An environment interference resistant distributed WiFi indoor personnel detection and intelligent control method and system

By constructing a distributed WiFi sensing network and utilizing adaptive notch filtering and decision fusion strategies, the environmental interference and blind spot problems in WiFi indoor personnel detection were solved, enabling real-time, accurate personnel detection and intelligent control on low-cost devices.

CN122373214APending Publication Date: 2026-07-10HEFEI NORMAL UNIV
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Patent Information

Authority / Receiving Office
CN ยท China
Patent Type
Applications(China)
Current Assignee / Owner
HEFEI NORMAL UNIV
Filing Date
2026-03-06
Publication Date
2026-07-10

AI Technical Summary

Technical Problem

Existing WiFi indoor people detection technologies suffer from high false alarm rates in complex dynamic environments and weak static detection capabilities, and also have blind spots, making it difficult to operate in real time on low-cost IoT devices.

Method used

A distributed WiFi sensing network is constructed. Through frequency domain feature analysis and multi-node collaborative decision-making, adaptive notch filtering and decision fusion strategies are used to identify and filter out environmental interference, thereby achieving global awareness of the presence of personnel.

Benefits of technology

Significantly reduces false trigger rate, covers sensing blind spots, enables accurate detection of indoor occupants, supports real-time operation of low-cost devices, and improves user experience and energy efficiency.

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Abstract

This invention discloses a distributed WiFi indoor personnel detection and intelligent control method and system with resistance to environmental interference, relating to the fields of wireless sensing and IoT control. The method includes: sensing nodes collecting CSI sequences, constructing frequency domain features through fast Fourier transform, using an adaptive notch filter algorithm to identify and eliminate periodic interference at specific frequencies, and extracting the non-periodic spectral energy of human breathing and micro-movements; the edge gateway employing a lightweight decision fusion strategy, performing a logical "OR" operation on the local features of multiple nodes, and utilizing spatial diversity to eliminate single-link line-of-sight blind spots and multipath dead zones; the controller constructing a dual-threshold three-state state machine based on CSI statistical features, setting a high trigger threshold to prevent false alarms, a low hold threshold to maintain static detection, and introducing an early warning mechanism. This invention effectively solves the problems of traditional wireless sensing being susceptible to interference in complex dynamic environments and having a high rate of missed static personnel detection, achieving highly robust non-contact personnel detection and energy-saving lighting control.
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Citation Information

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