Honeycomb-bird household intelligent fire-fighting unmanned aerial vehicle system

Abstract

The invention discloses a bee bird household intelligent fire-fighting unmanned aerial vehicle system, which relates to the technical field of fire-fighting unmanned aerial vehicles, comprises a bird-shaped unmanned aerial vehicle and a fire extinguishing case, and is characterized in that two electronic scanning eyes are mounted at the eyes of the bird-shaped unmanned aerial vehicle, a high-strength alloy drill bit is mounted at the mouth of the bird-shaped unmanned aerial vehicle, and a motor is embedded in the high-strength alloy drill bit; a fire extinguishing case is mounted at the bottom of the bird-shaped unmanned aerial vehicle, a fixing frame is fixedly connected to the fire extinguishing case, and the top end of the fixing frame is fixedly connected with the bird-shaped unmanned aerial vehicle; according to the device, through multi-source data fusion of the electronic scanning eye, the three-mode recognition module and the infrared scanning recognizer, information such as temperature, gas components, smoke concentration and fire source form can be captured in an omnibearing mode, the comprehensive risk score and the fire confidence coefficient are analyzed in combination with an algorithm, and compared with traditional single smoke sensing alarm, the alarm is more accurate. The false alarm rate caused by environmental interference such as kitchen oil fume and steam can be greatly reduced, the fire behavior can be accurately and rapidly locked, and the situation that the optimal fire extinguishing opportunity is missed is avoided.

Description

Technical Field

[0001] The present invention relates to the technical field of fire-fighting drones, and in particular to a Hummingbird household intelligent fire-fighting drone system. Background Art

[0002] In the field of modern home fire safety, with the increasing number of household electrical appliances and the complexity of living environment, fire hazards are constantly increasing, and the demand for efficient and intelligent fire-fighting equipment is becoming more urgent. Firefighting drones are a type of drone equipment specially used in the fire-fighting field. They are equipped with a variety of sensors, fire-fighting devices and intelligent control systems to realize fire monitoring, fire location, fire-fighting operations and other functions. They are an important part of the modern smart fire-fighting system.

[0003] Existing firefighting technology and equipment have numerous shortcomings. In the field of drone firefighting, professional-grade drones, such as the DJI Matrice 300, while performing well in industrial and large-scale scenarios, are bulky and cannot fit through narrow spaces like doors, windows, and hallways, making it difficult to enter homes for firefighting operations. Therefore, those skilled in the art have developed the Hummingbird household intelligent firefighting drone system to address the issues raised in the background art above. Summary of the Invention

[0004] The purpose of the present invention is to provide a Hummingbird household intelligent fire-fighting drone system to solve the problems raised in the above background technology.

[0005] To achieve the above object, the present invention provides the following technical solutions:

[0006] The Hummingbird household intelligent fire-fighting drone system includes a bird-shaped drone and a fire-extinguishing chassis. It is characterized in that the bird-shaped drone is equipped with two electronic scanning eyes in its eyes, and a high-strength alloy drill is installed in its mouth. A motor is embedded in the high-strength alloy drill. A fire-extinguishing chassis is installed at the bottom of the bird-shaped drone, and a fixing frame is fixedly connected to the fire-extinguishing chassis, and the top of the fixing frame is fixedly connected to the bird-shaped drone. A three-mode recognition module is fixedly connected to the bottom end of the fire-extinguishing chassis, and a battery box is provided at the bottom end of the fire-extinguishing chassis and on one side of the three-mode recognition module. A partition is fixedly connected to the inside of the fire-extinguishing chassis and above the three-mode recognition module, and a storage box is fixedly connected to the top of the partition, and two honeycomb fire-extinguishing capsule cabins are installed inside the storage box.

