Router device and system with earthquake early warning, broadcast alerting

Abstract

The application relates to the fields of earthquake early warning and Internet of Things, and discloses a router device and system with earthquake early warning and broadcast alarm, wherein the device comprises a router body, a main control processor, a LoRa module, a MEMS sensor, a buzzer, an indicator light and the like, and the system comprises early warning information receiving, emergency network management, distributed sensing, cross verification and decision and local device linkage modules. The early warning receiving module obtains early warning information through the Internet and the LoRa module, the emergency network module constructs a mesh network, manages nodes and routes emergency broadcast packets, the distributed sensing module collects vibration data, generates environmental noise fingerprints, constructs a regional dynamic baseline, the cross verification module verifies the validity of early warning, drives sound and light alarms, and the local linkage module links local area network devices through UDP broadcast or control. The application improves the reliability, accuracy and response speed of early warning through multi-path, emergency mesh network and dynamic baseline physical verification.

Description

Technical Field

[0001] This invention relates to the fields of earthquake early warning and Internet of Things (IoT) technology, specifically to a router device and system with earthquake early warning and broadcast alarm functions. Background Technology

[0002] Current earthquake early warning systems face numerous challenges in practical applications. On the one hand, the transmission of existing early warning information relies heavily on public communication networks, such as the internet or cellular networks. However, during disasters such as earthquakes, these public networks are highly susceptible to damage or congestion, preventing early warning information from being delivered to target users in a timely and reliable manner. This over-reliance on a single transmission path reduces the overall resilience of the early warning system, especially during the most critical moments of the disaster.

[0003] On the other hand, many existing earthquake monitoring or alarm devices often use fixed vibration thresholds for judgment. In real-world applications, the environment in which these devices operate is complex and variable. Non-seismic vibrations generated in daily life, such as traffic noise, construction activities, or indoor human activity, frequently trigger alarms, leading to a high false alarm rate. If the threshold is increased to avoid false alarms, it is easy to miss weak earthquake precursors or early P-wave signals, thus affecting the timeliness and accuracy of early warnings.

[0004] Furthermore, existing local alarm methods are typically limited to audible and visual alerts from a single device. This localized approach makes it difficult to ensure that all occupants can perceive the alarm in a timely manner, especially in large spaces or multi-room environments. Simultaneously, the lack of effective linkage mechanisms with smart home devices or other IoT terminals fails to fully leverage the role of early warning systems in guiding risk avoidance and mitigating losses. Summary of the Invention

[0005] To address the shortcomings of existing technologies, this invention provides a router device and system with earthquake early warning and broadcast alarm functions. It solves the problems of existing earthquake early warning technologies, such as the single information transmission path which is easily interrupted during disasters, the susceptibility of vibration signal discrimination to environmental noise interference leading to insufficient accuracy, and the limited range of local alarm linkage.

[0006] The first aspect of this invention provides a router device with earthquake early warning and broadcast alarm functions, comprising: The router body has a built-in main control processor, an antenna installed on the rear side of the router body, a LoRa wireless module installed in the middle of the router body, an emergency power supply and a MEMS accelerometer installed inside the router body, and a buzzer and indicator lights installed on the front side of the router body.

[0007] A second aspect of the present invention provides a router system with earthquake early warning and broadcast alarm functions. The system is applied to the aforementioned router device and includes: an early warning information receiving module, an emergency network management module, a distributed environmental perception module, a cross-validation and decision-making module, and a local device linkage module.

[0008] The early warning information receiving module is configured to receive earthquake early warning information through two paths. The main path receiving unit obtains authoritative early warning information via the internet. To address scenarios where the main network is interrupted, a bypass receiving unit is provided. This unit receives emergency broadcast packets from other nearby router devices via a LoRa wireless module, thereby establishing an early warning information channel independent of the public internet.

[0009] The emergency network management module is responsible for building and maintaining a decentralized emergency mesh network composed of multiple router devices. This module first analyzes the connection status of the local area network to which the device is connected through its network topology analysis unit, generating a local network load profile reflecting the current communication pressure. Subsequently, the dynamic role allocation unit assigns one or more role labels to the device within the emergency mesh network based on this profile and broadcasts them via a LoRa wireless module. The emergency routing decision unit is responsible for identifying other router devices within communication range as neighbor nodes and receiving their broadcast role labels. When it is necessary to forward emergency broadcast packets, this unit combines the role labels of neighbor nodes and the propagation status of the emergency broadcast packet to select the next-hop node for data forwarding, thus routing the emergency broadcast packet within the emergency network.

[0010] The distributed environmental sensing module is used to sense and quantify the vibration background of the environment in which the device is located. Its environmental noise acquisition unit drives the MEMS accelerometer to continuously collect raw vibration data. This data is processed by an environmental noise feature extraction formula, which aims to extract features from the waveform to generate a local environmental noise fingerprint that represents the current environmental vibration level. To avoid misjudgments caused by local environmental interference from a single node, the distributed baseline learning unit exchanges its local environmental noise fingerprints with neighboring nodes via a LoRa wireless module. Subsequently, this unit applies a baseline calculation formula to fuse and smooth the local and received fingerprint data, thereby calculating and continuously updating a regional dynamic environmental noise baseline that reflects the overall vibration level of the area.

