RF Presence Alert System Using Ambient IoT Signals
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Solution Overview
Problem
Existing radio frequency presence alert systems rely on specific device deployments for generating and sampling RF fields, leading to high deployment costs and issues with false alarms from movements outside the area of interest.
Innovation Solution
A presence alert system that leverages ambient RF signals from pre-deployed wireless IoT devices, using a sniffer to measure signal characteristics, machine learning algorithms to determine motion within a defined area of interest, and a software program to differentiate between actual and false alarms.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If specific wireless nodes/transceivers are deployed for RF field generation and sampling, then presence detection capability is improved, but deployment cost increases
Solution Approach 1:
The patent applies multi-functionality by enabling existing wireless devices (routers, access points, IoT devices) to serve dual purposes: their original communication functions plus presence detection. The RF sniffer repurposes ambient RF signals meant for data transmission into presence detection signals, eliminating the need for dedicated detection hardware and reducing deployment costs while maintaining detection capability
Solution Approach 2:
The system applies self-service by using the RF signals already being transmitted by wireless devices for their primary communication purposes. These same signals are captured by the RF sniffer for presence detection, allowing the existing infrastructure to serve itself for dual functions without requiring additional specialized devices or increasing deployment costs
2Reliability
If traditional motion sensors are deployed at entrance points, then intrusion detection capability is improved, but coverage area is limited
Solution Approach 1:
The patent transitions from spatial positioning (placing sensors at specific physical locations like entrances) to utilizing the electromagnetic dimension. RF signals propagate through three-dimensional space and can be detected throughout the entire coverage area of wireless devices, enabling presence detection throughout the entire building rather than only at sensor deployment points
3Measurement precision
If RF sniffing is performed continuously, then presence detection accuracy is improved, but energy consumption increases
Solution Approach 1:
The system implements periodic action by performing RF signal sampling at intervals rather than continuously. The RF sniffer captures RF signals at periodic time points, and the software program processes these periodic samples to detect presence. This periodic sampling approach maintains detection accuracy by capturing sufficient temporal variations in RF signals while significantly reducing energy consumption compared to continuous monitoring
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
The system provides efficient intrusion detection with reduced deployment costs and minimizes false alarms by utilizing existing wireless devices and machine learning to identify meaningful RF variations within specific areas.
Implementation Method 1
motion and/or presence sensing techniques that exploit changes in the radio frequency electromagnetic fields (i.e., often called RF fields) generated by wireless devices
Implementation Method 2
a transmitting component configured to transmit a radio frequency (RF), and a receiving component configured to receive the RF
Data Source
AI summary
A presence alert system (24) includes a sniffer (36), controller-circuitry (38), radio frequency (RF) background data (40), and a software program (42). The sniffer is configured to sample and measure a characteristic of ambient RF signals (33) over time. The controller-circuitry includes one or more processors and one or more storage mediums. The RF background data is stored in at least one of the one or more storage mediums, and is indicative of no moving presence. The software program is stored in at least one of the one or more storage mediums, and is executed by at least one of the one or more processors. The software program is configured to evaluate the measured characteristic of the ambient RF signals, compare the measured characteristic to the RF background data, and thereby determine motion of a presence (34).