1. PewPew Smart Gun Design
The A-Team: Josue Bautista, Liza Chiu,
Ryan Fleming, Hozaifa Jameel

2. US Firearm Statistics Domestic production of firearms
1 million to 2 million handguns
1 million to 1.5 million rifles
fewer than 1 million shotguns.
Firearm imports
2.2 million handguns (2009, after nearly doubling 2001 – 2007)
864,000 rifles (2009)
559,000 shotguns (2009)
2009 estimated total number of firearms available to civilians in the United States had increased to approximately 310 MILLION:
114 million handguns, 110 million rifles, and 86 million shotguns.
In 2008, federal police employed approx. 120,000 full-time law enforcement officers, authorized to make arrests and carry firearms in the United States.
The Bureau of Justice Statistics, Congressional Research Service, “Gun Control Legislation”
Group A: Bautista, Chiu, Fleming, Jameel

3. Gun Violence Statistics
Group A: Bautista, Chiu, Fleming, Jameel

4. Group A: Bautista, Chiu, Fleming, Jameel
Smart Gun Technology
MAIN TYPES
PROS
CONS
ELECTRONIC
(Magnetic Locks, Radio/RFID locks, PIN numbers)
Easy transfer of use (possession of key rather than identity of key holder)
More mechanical (simple operation)
Easy transfer of use
Malfunctions from signal failure
Unsafe storage of device & key together
Temporary memory loss
BIOMETRIC
(Fingerprint, Palmprint, Voice Activation, Grip)
Higher security
Specific to authorized users
More reliable identification
Denial of use
Reliance on technology
Delay of reading
Unreliable reading
Group A: Bautista, Chiu, Fleming, Jameel

5. Group A: Bautista, Chiu, Fleming, Jameel
Proposed Design
Focus on grip redesign
Utilizing existing technology
Layers:
Shape memory alloy
3d printed foam
Grip sensors with integrated GPS
Group A: Bautista, Chiu, Fleming, Jameel

6. Group A: Bautista, Chiu, Fleming, Jameel
Proposed Design
IDENTITY AUTHORIZATION
Utilizes unique DGR biometrics
Increased identity accuracy with additional pattern recognition data
THEFT PREVENTION
Difficulty of replication
Option to refine pattern recognition tolerance for increased security
Integrated GPS with grip sensor panel
SAFETY SUPPORT
Additive manufactured grips with time-released molding materials for comfort
Integrated pressure sensors with viscoelastic materials facilitates increase in safety training hours
Group A: Bautista, Chiu, Fleming, Jameel

7. Biometric Technology Classification of Biometric Modalities
Grip Pattern
Group A: Bautista, Chiu, Fleming, Jameel

8. Dynamic Grip RecognitionTM
Pioneered by NJIT
Researched since 1999
Onboard processor contained inside handgun
Tested by over 160 subjects incl 16 police officers
“Well over 99%” accuracy
16 pressure sensors arranged by fingertip distribution of test subjects
Normalization needed to create patterns
Computer will learn to recognize more patterns in a variety of environmental states
Recognition is first 1/10th of a second of trigger pull and unlocks weapon with no apparent lag to the shooter (will reduce accidental firing)
“The team demonstrated that changes over time to the pressure pattern created on the grip of a handgun as one counter-braces the force of trigger pull were individual to the user, reproducible and measurable.”
Group A: Bautista, Chiu, Fleming, Jameel
Chen, Recce. “Handgrip Recognition,” Journal of Engineering, Computing and Architecture, 1:2 (2007)

9. Group A: Bautista, Chiu, Fleming, Jameel
Fingerprint vs DGR
BIOMETRIC TYPE
PROS
CONS
FINGERPRINT
Unique
Established, best known marker
Additional cross-checking with criminal database (future)
Requires clear scan
Requires bare hands
Requires clean, dry hands (no sweat or dirt)
Can be replicated
DYNAMIC GRIP RECOGNITION
More unique neurophysiologic pattern
Increasingly accurate with use
Hard to replicate
Increased failure rate with multiple users
"It turns out only about one in 10,000 people place their fingers in exactly the same spot and exert precisely the same amount of pressure. It’s not only a reliable identifier, but it’s also harder to defeat,” Kaufman said. “I can defeat fingerprints, because I can take it from something else like a glass … once I’ve done that, all I have to do is override the system by using a mockup of your fingerprint. Because this is a pattern-recognition biometric, it’s harder to defeat.”
--A study on using biometrics for computer mice
Group A: Bautista, Chiu, Fleming, Jameel

10. Additive Manufactured Grips
Shape memory alloys (SMAs) are metals that "remember" their original shapes
Lawrence Livermore National Laboratory (LLNL) material scientists have found that 3D-printed foam works better than standard cellular materials in terms of durability and long-term mechanical performance
“3D printing of foams offers tremendous flexibility in creating programmable architectures, customizable shapes and tunable mechanical response,” said lead author Amitesh Maiti
Time-released high viscoelasticity (like a memory foam pillow)
Integrated pressure sensors with viscoelastic materials contribute to database of grip patterns and facilitates increased hours in safety training
Lawrence Livermore National Laboratory (LLNL)
Group A: Bautista, Chiu, Fleming, Jameel

11. Group A: Bautista, Chiu, Fleming, Jameel
“No technology is foolproof”
- Nancy Ross, representative for the Association of New Jersey Rifle and Pistol Clubs
Group A: Bautista, Chiu, Fleming, Jameel