[0011] The cross-validation and decision-making module is used to verify early warning information to improve accuracy. When an emergency broadcast packet is received from the bypass path, this module initiates the physical verification process. The dynamic threshold generation unit intervenes first, calculating a dynamic verification threshold based on a threshold calculation formula. This formula multiplies the real-time updated regional dynamic environmental noise baseline by a preset sensitivity coefficient and adds a preset base offset. The preset sensitivity coefficient is pre-set based on empirical data distinguishing weak seismic P-wave signals from everyday background noise, while the preset base offset is pre-set based on the minimum threshold for validity. Simultaneously, the physical vibration verification unit is activated, driving the MEMS accelerometer to collect real-time vibration data within a very short time window. This data is then processed using a vibration feature extraction formula to generate a quantified real-time vibration feature value. Finally, the decision logic unit compares this real-time vibration feature value with the dynamically generated verification threshold. If the feature value exceeds the threshold, the early warning information is deemed valid; otherwise, it is deemed invalid, thus filtering out false alarms caused by signal mistransmission or environmental noise. Once a valid warning is detected, the unit issues a start command, activates the buzzer and indicator lights to trigger an audible and visual alarm, and notifies the emergency network management module and the local device linkage module.

[0012] The local device linkage module is responsible for transmitting early warning information to end-user devices. Upon receiving a valid early warning command from the cross-validation and decision-making module, this module generates a specific UDP broadcast packet containing the early warning information and broadcasts it to devices within the local area network to which the device is connected. Furthermore, for smart home devices supporting compatible protocols, this module can also directly control these devices to perform linkage actions by calling their application programming interfaces (APIs).

[0013] This invention provides a router device and system with earthquake early warning and broadcast alarm functions. It has the following beneficial effects: 1. This invention adopts a dual-path early warning information acquisition method by setting up the Internet main path reception and LoRa wireless module bypass reception, and uses multiple devices to build an emergency mesh network. This design can still transmit early warning information through the self-organizing network between devices when the public communication network is interrupted or congested due to disasters, which solves the reliability problem of a single information source and improves the success rate of early warning information transmission in extreme situations.

[0014] 2. This invention collects and exchanges environmental noise fingerprints of each node through a distributed environmental sensing module to construct a regional dynamic environmental noise baseline, and dynamically generates a verification threshold based on this baseline. This method can effectively distinguish between local, non-seismic environmental vibrations and real seismic P-wave signals, avoid false alarms caused by sudden changes in environmental noise of a single node, and improve the accuracy of early warning judgment.

[0015] 3. This invention includes a local device linkage module. After confirming a valid warning, it can trigger smart home devices to respond in a coordinated manner within the local area network by broadcasting or calling APIs. This expands the sound and light alarm of a single device into a multi-device, multi-form alarm throughout the house, enhancing the reminder effect to users and providing technical means for automated emergency response. Attached Figure Description

[0016] Figure 1 This is a three-dimensional schematic diagram of a router device with earthquake early warning and broadcast alarm functions according to an embodiment of the present invention; Figure 2 This is a side view of a router device with earthquake early warning and broadcast alarm functions according to an embodiment of the present invention; Figure 3 This is a cross-sectional structural diagram of the router body of a router device with earthquake early warning and broadcast alarm according to an embodiment of the present invention; Figure 4 This is a diagram illustrating the architecture of a router system with earthquake early warning and broadcast alarm functions, as described in an embodiment of the present invention. Figure 5 This is a flowchart illustrating the overall workflow of a router system with earthquake early warning and broadcast alarm functions, as described in an embodiment of the present invention. Figure 6 This is a flowchart of the decision-making process of the cross-validation and decision-making module in an embodiment of the present invention.

[0017] The components include: 1. Router body; 2. Antenna; 3. LoRa wireless module; 4. MEMS accelerometer; 5. Buzzer; 6. Indicator light; 7. Emergency power supply; 10. Early warning information receiving module; 20. Emergency network management module; 30. Distributed environmental perception module; 40. Cross-validation and decision-making module; and 50. Local device linkage module. Detailed Implementation

[0018] The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0019] Please see the appendix Figure 1 -Appendix Figure 4The present invention first provides a router device with earthquake early warning and broadcast alarm, including: a router body 1, a main control processor built into the router body 1, an antenna 2 installed on the rear side of the router body 1, a LoRa wireless module 3 installed in the middle of the router body 1, an emergency power supply 7 and a MEMS accelerometer 4 installed inside the router body 1, and a buzzer 5 and an indicator light 6 installed on the front side of the router body 1.

[0020] Specifically, the router body 1 is usually made of industrial-grade plastic or metal materials to ensure that the device has good structural strength and electromagnetic compatibility. It also reserves necessary external interfaces, such as Ethernet ports and power interfaces, for the device's regular network functions and power supply.

[0021] The main control processor is the core processing unit of the device, responsible for carrying all system software functions and various network management tasks of traditional routers. The main control processor is usually a high-performance embedded processor, such as a multi-core CPU based on the ARM architecture, which has sufficient computing power and storage resources.

