phone LTE 5G wireless technology, Sebastian said.
While NJIT may be using Beretta pistols to test its technology, the Beretta company has not supported the school's efforts, according to Sebastian.
"We're out of money," he said. "We're able to keep things going for another semester or so, but we're looking at private investment and we'll see if the mood is changing. "...That may bring more investors out of the cold."
NJIT's grip recognition is only one smart gun technology among many available. Others include fingerprint recognition though infrared fingerprint readers and the use of RFID radio chips.
While several technologies can be used to recognize fingerprints, such as infrared, optical scanning and pressure sensors that can determine the grooves of a person's fingerprints, Sebastian argues they're too kludgy to use, and not always reliable.
"At best, we found that they were 75% reliable, and that's under laboratory conditions," he said. "And there are all kinds of ways they can be confused and not work: Dry fingers on capacitor systems cause problems; leaving behind the residue of your finger print can cause problems; cold hands; gloves, no gloves. There are a lot of reasons just as a technology that it is flawed.