[0007] As a further solution of the present invention, the three-mode recognition module adopts a heat-smell-smoke three-mode fire recognition algorithm, which includes a heat detection module, an odor detection module, and a smoke detection module; the steps of the heat-smell-smoke three-mode fire recognition algorithm are as follows:

[0008] S1, data preprocessing and feature extraction;

[0009] S2, feature-level fusion;

[0010] S3. Decision-level fusion.

[0011] As a further solution of the present invention: in S1:

[0012] Input: thermal temperature matrix (T mxn ), odor sensor array data (G k ), smoke concentration value (S);

[0013] The output is: the normalized eigenvector of each mode (Fthermal, Fgas, Fsmoke);

[0014] S1 further includes the following steps:

[0015] S1-1: Data synchronization and time window alignment

[0016] S1-1.1: Use a sliding time window to align the three modal data to ensure time synchronization;

[0017] S1-1.2: Filter sensor noise;

[0018] S1-2: Feature Standardization

[0019] S1-2.1: Standardization of thermal characteristics. The detailed steps are: Extract the maximum value of the temperature distribution matrix (T max ), gradient change (ΔT / Δt), abnormal area ratio (A hot ), the standardized formula of thermal characteristics is: Among them, T max is the baseline temperature, σ is the standard deviation of historical data;

[0020] S1-2.2: Standardization of odor characteristics. The detailed steps are: Extract the CO concentration (C co ), CO2 concentration VOCs (volatile organic compounds) concentration The standardized formula for odor characteristics is: Among them, μ is the upper limit of the sensor range;

[0021] S1-2.3: Standardization of smoke sensor characteristics. The detailed steps are as follows: Extract the smoke concentration value (S) and its rate of change (ΔS / Δt). The standardization formula of the smoke sensor characteristics is:

[0022] As a further solution of the present invention: in S2:

[0023] Input: normalized feature vectors Fthermal, Fgas, Fsmoke;

[0024] The output is: comprehensive risk score Rfusion;

[0025] Among them, S2 also includes the following steps:

[0026] S2-1: Dynamic Weight Allocation

[0027] S2-1.1: Dynamically adjust the weight according to the sensor confidence. The weight adjustment formula is:

[0028] S2-1.2: Calculate the confidence level using the following formula:

[0029] S2-2: Weighted Fusion Calculation

[0030] S2-2.1: Score the comprehensive risk. The scoring formula is: Rfusion = ωT·||Fthermal||+ωG·||Fgas||+ωS·||Fsmoke||, where ||F|| is the L2 norm of the feature vector (after normalization).

[0031] As a further solution of the present invention: in S3:

[0032] Input: Independent fire probability of each mode Pthermal, Pgas, Psmoke;

[0033] Output: Final fire confidence Bel(Fire);

[0034] Among them, S3 also includes the following steps:

[0035] S3-1: Basic Probability Assignment

[0036] S3-1.1: Framework definition and identification, framework formula: θ = {Fire, NonFire};

[0037] S3-1.2: Assign the independent fire probability to each mode. The assignment formula is: mi(Fire) = mi(θ)=1-mi(Fire), where α is the false alarm suppression coefficient (empirical value 0.2-0.5);

[0038] S3-2: Dempster Combination Rules

[0039] S3-2.1: Combine the three modal evidence and calculate the final confidence level. The calculation formula is:

[0040] S3-2.2: Calculate the conflict factor using the following formula:

[0041] S3-2.3: Calculate the final confidence level using the formula: Bel(Fire) = mtotal(Fire).

[0042] As a further solution of the present invention: the decision rule of the decision-level fusion is:

[0043] Condition 1: If Rfusion>θ and Bel(Fire)>θ2, a fire alarm is triggered.

[0044] Condition 2: If a single mode is triggered, start the redundant verification process.

[0045] As a further solution of the present invention: an air inlet is opened on one side of the honeycomb fire extinguishing capsule cabin, two jet boosters are installed on the outer wall of the fire extinguishing box, and the air outlet heads of the jet boosters pass through the fire extinguishing box and are connected to the air inlet.