[0022] The main control processor integrates multiple communication interfaces, such as SPI, I2C, UART and GPIO, for data exchange and control with the hardware within the router device.

[0023] Antenna 2 typically employs an omnidirectional design to ensure uniform signal coverage in the horizontal direction. LoRa wireless module 3 integrates an RF transceiver chip, a microcontroller, and a baseband processing circuit, supports LoRa modulation technology, and can operate in unlicensed spectrum, such as the 868MHz band in Europe, the 915MHz band in North America, or the 433MHz band in Asia. The transmit power of LoRa wireless module 3 is configurable to adapt to different transmission distances and regulatory requirements, while also having high receive sensitivity, enabling it to capture weak long-distance signals.

[0024] The microcontroller inside the LoRa wireless module 3 is responsible for handling the LoRa protocol stack, including packet encapsulation and decapsulation, spreading factor setting, code rate selection, and CRC check. The LoRa wireless module 3 communicates with the main control processor through a digital interface, such as a UART or SPI interface.

[0025] MEMS accelerometer 4 uses microelectromechanical systems (MEMS) technology and integrates a triaxial accelerometer, which can measure acceleration components in the X, Y, and Z directions in real time.

[0026] The measurement range, resolution, and noise density of the MEMS accelerometer sensor 4 were selected to meet the requirements for accurate detection of weak vibration signals such as seismic P-waves. For example, a sensor with high resolution (such as 12-bit or 16-bit) and low noise characteristics was selected to distinguish between ambient background noise and actual seismic vibrations.

[0027] The MEMS accelerometer 4 connects to the host processor via a digital interface, such as I2C or SPI. The host processor can configure the operating parameters of the MEMS accelerometer 4, such as the sampling rate and data output rate, and periodically or on demand read the sensor's raw vibration data. The MEMS accelerometer 4 integrates an analog-to-digital converter (ADC) to convert the analog acceleration signal into a digital signal output.

[0028] The buzzer 5 and the indicator light 6 together constitute the local audible and visual alarm unit of the router device, which is used to send a direct, localized warning signal to the user after confirming the warning.

[0029] Buzzer 5 is preferably a piezoelectric buzzer, with a sound pressure level selected to ensure sufficient intensity to produce an alarm sound in a typical indoor home or office environment, for example, a sound pressure level of no less than 85 decibels at 1 meter. Its frequency is set within the range most sensitive to the human ear, such as 2 kHz to 4 kHz. The main control processor can drive buzzer 5 to emit continuous or intermittent beeps with a specific rhythm through a general-purpose input / output interface (GPIO) according to preset alarm modes to convey warning information.

[0030] Indicator light 6 is preferably a high-brightness light-emitting diode (LED), typically red in color to conform to general warning standards. When an alarm is triggered, the main control processor also controls indicator light 6 to flash at a high frequency via the GPIO interface. This visual signal works in sync with the audible signal of buzzer 5, creating a multimodal alarm effect and enhancing the effectiveness of the warning, especially in noisy environments or when the user is asleep, where a single signal may be difficult to perceive.

[0031] Emergency power supply 7 is used to provide short-term independent power supply for the core early warning function of the device in the event of an interruption of external mains power supply, ensuring that the device can still receive, verify and alarm early warning information at the moment of power failure.

[0032] Emergency power supply 7 can be composed of supercapacitors or small-capacity rechargeable lithium batteries. Its capacity selection should be based on the ability to support the core early warning components to continue working for a preset time (e.g., tens of seconds to several minutes) after a power outage.

[0033] The emergency power supply 7 integrates a dedicated power management integrated circuit (IC). When the mains power supply is normal, the IC is responsible for charging and maintaining the energy storage components. When the mains power is detected to be interrupted, it automatically and uninterruptedly switches the power supply mode to the backup power output.

[0034] Please see the appendix Figure 4 -Appendix Figure 6 This invention also provides a router system with earthquake early warning and broadcast alarm functions. The router system is built into the main control processor and includes: an early warning information receiving module 10, an emergency network management module 20, a distributed environmental perception module 30, a cross-validation and decision-making module 40, and a local device linkage module 50.

[0035] The early warning information receiving module 10 is used to acquire early warning information from different channels. It includes a main path receiving unit and a bypass receiving unit. The main path receiving unit communicates with the official early warning server via an internet interface to receive authoritative early warning information. The bypass receiver unit drives the LoRa wireless module 3 to receive emergency broadcast packets forwarded by other nodes in the event of an internet outage. .

[0036] The emergency network management module 20 is used to build and maintain an emergency communication network between nodes. It includes a network topology analysis unit, a dynamic role allocation unit, and an emergency routing decision unit. The network topology analysis unit analyzes the connection status of the local area network of this router device and generates a local network load profile. The dynamic role assignment unit assigns role tags to this router device based on the profile. The emergency routing decision unit determines the routing based on the role labels of neighboring nodes. Based on network conditions, select the optimal path to forward emergency broadcast packets.

