Detection of Unauthorized Objects on ATM

A method for detecting unauthorized objects on an automated teller machine (ATM), comprising:

• transmitting, by a LoRa modulator, spread-spectrum modulation signals to a card slot and a keypad of the ATM;
• receiving, by the LoRa modulator, rebounded signal patterns from the card slot and the keypad;
• analyzing, by a sensor infused with a trained algorithm, the rebounded signal patterns to detect any disruptions indicative of unauthorized objects;
• scanning, by a transparent laser-guided system, the ATM card slot to generate a three-dimensional image;
• analyzing, by the trained algorithm, the three-dimensional image for dimensional changes in the ATM card slot;
• detecting, by the sensor, weight distribution and pressure patterns on the ATM keypad during use;
• identifying, by the trained algorithm, anomalies in the weight distribution or pressure patterns indicative of unauthorized keypad overlays;
• determining, by a consensus analysis, the presence of unauthorized objects on or within the ATM based on signal disruptions, dimensional changes, or anomalous weight distribution;
• and
• triggering, by the sensor, an alarm process that includes disabling the ATM and notifying authorities upon detecting unauthorized objects.

A system for detecting unauthorized objects on an automated teller machine (ATM), comprising:

• a LoRa modulator configured to transmit spread-spectrum modulation signals to a card slot and a keypad of the ATM and to receive rebounded signal patterns therefrom;
• a transparent laser-guided system configured to scan the ATM card slot and generate a three-dimensional image;
• a sensor infused with a trained algorithm, the algorithm comprising a deep convolutional neural network (DCNN) and a structural interpretation network (StNet), configured to analyze the rebounded signal patterns and the three-dimensional image to detect dimensional changes in the ATM card slot and disruptions in signal patterns indicative of unauthorized objects;
• a weight sensor configured to detect the weight distribution and pressure patterns on the ATM keypad during user interaction;
• a consensus analysis module configured to determine the presence of unauthorized objects based on signal disruptions, dimensional changes, or anomalous weight distribution;
• and
• a control module configured to initiate an alarm process, including disabling the ATM and transmitting notifications to authorities, upon determining the presence of unauthorized objects.