[0046] As a further solution of the present invention: two air outlet grooves are provided on the storage box, and the air outlet of the honeycomb fire extinguishing capsule cabin is connected to the air outlet grooves, and discharge pipes are fixedly connected on an outer wall of the storage box and located at the two air outlet grooves, and a fire extinguishing capsule conveyor belt is installed inside the fire extinguishing box and below the discharge pipe, and the fire extinguishing capsule conveyor belt is located above the partition, and a transparent hatch is installed on the top of the fire extinguishing box.

[0047] As a further solution of the present invention: a high-voltage transmitter is installed at one end of the fire extinguishing box away from the jet booster, and an infrared scanning identifier is fixedly connected to an outer wall of the fire extinguishing box and located above the high-voltage transmitter.

[0048] As a further solution of the present invention: an LED light strip is installed at one end of the fire extinguishing chassis, and the LED light strip is in a U-shape, and a working status display is provided at one end of the fire extinguishing chassis and inside the LED light strip.

[0049] Compared with the prior art, the present invention has the following beneficial effects:

[0050] 1. This device integrates multi-source data from an electronic scanning eye, a three-mode recognition module, and an infrared scanning identifier to comprehensively capture information such as temperature, gas composition, smoke concentration, and fire source form. Combined with algorithmic analysis, it generates a comprehensive risk score and fire confidence level. Compared to traditional single-smoke alarms, this device significantly reduces false alarms caused by environmental interference such as kitchen fumes and steam, allowing it to accurately and quickly identify fires and avoid missing the optimal firefighting opportunity.

[0051] 2. This device can automatically start the high-strength alloy drill in the drone's mouth when facing common obstacles such as anti-theft nets, closed doors and windows that hinder firefighting. Its built-in motor can intelligently adjust the speed and torque according to the material of the obstacle, quickly breaking through the obstacle and opening up the fire-fighting channel. This breaks through the dilemma of traditional fire-fighting equipment being unable to get close to the fire source due to obstacles, and ensures the smooth progress of fire-fighting operations. BRIEF DESCRIPTION OF THE DRAWINGS

[0052] Figure 1 This is a three-dimensional diagram of the Hummingbird household intelligent fire-fighting drone system.

[0053] Figure 2 This is a three-dimensional image of the bird-shaped drone in the Hummingbird household intelligent fire-fighting drone system.

[0054] Figure 3 This is a three-dimensional image of the fire extinguishing chassis in the Hummingbird household intelligent fire-fighting drone system.

[0055] Figure 4 This is a three-dimensional image of the storage box in the Hummingbird household intelligent fire-fighting drone system.

[0056] Figure 5 This is a schematic diagram of the internal structure of the fire extinguishing chassis in the Hummingbird household intelligent fire-fighting drone system.

[0057] In the picture: 1. Bird-shaped drone; 2. Electronic scanning eye; 3. Fixing bracket; 4. Fire extinguisher box; 5. Transparent hatch; 6. Three-mode recognition module; 7. Battery box; 8. Partition; 9. Storage box; 10. Honeycomb fire extinguishing capsule cabin; 11. Air inlet; 12. Jet booster; 13. Air outlet trough; 14. Discharge pipe; 15. Fire extinguishing capsule conveyor belt; 16. Infrared scanning identifier; 17. High-voltage transmitter; 18. LED light strip; 19. Working status display; 20. High-strength alloy drill bit. DETAILED DESCRIPTION

[0058] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. All other embodiments obtained by ordinary technicians in this field based on the embodiments of the present invention without making any creative efforts shall fall within the scope of protection of the present invention.