[0037] The distributed environment sensing module 30 is used for collaborative learning of the background vibration characteristics of the regional environment. It includes an environmental noise acquisition unit and a distributed baseline learning unit. In non-alarm states, the environmental noise acquisition unit periodically drives the MEMS accelerometer 4 to acquire raw vibration data. The environmental noise fingerprint was calculated using the environmental noise feature extraction formula. The formula for extracting environmental noise features is: ; In the formula: The calculated environmental noise fingerprint; For example, a preset feature extraction function, such as calculating the root mean square value of a signal; The raw vibration data was acquired from MEMS accelerometer 4. This is the start time of data collection; This represents the duration window for data acquisition.

[0038] The distributed baseline learning unit exchanges its environmental noise fingerprints with neighboring nodes via the LoRa wireless module 3. And based on the baseline calculation formula, the dynamic environmental noise baseline of a region is continuously updated. The baseline calculation formula is: ; In the formula: In time Calculated regional dynamic environmental noise baseline; For the current router device The set of neighboring nodes; To assign to neighboring nodes The weights; To the neighbor node Received environmental noise fingerprint; This refers to the delay time between communication and processing. This is the summation symbol.

[0039] The cross-validation and decision module 40 is used to physically verify the received warning information and make a final decision. It includes a dynamic threshold generation unit, a physical vibration verification unit, and a decision logic unit.

[0040] The dynamic threshold generation unit is based on the regional dynamic environmental noise baseline. A verification threshold is generated in real time using a threshold calculation formula. The threshold calculation formula is: ; In the formula: In time The generated dynamic verification threshold; This is the preset sensitivity coefficient; This is the preset base offset.

[0041] Upon receiving the warning information, the physical vibration verification unit immediately drives the MEMS accelerometer 4 to collect real-time vibration data. The real-time vibration characteristic values ​​were calculated using the vibration feature extraction formula. The vibration feature extraction formula is as follows: ; In the formula: These are the calculated real-time vibration characteristic values; The same feature extraction function is used as that used in the environmental noise acquisition unit; This refers to vibration data collected in real time. The moment the warning information was received; This is a short time window used for verification.

[0042] The decision logic unit will use real-time vibration characteristic values With verification threshold Compare. If Greater than If the warning is valid, a start command will be generated.

[0043] After receiving the start command, the local device linkage module 50 sends control information to other smart devices (such as smart speakers, TVs, etc.) in the local area network to trigger these devices to perform coordinated alarms.

[0044] The early warning information receiving module 10 is designed to provide reliable early warning information input with redundant paths for the entire system. This module includes a main path receiving unit and a bypass receiving unit, which operate in parallel to ensure that early warnings can be obtained under different network conditions.

[0045] The main path receiving unit is responsible for obtaining authoritative early warning information via the high-speed Internet. When the device is connected to the network normally, the main path receiving unit establishes an encrypted long connection based on the Transmission Control Protocol (TCP) with the officially designated early warning information publishing server through the wide area network (WAN) interface of the router device, for example, using Transport Layer Security (TLS) for channel encryption.

[0046] To maintain the connection's activity and quickly detect disconnections, a heartbeat mechanism exists between the main path receiving unit and the server. When a warning message is received from the server... Upon receiving a data packet, the main path receiving unit first verifies the digital signature of the data packet to confirm the authority and completeness of the information source. After successful verification, the data packet is parsed to extract key early warning fields, including event ID, epicenter location, estimated magnitude, estimated arrival time of P-wave, and estimated arrival time of S-wave. The structured early warning data is then submitted to the subsequent cross-validation and decision-making module 40.

[0047] The bypass receiver unit is responsible for acquiring early warning information via a low-power wireless ad hoc network in the event of an internet connection interruption or unavailability. This unit interacts with the LoRa wireless module 3. In system standby mode, the bypass receiver unit instructs the LoRa wireless module 3 to operate in a low-power channel monitoring mode. When it detects an emergency broadcast packet from another node in the network... At that time, LoRa wireless module 3 will report the received data.

[0048] The bypass receiving unit first performs a Cyclic Redundancy Check (CRC) on the data packet to ensure data integrity during transmission. After the check passes, the bypass receiving unit decrypts the data packet payload and parses out simplified core warning fields, such as the event ID and the estimated arrival time of the P-wave. To prevent information from being repeatedly broadcast in the network, the bypass receiving unit determines whether the warning is a duplicate based on the event ID. After confirming that it is a new and valid warning, the unit also submits the parsed warning data to the cross-validation and decision module 40.

[0049] The emergency network management module 20 is designed to enable intelligent management and efficient operation of the LoRa wireless ad hoc network, aiming to utilize limited emergency channel resources for the transmission of critical early warning information. This module senses the local area network service status of the router device, assigns a dynamic role to the router device within the ad hoc network, and executes adaptive routing strategies accordingly. Logically, this module includes a network topology analysis unit, a dynamic role allocation unit, and an emergency routing decision unit.

[0050] The network topology analysis unit periodically performs status assessments on the local area networks (including wired Ethernet and wireless Wi-Fi networks) served by this router device to generate a local network load profile that can quantitatively describe the current network service environment. .

