Gun Use Monitored by Mood Detection
Firearm misuse is rife throughout the world, especially in the USA where gun deaths number in the tens of thousands per annum. Where an outright ban of guns is not feasible, nor is a ban of ammunition, systems are needed that ensure that guns are used for their intended peaceful purpose, eg hunting. This is especially so in jurisdictions, such as Western Europe and Australasia, where the use of guns in self-defence may not constitute a legal defence against a criminal prosecution for manslaughter. Also in these jurisdictions often the licensing of firearms is restricted to specific functions, such as hunting or rifle-range activities, and the use of guns for other purposes is expressly banned.
There has been much focus on the use of biometrics to ensure that the user of a gun is the licensed or qualified individual and that other users cannot use the firearm because their biometrically measured data does not match that in the gun. This invention is where, rather than using biometrics to identify the user, the biometric data is used to determine the mood of the user, and is then further used to limit the functionality of the gun subject to the detected mood. This would be used in circumstances where the lawful use of the gun is solely for peaceful purposes such as hunting and rifle-range activities and to prevent the use of a gun where the mood detected is, for example, anger, over-excitement, panic and the like.
Human emotions can
1. cause affective experiences such as feelings of arousal and (dis)pleasure;
2. generate cognitive processes; e.g., emotionally relevant perceptual effects, appraisals, labeling processes;
3. activate widespread physiological adjustments to arousing conditions; and
4. lead to behavior that is often expressive, goal directed, and adaptive.
People's emotional state can be accessed through processing data with algorithms from their biometric signals measured using sensors. These signals can be assigned to two groups:
1. A broad range of physiological measures signals and
2. Specialized areas of signal processing: speech processing, movement analysis, and computer vision techniques
The exact measurement methods that can be measured with biometric sensors and processed to determine mood include speech processing, movement analysis, eye monitoring, face monitoring, ECG, sweat detection, skin and body temperature, and others. Examples are given in US 2010/0332842 A1.
The technology of this invention involves the use of appropriate sensors to measure one or more biometric signal which is then processed by computer software to determine the likely mood of the person holding or in control of a gun. This mood is matched with the "allowed" moods for gun discharge and the function of the gun is then controlled and or modified as is appropriate - this can include preventing discharge, preventing re-loading, preventing full automatic mode and the like.
The biometric sensors can be built into the gun, eg ECG or sweat and temperature sensors, or external to the gun, eg a smartphone camera used to monitor eye and faces of the users, or a special piece of external hardware that contains one or more sensors, or any combination of these. These are known as the "local" devices.
The computer code can be processed in a computer chips resident in the gun, or resident in a third party device, such as a smartphone or the special piece of external hardware that contains one or more biometric sensors, or in the cloud where at least one of the local has internet access.
The various local devices, if there is more than one in the gun, that contain the sensors and possibly also the computer capability can communicate wirelessly with each other and can also if required communicate via the internet, where for example external cloud databases can monitor user mood, and/or enable external control of the gun, whereby computer algorithms or human operators, eg government operatives, can enable or disable automatic gun control systems as that described here.
Mood monitoring combined with gun usage data can be used to fine tune the algorithms controlling gun use. This data can also be used to determine whether the mood control of gun use is appropriate and is working. The data may also be used to determine individuals at high risk of inappropriate gun use by mood monitoring when they are not using their firearms.