[0059] Example 1

[0060] Reference Figure 1-5This embodiment provides a hummingbird household intelligent fire-fighting drone system, including a bird-shaped drone 1 and a fire extinguishing chassis 4, characterized in that the eyes of the bird-shaped drone 1 are equipped with two electronic scanning eyes 2, the mouth of the bird-shaped drone 1 is equipped with a high-strength alloy drill bit 20, and a motor is embedded in the high-strength alloy drill bit 20; a fire extinguishing chassis 4 is installed at the bottom of the bird-shaped drone 1, and a fixing frame 3 is fixedly connected to the fire extinguishing chassis 4, and the top of the fixing frame 3 is fixedly connected to the bird-shaped drone 1; a three-mode recognition module 6 is fixedly connected to the bottom end of the fire extinguishing chassis 4; a battery box 7 is provided at the bottom end of the fire extinguishing chassis 4 and located on one side of the three-mode recognition module 6; a partition 8 is fixedly connected to the inside of the fire extinguishing chassis 4 and located above the three-mode recognition module 6; a storage box 9 is fixedly connected to the top of the partition 8, and two honeycomb fire extinguishing capsule cabins 10 are installed inside the storage box 9.

[0061] The three-mode recognition module 6 adopts a heat-smell-smoke three-mode fire recognition algorithm, which includes a heat detection module, an odor detection module and a smoke detection module; the steps of the heat-smell-smoke three-mode fire recognition algorithm are: S1, data preprocessing and feature extraction; S2, feature-level fusion; S3, decision-level fusion.

[0062] In S1:

[0063] Input: thermal temperature matrix (T mxn ), odor sensor array data (G k ), smoke concentration value (S);

[0064] The output is: the normalized eigenvector of each mode (Fthermal, Fgas, Fsmoke);

[0065] S1 further includes the following steps:

[0066] S1-1: Data synchronization and time window alignment

[0067] S1-1.1: Use a sliding time window to align the three modal data to ensure time synchronization;

[0068] S1-1.2: Filter sensor noise;

[0069] S1-2: Feature Standardization

[0070] S1-2.1: Standardization of thermal characteristics. The detailed steps are: Extract the maximum value of the temperature distribution matrix (T max ), gradient change (ΔT / Δt), abnormal area ratio (A hot ), the standardized formula of thermal characteristics is: Among them, T max is the baseline temperature, σ is the standard deviation of historical data;

[0071] S1-2.2: Standardization of odor characteristics. The detailed steps are: Extract the CO concentration (C co ), CO2 concentration VOCs (volatile organic compounds) concentration The standardized formula for odor characteristics is: Among them, μ is the upper limit of the sensor range;

[0072] S1-2.3: Standardization of smoke sensor characteristics. The detailed steps are as follows: Extract the smoke concentration value (S) and its rate of change (ΔS / Δt). The standardization formula of the smoke sensor characteristics is:

[0073] In the S2:

[0074] Input: normalized feature vectors Fthermal, Fgas, Fsmoke;

[0075] The output is: comprehensive risk score Rfusion;

[0076] Among them, S2 also includes the following steps:

[0077] S2-1: Dynamic Weight Allocation

[0078] S2-1.1: Dynamically adjust the weight according to the sensor confidence. The weight adjustment formula is:

[0079] S2-1.2: Calculate the confidence level using the following formula:

[0080] S2-2: Weighted Fusion Calculation

[0081] S2-2.1: Score the comprehensive risk. The scoring formula is: Rfusion = ωT·||Fthermal||+ωG·||Fgas||+ωS·||Fsmoke||, where ||F|| is the L2 norm of the feature vector (after normalization).

[0082] In the S3:

[0083] Input: Independent fire probability of each mode Pthermal, Pgas, Psmoke;

[0084] Output: Final fire confidence Bel(Fire);

[0085] Among them, S3 also includes the following steps:

[0086] S3-1: Basic Probability Assignment

[0087] S3-1.1: Framework definition and identification, framework formula: θ = {Fire, NonFire};

[0088] S3-1.2: Assign independent fire probability to each mode. The assignment formula is: mi(θ)=1-mi(Fire), where α is the false alarm suppression coefficient (empirical value 0.2-0.5);

[0089] S3-2: Dempster Combination Rules

[0090] S3-2.1: Combine the three modal evidence and calculate the final confidence level. The calculation formula is:

[0091] S3-2.2: Calculate the conflict factor using the following formula:

[0092] S3-2.3: Calculate the final confidence level using the formula: Bel(Fire) = mtotal(Fire).