[0051] To generate this profile, the network topology analysis unit obtains a series of key performance indicators by querying the network protocol stack status table inside the main control processor.

[0052] First, obtain the number of currently connected devices. This data can be obtained by querying the address lease list or the Address Resolution Protocol (ARP) cache table of the Dynamic Host Configuration Protocol (DHCP) server.

[0053] Secondly, analyze the distribution of connection device types. This analysis can initially determine the device manufacturer by parsing the Organization Unique Identifier (OUI) of the device's MAC address, or identify specific device types such as webcams and smart speakers by monitoring the traffic patterns of specific ports.

[0054] Third, calculate the average network traffic load over a period of time. This data is calculated by counting the total number of bytes entering and leaving the network interface controller (NIC) within a preset time window.

[0055] The network topology analysis unit integrates the collected and calculated data from multiple dimensions into a structured local network load profile. Data object. This profile is updated in real time and transmitted to the dynamic role allocation unit as the direct basis for its role determination.

[0056] The dynamic role allocation unit receives the local network load profile generated by the network topology analysis unit. Based on this profile, a clear role label is assigned to this router device in the emergency self-organizing network. .

[0057] This dynamic role allocation unit has a pre-set set of judgment rules used to map input quantitative indicators to specific roles. For example, when a local network load profile is used... Number of connected devices When the density exceeds a preset high-density threshold, the unit will assign a role label to this router device. Set as a high-density node. Conversely, if the number of connected devices is low... If the density is below a preset low-density threshold, it is set as an isolated node.

[0058] In addition, if the average network traffic load If the network traffic remains below a preset low-traffic threshold, it indicates that the device's local area network communication load is relatively light, making it suitable for undertaking more emergency network relay tasks. In this case, the dynamic role allocation unit can assign role tags. It is designated as a critical communication node. If no specific rule is met, it is assigned the default role of a standard node. These thresholds are configurable parameters stored in the device's non-volatile memory.

[0059] After completing the role determination, the dynamic role allocation unit will update the role tags. This information is transmitted internally within the system for use by the emergency routing decision unit. Simultaneously, this unit periodically instructs the LoRa wireless module 3 to send a message containing the router's device ID and current role tag. The status information packet is broadcast to the surrounding area. This status information includes a timestamp to ensure the accuracy and freshness of neighboring nodes updating their local neighbor node tables, so that neighboring nodes can know the role status of this router device.

[0060] The emergency routing decision unit receives an emergency broadcast packet that needs to be forwarded. When activated, its function is to replace the traditional blind flooding broadcast and implement a network role-based directed routing strategy.

[0061] This unit first maintains a neighbor node table in the main controller's memory. This table is dynamically updated by continuously listening to status information packets broadcast by other nodes. The table records the unique identifier (ID) of each neighbor node and its latest role label. .

[0062] When the decision logic unit or bypass receiving unit delivers an emergency broadcast packet When forwarding, the emergency routing decision unit executes the following judgment process: First, it extracts the event ID of the emergency broadcast packet and compares it with a local cached list of processed event IDs. If the ID already exists, the packet is discarded to avoid information broadcast storms and loop paths in the ad hoc network. The event IDs in this cached list have a preset time-to-live (TTL) and are automatically removed after expiration to avoid buffer overflow and allow repeated processing of long-standing warning events.

[0063] If it is a new warning event, the unit traverses the neighbor node table and selects one or more optimal next-hop nodes according to preset routing priority rules. These rules specifically include: prioritizing role labels. Forwarding data packets to neighbors of high-density nodes ensures that early warning information reaches more potential users. In the absence of high-density nodes, neighbors labeled as critical communication nodes are prioritized to guarantee reliable propagation of information along the network backbone. Simultaneously, this unit avoids forwarding data packets back to their immediate upstream source node.

[0064] After completing node selection, the emergency routing decision unit generates a packet containing an emergency broadcast packet. The routing instructions specify the content and the target neighbor node ID. These instructions are sent to the LoRa wireless module 3, which then executes a directional wireless transmission to the designated node. This method enables intelligent management of the propagation path of early warning information within the emergency ad hoc network.

[0065] The distributed environmental sensing module 30 is designed to collaboratively utilize the vibration sensing capabilities of multiple router devices to dynamically learn and establish a regional environmental background noise model, thereby distinguishing between everyday environmental vibrations and potential seismic P-wave signals. This module includes an environmental noise acquisition unit and a distributed baseline learning unit.

[0066] When the router device is in a non-alarm state, the environmental noise acquisition unit drives the MEMS accelerometer 4 at preset time intervals (e.g., once per hour) to initiate raw vibration data for a duration (e.g., 10 seconds). Data acquisition. After acquisition, the unit performs a specific signal processing algorithm on the acquired raw vibration data, and calculates a quantitative value representing the current local environmental vibration level, i.e., the environmental noise fingerprint, using an environmental noise feature extraction formula. This fingerprint reflects the background noise characteristics of the microenvironment in which this router device is located. The formula for extracting environmental noise features is: ; In the formula: The calculated environmental noise fingerprint is a scalar value that reflects the vibration intensity. The preset feature extraction function can calculate the root mean square (RMS) value of the signal, energy within a specific frequency range, peak acceleration, or short-time average power, etc., to quantify the vibration intensity. The raw vibration data was acquired from MEMS accelerometer 4. This is the start time of data collection; This represents the duration window for data acquisition.

