System and method smart stand-alone multi-sensor gateway for detection of person-borne threats
A system and method for a smart stand-alone multi-sensor gateway for detection of person-borne threats. The multi-sensor gateway system consists of two pillars comprising a plurality of sensors that build a gateway for patrons to pass through that detects concealed threats carried on-body. The threat detection relies on artificial intelligence (AI) to analyze the sensors' data and assess the presence of a threat. The AI is performed on an edge device contained within the gateway. The gateway can consist of a plurality of peripherals that enhance the sensing capability of the gateway, such as a camera or an accelerometer, and provide the security guard with information around alerts and threat locations such as with displays or audible alerts and manage the operations such as displays to control throughput.
1 . A stand-alone multi-sensor gateway system for detection of a person-borne threat comprising:
a first pillar and a second pillar spaced apart to define a passageway;
a plurality of first sensors on the first pillar and a plurality of second sensors on the second pillar, the sensors including at least one magnetic sensor and at least one optical break-beam sensor;
an integrated camera mounted on at least one of the pillars;
a Wi-Fi® module on at least one of the pillars, configured for peer-to-peer wireless communication between the pillars;
a display screen mounted on the first pillar and a second display screen mounted on the second pillar, wherein:
the first display screen is configured to face incoming patrons and display a screen state selected from a group consisting of: a READY state, a SCAN state, a PASS state, and an ALERT state; and
the second display screen is configured to face security personnel and display alert information including a visual indication of a detected threat;
an edge computing device housed within one of the pillars, comprising a processor configured to:
receive sensor and camera data;
perform threat detection using embedded artificial intelligence models locally, without reliance on a remote server;
trigger a change in the screen state based on the threat detection result; and
transmit alert data wirelessly to a security system.
2 . The system of claim 1 wherein the person-borne threat further comprises detection of weapon consisting of a knife, gun and bat.
3 . The system of claim 1 wherein the plurality of first and second sensors selected form list consisting of a magnetic sensor, an optical break-beam sensor and a static magnet array sensor.
4 . The system of claim 1 wherein the multi-sensor gateway further comprising a power supply.
5 . The system of claim 1 wherein the platform server and processor further comprises processing modules selected from a list consisting of machine learning models, data acquisition module, ML classification module, table user interface and enterprise functionality modules.
6 . The system of claim 1 further comprising a screen kiosk, the screen kiosk consisting of a tablet and configured to display the screen state.
7 . The system of claim 1 wherein the screen state further comprises displaying different images and icons on the first and second pillar providing information on the screening status.
8 . The system of claim 1 further comprising a divestment table for patrons to place items for security to check.
9 . The system of claim 1 wherein when the person borne-threat is detected, an alert or notification is sent to security and an alarm is triggered.
10 . The system of claim 1 wherein artificial intelligence (AI) analysis and processing is performed on edge device on the multi-sensor gateway.
11 . The system of claim 1 wherein the multi-sensor gateway further comprises enhanced sensing capability, configured to support cameras and accelerometer sensors.
12 . The system of claim 1 wherein artificial intelligence (AI) analysis and processing is performed on edge device on the multi-sensor gateway.
13 . The system of claim 1 wherein the multi-sensor gateway further comprises enhanced sensing capability, configured to support cameras and accelerometer sensors.
14 . The system of claim 1 , wherein the second display screen includes a human avatar visualization indicating the approximate location of the detected threat on the patron's body.
15 . The system of claim 1 , further comprising an audible alert mechanism configured to emit different tones based on severity level of the detected threat.
16 . The system of claim 1 , wherein the sensors are calibrated to define at least three vertical detection zones corresponding to different body regions.
17 . The system of claim 1 , wherein the edge computing device is further configured to calculate and display a throughput efficiency score based on patron processing time.
18 . A method of detecting person-borne threats using a stand-alone multi-sensor gateway system, the method comprising the steps of:
providing a first pillar and a second pillar spaced apart to define a passageway;
providing a plurality of first sensors on the first pillar and a plurality of second sensors on the second pillar, the sensors including at least one magnetic sensor and at least one optical break-beam sensor;
providing an integrated camera on the first or second pillar;
providing a Wi-Fi® module on the first pillar configured for the pillars to communicate over Wi-Fi®;
providing a display screen on the first pillar and second pillar for displaying a plurality of screen states wherein:
the first display screen is configured to face incoming patrons and display a screen state selected from a group consisting of: a READY state, a SCAN state, a PASS state, and an ALERT state; and
the second display screen is configured to face security personnel and display alert information including a visual indication of a detected threat;
an edge computing device housed within one of the pillars, comprising a processor configured to:
receive sensor and camera data;
perform threat detection using embedded artificial intelligence models locally, without reliance on a remote server;
trigger a change in the screen state based on the threat detection result; and
transmit alert data wirelessly to a security system.
19 . The method of claim 18 further comprising the step of instructing patron to a divestment table to divest objects after walking through first and second pillars.
20 . The method of claim 18 further comprising the step of instructing patron to a screen kiosk and capturing additional image of patron and displaying screen state on screening kiosk.
21 . The system of claim 18 wherein the platform server and processor further comprises processing modules selected from a list consisting of machine learning models, data acquisition module, ML classification module, table user interface and enterprise functionality modules.