[0093] The decision rule of the decision-level fusion is:

[0094] Condition 1: If Rfusion>θ and Bel(Fire)>θ2, a fire alarm is triggered.

[0095] Condition 2: If a single mode is triggered, start the redundant verification process.

[0096] When this embodiment is in use, after the drone is turned on, the electronic scanning eye 2 of the bird-shaped drone 1, the three-mode recognition module 6 in the fire extinguishing chassis 4, the infrared scanning identifier 16 and other sensors are powered on for self-test, the battery box 7 supplies power to each module, the fixing bracket 3 ensures the rigid connection between the fire extinguishing chassis 4 and the drone, and the transparent hatch 5 protects the internal components. After the self-test is completed, the electronic scanning eye 2 starts to collect environmental visual images, the three-mode recognition module 6 enters the real-time monitoring state, the thermal detection module scans the environmental temperature field, the odor detection module collects air components, the smoke detection module monitors the smoke concentration, and continuously outputs raw data. According to the multi-source data fusion analysis, it is determined that the comprehensive risk score Rfusion and the final fire confidence Bel(Fire) meet the preset threshold, then the fire is confirmed.

[0097] Example 2

[0098] Reference Figure 1-5This embodiment is based on the previous embodiment, and differs from the previous embodiment in that an air inlet 11 is opened on one side of the honeycomb fire extinguishing capsule cabin 10, two jet boosters 12 are installed on the outer wall of the fire extinguishing box 4, and the air outlet head of the jet booster 12 passes through the fire extinguishing box 4 and is connected to the air inlet 11.

[0099] Two air outlet grooves 13 are provided on the storage box 9, and the air outlet of the honeycomb fire extinguishing capsule cabin 10 is connected to the air outlet groove 13. A discharge pipe 14 is fixedly connected to the two air outlet grooves 13 on an outer wall of the storage box 9. A fire extinguishing capsule conveyor belt 15 is installed inside the fire extinguishing box 4 and below the discharge pipe 14. The fire extinguishing capsule conveyor belt 15 is located above the partition 8, and a transparent hatch 5 is installed on the top of the fire extinguishing box 4.

[0100] A high-voltage transmitter 17 is installed at one end of the fire extinguishing box 4 away from the jet booster 12 , and an infrared scanning identifier 16 is fixedly connected to an outer wall of the fire extinguishing box 4 and located above the high-voltage transmitter 17 .

[0101] An LED light strip 18 is installed at one end of the fire extinguishing box 4, and the LED light strip 18 is in a circular shape. A working status display 19 is provided at one end of the fire extinguishing box 4 and inside the LED light strip 18.

[0102] When this embodiment is in use, after the fire is confirmed, the infrared scanning identifier 16 accurately locates the fire source, combines the visual information of the electronic scanning eye 2, plans the flight path of the drone, and adjusts its posture to approach the fire source. During this process, if it encounters obstacles such as anti-theft nets, closed doors and windows, the high-strength alloy drill bit on the mouth of the bird-shaped drone 1 will automatically start. According to the material of the obstacle, the motor in the high-strength alloy drill bit automatically adjusts the speed and torque to perform obstacle removal operations, creating conditions for subsequent fire extinguishing. When the drone arrives at the appropriate position, the jet booster 12 is started, and the high-pressure airflow is injected into the honeycomb fire extinguishing capsule cabin 10 through the air inlet 11 to accelerate the energy storage of the capsule. The fire extinguishing capsule conveyor belt 15 runs to transport the fire extinguishing capsule to the discharge pipe 14 is in the ready position, the air outlet of the capsule is aligned with the air outlet slot 13 of the storage box 9 to ensure airflow conduction, and the fire extinguishing capsule is launched to the fire source area at high speed through the high-voltage transmitter 17. The LED light strip 18 flashes to indicate the working status. After the fire is extinguished, the drone returns to the base station and waits for the next mission. The device can capture temperature, gas composition, smoke concentration, fire source form and other information in all directions through the multi-source data fusion of the electronic scanning eye 2, the three-mode recognition module 6 and the infrared scanning identifier 16. Combined with the algorithm analysis of the comprehensive risk score and fire confidence, compared with the traditional single smoke alarm, it can greatly reduce the false alarm rate caused by environmental interference such as kitchen fumes and steam, accurately and quickly lock the fire, and avoid missing the best time to extinguish the fire.