[0067] The distributed baseline learning unit periodically exchanges short messages with neighboring nodes in the emergency self-organizing network via LoRa wireless module 3. During this exchange, the router device broadcasts its latest environmental noise fingerprint to the neighboring nodes. It also receives low-bandwidth data packets from neighboring nodes, each containing its own environmental noise fingerprint.

[0068] This distributed baseline learning unit collects these neighbor fingerprint data, combines them with the router device's own fingerprint, and continuously updates a regional dynamic environmental noise baseline reflecting the overall environmental background noise of the area where the router device is located, based on the baseline calculation formula. The baseline is dynamically changed to adapt to variations in regional environmental noise over time (e.g., day / night, season). The baseline calculation formula is: ; In the formula: In time The calculated regional dynamic environmental noise baseline is a comprehensive scalar value that reflects the regional background vibration level. For the current router device The set of all reachable neighbor nodes in the emergency mesh network; To assign to neighboring nodes The weight is a unitless scalar value that can be dynamically adjusted based on factors such as the signal strength of the LoRa link, connection stability, packet loss rate, or historical data confidence level to reflect the importance of neighbor data. To the neighbor node Received environmental noise fingerprint; This is the delay time between communication and processing, used to compensate for the time difference between data acquisition and computation; This is the summation symbol.

[0069] Please see the appendix Figure 6The cross-validation and decision module 40, upon receiving an early warning message, performs independent verification through local physical sensing to make a final alarm decision. Its core purpose is to improve the reliability of early warnings and suppress false alarms. Logically, the cross-validation and decision module 40 includes a dynamic threshold generation unit, a physical vibration verification unit, and a decision logic unit.

[0070] The dynamic threshold generation unit receives the regional dynamic environmental noise baseline calculated and provided by the distributed environment sensing module 30. The function of this dynamic threshold generation unit is to generate an adaptive verification threshold in real time based on this dynamically changing baseline using a threshold calculation formula. The verification threshold is not a fixed value, but rather adjusts according to changes in the background noise of the area. This ensures that false alarms are not easily detected in noisy environments, while maintaining sensitivity to weak signals in quiet environments. The threshold calculation formula is as follows: ; In the formula: In time The generated dynamic verification threshold has the same unit as the vibration characteristic value. This is a preset sensitivity coefficient used to adjust the floating ratio of the verification threshold relative to the noise baseline; This is a preset base offset, with units consistent with the vibration characteristic value, used to set an absolute minimum trigger threshold.

[0071] The verification threshold calculated by the dynamic threshold generation unit It is immediately transmitted to the physical vibration verification unit as a benchmark for its subsequent comparison and judgment.

[0072] The physical vibration verification unit is activated after the early warning information receiving module 10 submits the early warning information. Its function is to immediately perform real-time vibration detection on the physical environment where the router device is located the moment it receives the external early warning signal, so as to obtain direct evidence of whether there is a ground motion (such as a P wave) corresponding to the early warning information in the local area.

[0073] Upon activation, the physical vibration verification unit immediately sends a high-priority acquisition command to the MEMS accelerometer 4. The MEMS accelerometer 4 then operates in high sampling rate mode, at the moment of receiving the warning information. Extremely short verification time window starting from Inside, a real-time triaxial acceleration data stream is acquired. .

[0074] After data acquisition, this unit uses the same feature extraction function as the environmental noise acquisition unit to process the real-time vibration data using the vibration feature extraction formula, and calculates a real-time vibration feature value that quantifies the current instantaneous vibration intensity. The vibration feature extraction formula is as follows: ; In the formula: The calculated real-time vibration characteristic value is a scalar value that reflects the instantaneous vibration intensity. The same feature extraction function is used as that used by the environmental noise acquisition unit; This refers to vibration data collected in real time. The moment the warning information was received; This is a short time window used for verification.

[0075] The physical vibration verification unit calculates the real-time vibration characteristic values. It is immediately transmitted to the decision logic unit for final comparison and judgment.

[0076] The decision logic unit is the final arbiter of the entire cross-validation and decision module 40. Its function is to compare the real-time measurement results provided by the physical vibration verification unit with the adaptive standard set by the dynamic threshold generation unit, so as to obtain the final judgment on the effectiveness of the early warning.

[0077] The decision logic unit receives real-time vibration characteristic values ​​from the physical vibration verification unit. and the dynamic verification threshold from the dynamic threshold generation unit. Its core operation is a conditional judgment: it processes the collected real-time vibration characteristic values... The dynamic verification threshold at the current moment Compare them.

[0078] If the judgment result is a real-time vibration characteristic value Greater than the dynamic verification threshold If the vibration intensity detected by the local sensor significantly exceeds the background noise level of the current area and meets the preset sensitivity requirement, it is sufficient to confirm the authenticity of the warning information.