[0103] It will be apparent to those skilled in the art that the present invention is not limited to the details of the exemplary embodiments described above and that the invention can be embodied in other specific forms without departing from the spirit or essential characteristics of the invention. Therefore, the embodiments should be considered in all respects as illustrative and non-restrictive, and the scope of the invention is defined by the appended claims, not the foregoing description, and all variations within the meaning and range of equivalents of the claims are intended to be included therein. Any reference sign in a claim should not be construed as limiting the claim to which it relates.

[0104] In addition, it should be understood that although this specification is described in terms of implementation methods, not every implementation method contains only one independent technical solution. This narrative method of the specification is only for the sake of clarity. Those skilled in the art should regard the specification as a whole. The technical solutions in each embodiment can also be appropriately combined to form other implementation methods that can be understood by those skilled in the art.

Claims

1. The Hummingbird household intelligent fire-fighting drone system comprises a bird-shaped drone (1) and a fire-fighting chassis (4), characterized in that: The bird-shaped drone (1) is provided with two electronic scanning eyes (2) on its eyes, a high-strength alloy drill bit (2) (0) on its mouth, a motor embedded in the high-strength alloy drill bit (2) (0), a fire extinguishing machine box (4) on its bottom, a fixing frame (3) fixedly connected to the fire extinguishing machine box (4), and a top of the fixing frame (3) fixedly connected to the bird-shaped drone (1), a three-mode recognition module (6) fixedly connected to the bottom of the fire extinguishing machine box (4), a battery box (7) provided at the bottom of the fire extinguishing machine box (4) and located on one side of the three-mode recognition module (6), a partition (8) fixedly connected to the inside of the fire extinguishing machine box (4) and located above the three-mode recognition module (6), a storage box (9) fixedly connected to the top of the partition (8), and two honeycomb-type fire extinguishing capsule cabins (10) installed in the storage box (9); The three-mode recognition module (6) adopts a heat-smell-smoke three-mode fire recognition algorithm, which includes a heat detection module, an odor detection module and a smoke detection module; the steps of the heat-smell-smoke three-mode fire recognition algorithm are as follows: S1, data preprocessing and feature extraction; S2, feature-level fusion; S3. Decision-level fusion.

2. The Fengniao household intelligent fire-fighting drone system according to claim 1 is characterized in that: In S1: Input: thermal temperature matrix (T mxn ), odor sensor array data (G k ), smoke concentration value (S); The output is: the normalized eigenvector of each mode (Fthermal, Fgas, Fsmoke); S1 further includes the following steps: S1-1: Data synchronization and time window alignment S1-1.1: Use a sliding time window to align the three modal data to ensure time synchronization; S1-1.2: Filter sensor noise; S1-2: Feature Standardization S1-2.1: Standardization of thermal characteristics. The detailed steps are: Extract the maximum value of the temperature distribution matrix (T max ), gradient change (ΔT / Δt), abnormal area ratio (A hot ), the standardized formula of thermal characteristics is: Among them, T max is the baseline temperature, σ is the standard deviation of historical data; S1-2.2: Standardization of odor characteristics. The detailed steps are: Extract the CO concentration (C co ), CO2 concentration VOCs (volatile organic compounds) concentration The standardized formula for odor characteristics is: Among them, μ is the upper limit of the sensor range; S1-2.3: Standardization of smoke sensing characteristics. The detailed steps are as follows: Extract the smoke concentration value (S) and its rate of change (ΔS / Δt). The standardization formula of the smoke sensing characteristics is:

3. The Fengniao household intelligent fire-fighting drone system according to claim 1 is characterized in that: In S2: Input: normalized feature vectors Fthermal, Fgas, Fsmoke; The output is: comprehensive risk score Rfusion; Among them, S2 also includes the following steps: S2-1: Dynamic Weight Allocation S2-1.1: Dynamically adjust the weight according to the sensor confidence. The weight adjustment formula is: S2-1.2: Calculate the confidence level using the following formula: S2-2: Weighted Fusion Calculation S2-2.1: Score the comprehensive risk. The scoring formula is: Rfusion = ωT·||Fthermal||+ωG·||Fgas||+ωS·||Fsmoke||, where ||F|| is the L2 norm of the feature vector (after normalization).

4. The Fengniao household intelligent fire-fighting drone system according to claim 1 is characterized in that: In the S3: Input: Independent fire probability of each mode Pthermal, Pgas, Psmoke; Output: Final fire confidence Bel(Fire); Among them, S3 also includes the following steps: S3-1: Basic Probability Assignment S3-1.1: Framework definition and identification, framework formula: θ = {Fire, NonFire}; S3-1.2: Assign independent fire probability to each mode. The assignment formula is: mi(θ) = 1 - mi(Fire), where α is the false alarm suppression coefficient (empirical value 0.2 to 0.5); S3-2: Dempster Combination Rules S3-2.1: Combine the three modal evidence and calculate the final confidence level. The calculation formula is: S3-2.2: Calculate the conflict factor using the following formula: S3-2.3: Calculate the final confidence level using the formula: Bel(Fire) = mtotal(Fire).

5. The Fengniao household intelligent fire-fighting drone system according to claim 1 is characterized in that: The decision rule of the decision-level fusion is: Condition 1: If Rfusion>θ and Bel(Fire)>θ2, a fire alarm is triggered. Condition 2: If a single mode is triggered, start the redundant verification process.

6. The Fengniao household intelligent fire-fighting drone system according to claim 1 is characterized in that: An air inlet (11) is provided on one side of the honeycomb fire extinguishing capsule cabin (10), and two jet boosters (12) are installed on the outer side wall of the fire extinguishing machine box (4), and the air outlet heads of the jet boosters (12) pass through the fire extinguishing machine box (4) and are connected to the air inlet (11).

7. The Fengniao household intelligent fire-fighting drone system according to claim 1 is characterized in that: The storage box (9) is provided with two air outlet grooves (13), and the air outlet of the honeycomb fire extinguishing capsule cabin (10) is connected to the air outlet grooves (13). A discharge pipe (14) is fixedly connected to the two air outlet grooves (13) on an outer wall of the storage box (9). A fire extinguishing capsule conveyor belt (15) is installed inside the fire extinguishing machine box (4) and below the discharge pipe (14). The fire extinguishing capsule conveyor belt (15) is located above the partition (8), and a transparent hatch (5) is installed on the top of the fire extinguishing machine box (4).

8. The Fengniao household intelligent fire-fighting drone system according to claim 1 is characterized in that: A high-voltage transmitter (17) is installed at one end of the fire extinguishing machine box (4) away from the jet booster (12), and an infrared scanning identifier (16) is fixedly connected to an outer side wall of the fire extinguishing machine box (4) and located above the high-voltage transmitter (17).

9. The Fengniao household intelligent fire-fighting drone system according to claim 1 is characterized in that: An LED light strip (18) is installed at one end of the fire extinguishing box (4), and the LED light strip (18) is in a circular shape. A working status display (19) is provided at one end of the fire extinguishing box (4) and inside the LED light strip (18).

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