[0079] If the judgment result is a real-time vibration characteristic value Less than or equal to the dynamic verification threshold If the warning is not detected, the decision-making logic unit determines it as an invalid warning. This means that although a warning message was received, no significant vibrations consistent with earthquake characteristics were detected in the local environment, thus effectively avoiding panic caused by false alarms or misinformation.

[0080] Upon determining that a warning is valid, the decision logic unit immediately generates and sends a series of activation commands. These commands include: sending drive commands to buzzer 5 and indicator light 6 to activate local audible and visual alarms; sending forwarding commands to the emergency routing decision unit to ensure that the warning information can be promptly forwarded to other nodes through the LoRa emergency self-organizing network; and sending linkage commands to the local device linkage module 50 to trigger a coordinated alarm response from smart devices within the local area network.

[0081] The local device linkage module 50 is designed to maximize the use of smart devices within the home for multimodal alarms after receiving a valid early warning activation command from the cross-validation and decision module 40, thereby enhancing the reach and intensity of the early warning information.

[0082] The local device linkage module 50 receives a start command from the decision logic unit. This start command typically contains key information about the warning event, such as the expected arrival time of the seismic wave and suggested evacuation behaviors.

[0083] Upon receiving the instruction, the local device linkage module 50 immediately performs two types of operations: First, the router sends specific UDP broadcast packets to all devices within the local area network (LAN) it is connected to (including wireless devices connected via Wi-Fi and wired devices connected via Ethernet). These broadcast packets carry structured warning data, the format of which is typically defined by a predefined application layer protocol, allowing devices on the LAN with the appropriate applications installed or capable of parsing the data to directly receive and display the warning information. The broadcast packet content may include a brief description of the earthquake event, emergency evacuation instructions, and suggested evacuation routes.

[0084] Secondly, the local device linkage module 50 utilizes the router's function as a smart home gateway to interact with compatible smart home devices within the local area network via standardized communication protocols or pre-built application programming interfaces (APIs). For example, for smart speakers, the local device linkage module 50 can invoke their function to play high-volume warning voice messages; for smart TVs, it can force a switch to a warning screen displaying evacuation guidelines; and for smart lighting devices, it can control them to flash at a preset frequency and color to create a visual warning. For devices supporting the Universal Plug and Play (UPnP) protocol, the module can directly detect and control their alarm functions. Through these linkages, simultaneous multi-sensory warnings for users, including auditory and visual ones, are achieved.

[0085] Working principle: Under normal conditions, this router system continuously performs environmental background monitoring and network management.

[0086] On one hand, the distributed environmental sensing module 30 periodically drives the local MEMS accelerometer 4 to collect environmental vibration data and extract a local environmental noise fingerprint. Simultaneously, the distributed environmental sensing module 30 exchanges environmental noise fingerprints with neighboring nodes via the LoRa wireless module 3, and combines this information to dynamically calculate and update a regional environmental noise baseline. This environmental noise baseline reflects the real-time background vibration level of the local area and its surroundings.

[0087] On the other hand, the emergency network management module 20 continuously monitors the local area network connection status and load of this router device, and dynamically assigns roles (such as high-density nodes or key communication nodes) to this router device in the LoRa emergency self-organizing network, providing a basis for decision-making for subsequent emergency information forwarding.

[0088] When an earthquake early warning is issued, the early warning information receiving module 10 acquires the information through redundant paths. If the internet connection is normal, it obtains authoritative early warning information from the official early warning server through the main path receiving unit. If the internet is interrupted, it drives the LoRa wireless module 3 through the bypass receiving unit to receive emergency broadcast packets from other nodes in the emergency self-organizing network.

[0089] Upon receiving the warning information, the cross-validation and decision module 40 immediately initiates the verification process. This module first utilizes the regional dynamic environmental noise baseline generated by the previously distributed environmental sensing module 30 to calculate a verification threshold that adapts to the current environmental noise level. Next, the physical vibration verification unit quickly drives the MEMS accelerometer 4 to perform a short-term, high-sampling-rate real-time vibration data acquisition and extracts real-time vibration feature values. The decision logic unit compares these real-time vibration feature values ​​with the dynamically generated verification threshold. If the real-time vibration feature value is higher than the verification threshold, the warning information is deemed valid; otherwise, it is deemed an invalid warning, thus avoiding false alarms.

[0090] If the warning is deemed valid, the router system will activate the buzzer 5 and indicator light 6 to issue an audible and visual alarm. Simultaneously, it will initiate local device linkage. The local device linkage module 50 will send warning information and control commands to all smart devices within the local area network, prompting smart speakers, televisions, and other devices to simultaneously issue hazard avoidance information. At the same time, the emergency routing decision unit in the emergency network management module 20 will forward the warning information to other nodes in the emergency ad hoc network via the LoRa wireless module 3, according to a preset routing strategy (such as prioritizing high-density nodes or key communication nodes), to achieve chain propagation and wide-area coverage of the warning information.

Claims

1. A router device with earthquake early warning and broadcast alarm functions, characterized in that, include: The router body (1) has a built-in main control processor, an antenna (2) installed on the rear side of the router body (1), a LoRa wireless module (3) installed in the middle of the router body (1), an emergency power supply (7) and a MEMS accelerometer (4) installed inside the router body (1), and a buzzer (5) and an indicator light (6) installed on the front side of the router body (1).

2. A router system with earthquake early warning and broadcast alarm functions, characterized in that: The router device with earthquake early warning and broadcast alarm functions as described in claim 1 includes: The early warning information receiving module is configured to receive earthquake early warning information, which includes authoritative early warning information and emergency broadcast packages. An emergency network management module is configured to build and maintain an emergency mesh network with multiple router devices through a LoRa wireless module (3), and manage the node roles in the emergency mesh network based on the local network load of the router system environment, so as to route the emergency broadcast packets. The distributed environmental sensing module is configured to collect the original vibration data of the router device, generate a local environmental noise fingerprint, and exchange the local environmental noise fingerprint with neighboring nodes through the LoRa wireless module (3) to construct a regional dynamic environmental noise baseline. The cross-validation and decision module is configured to receive the earthquake early warning information, and determine the validity of the earthquake early warning information based on the regional dynamic environmental noise baseline and the real-time vibration characteristic value obtained by the MEMS accelerometer (4), and drive the buzzer (5) and indicator light (6) to alarm when the information is determined to be valid; The local device linkage module is configured to trigger alarms and linkages of devices within the local area network after receiving a valid determination from the cross-validation and decision module.

3. A router system with earthquake early warning and broadcast alarm functions according to claim 2, characterized in that, The early warning information receiving module includes: The main path receiving unit is used to receive the authoritative early warning information via the Internet; A bypass receiving unit is used to receive the emergency broadcast packet from a surrounding router device via the LoRa wireless module (3).

4. A router system with earthquake early warning and broadcast alarm functions according to claim 2, characterized in that, The emergency network management module includes: The network topology analysis unit is used to analyze the connection status of the router system's local area network in order to generate a local network load profile. A dynamic role assignment unit is used to assign one or more role labels to the router system in the emergency mesh network based on the local network load profile, and broadcast the role labels. An emergency routing decision unit is used to identify other router devices within the direct communication range of the emergency mesh network as neighbor nodes through the LoRa wireless module (3), and to receive the neighbor node role label broadcast by the neighbor node; when it is necessary to forward the emergency broadcast packet, the emergency routing decision unit selects the next-hop node according to the neighbor node role label and the propagation status of the emergency broadcast packet to instruct the LoRa wireless module (3) to forward the emergency broadcast packet.

5. A router system with earthquake early warning and broadcast alarm functions according to claim 2, characterized in that, The distributed environment awareness module includes: An environmental noise acquisition unit is used to drive the MEMS accelerometer (4) to acquire the original vibration data and generate the local environmental noise fingerprint according to the environmental noise feature extraction formula. A distributed baseline learning unit is used to exchange the local environmental noise fingerprints of each neighboring node through the LoRa wireless module (3) and to calculate the regional dynamic environmental noise baseline according to the baseline calculation formula.

6. A router system with earthquake early warning and broadcast alarm functions according to claim 3, characterized in that, The cross-validation and decision module includes: A dynamic threshold generation unit is used to dynamically generate a verification threshold based on the dynamic environmental noise baseline of the region. A physical vibration verification unit is used to drive the MEMS accelerometer (4) to collect real-time vibration data and generate the real-time vibration characteristic value when the emergency broadcast package is received; The decision logic unit is used to compare the real-time vibration characteristic value with the verification threshold to determine the validity of the earthquake early warning information.

7. A router system with earthquake early warning and broadcast alarm functions according to claim 6, characterized in that, The dynamic threshold generation unit is specifically used for: Based on the threshold calculation formula, the dynamic environmental noise baseline of the region is multiplied by a preset sensitivity coefficient and a preset base offset is added to generate the verification threshold. The preset sensitivity coefficient is set based on distinguishing weak seismic P-wave signals from everyday background noise, and the preset base offset is set based on the minimum threshold for determining validity.

8. A router system with earthquake early warning and broadcast alarm functions according to claim 6, characterized in that, The physical vibration verification unit is specifically used for: When the bypass receiving unit receives the emergency broadcast packet, it is activated and drives the MEMS accelerometer (4) to collect the real-time vibration data within a very short time window, and generates the real-time vibration feature value according to the vibration feature extraction formula.

9. A router system with earthquake early warning and broadcast alarm functions according to claim 6, characterized in that, The decision logic unit is specifically used for: The real-time vibration characteristic value is compared with the verification threshold. If the real-time vibration characteristic value is greater than the verification threshold, the earthquake early warning information is determined to be a valid early warning; otherwise, it is determined to be an invalid early warning. When a valid warning is detected, a start command is sent to the buzzer (5), indicator light (6), emergency routing decision unit, and local device linkage module.

10. A router system with earthquake early warning and broadcast alarm functions according to claim 2, characterized in that, The local device linkage module is specifically configured as follows: When the earthquake early warning information is deemed valid, a UDP broadcast packet carrying the early warning information is generated and broadcast to devices on the local area network connected to the router system, or an application programming interface with a compatible protocol is invoked to control smart home devices and trigger alarm or linkage actions.

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