Method for integrated analysis of fire-fighting sensing data

Abstract

The invention is applicable to the fire-fighting Internet of Things, and provides an integrated fire-fighting sensing data analysis method, which comprises the following steps of: multi-protocol compatible analysis: converting original data of different manufacturer equipment into a unified JSON format by utilizing a universal adapter with a built-in protocol engine, and solving the problem of'data islands'; real-time state monitoring: through a heartbeat packet mechanism and historical data judgment, generating an equipment state label in real time, and performing second-level storage through a distributed database; and fast data processing: a calculation unit adopts a jdk21 virtual thread to complete analysis, and deploys a plurality of sets of analysis nodes by docker at the same time, so that the analysis output time of a large amount of data is less than 100 milliseconds. Data islands are broken, and the compatibility of cross-brand equipment is improved. The real-time performance is obviously improved, and the response speed reaches the industrial grade standard. And the false alarm rate is reduced by using historical data.

Description

Technical Field

[0001] The present invention relates to a fire protection internet of things, and in particular to a method for analyzing fire protection sensor data in an integrated manner. Background Art

[0002] Existing major manufacturers have their own data analysis platforms, but most can only analyze data generated by their own branded equipment and cannot simultaneously analyze multiple protocols. This makes data integration difficult and can also create fire hazards due to high false alarm rates and lack of real-time performance. Therefore, this invention proposes an integrated method for analyzing fire sensor data. Summary of the Invention

[0003] The present invention provides an integrated method for analyzing fire sensor data to solve the technical problems mentioned in the background technology.

[0004] A method for analyzing fire sensor data in an integrated manner, the method comprising:

[0005] Multi-protocol compatible parsing: Using a universal adapter with a built-in protocol engine, raw data from devices from different manufacturers is converted into a unified JSON format, solving the "data island" problem;

[0006] Real-time status monitoring: Through the heartbeat packet mechanism and historical data judgment, device status tags are generated in real time and stored in a distributed database in seconds;

[0007] Fast data processing: The computing unit uses JDK 21 virtual threads to complete parsing. At the same time, multiple parsing nodes are deployed with Docker, achieving parsing output time of less than 100 milliseconds for large amounts of data.

[0008] As a further technical solution of the present invention, the protocol engines in the multi-protocol compatibility parsing step include LwM2M, MQTT, and GB26875.3-2011.

[0009] As a further technical solution of the present invention, the JSON format includes standardized fields for device ID, data type, and value.

[0010] As a further technical solution of the present invention, the heartbeat packet mechanism detects the online status of the device every 10 seconds.

[0011] As a further technical solution of the present invention, the device status label includes online, offline, fault and fire alarm.

[0012] Beneficial effects achieved by the present invention:

[0013] This invention breaks down data silos and enhances cross-brand device compatibility. It significantly improves real-time performance, reaching industrial-grade response speeds. It also leverages historical data to reduce false alarm rates. DETAILED DESCRIPTION

[0014] To make the purpose, technical solutions, and advantages of the embodiments of the present invention more clear, the technical solutions in the embodiments of the present invention are clearly and completely described below. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of the present invention.

[0015] In the description of the present invention, the terms "first" and "second" are used for descriptive purposes only and should not be understood to indicate or imply relative importance or implicitly specify the number of the technical features indicated. Therefore, a feature specified as "first" or "second" may explicitly or implicitly include one or more of the features. In the description of the present invention, "plurality" means two or more, unless otherwise specifically defined.

[0016] An embodiment of the present invention provides a method for analyzing fire sensor data in an integrated manner, the method comprising:

[0017] Multi-protocol compatible parsing: Utilizes universal adapters with built-in LwM2M, MQTT, GB26875.3-2011 and other protocol engines to convert raw data from devices of different manufacturers into a unified JSON format (including standardized fields for device ID, data type, and value), solving the "data island" problem.

[0018] The original data include original data 1, 2 and 3;

[0019] Original data 1: Haikang / Guanghai used: GB26875.3-2011 data, the format is as follows: 4040698e0101190e14090719c1000000000000000000000000040002190101003f2323;

[0020] Original data 2: Hikvision Fire Protection Cloud HTTP push data, the format is as follows:

[0021] {"fps":{"msgList":[{"msgType":"980008","body":{"notifyType":null,"data":[{"resourceID":"1099015937377193985","resourceSerial":"860586062822827","unitName":"Bo Run Yuan Tong","companyName":"Xinjiang Wen Teng Information Technology Co., Ltd.","monitorPhase":0,"resourceName":"Dormitory Building Fire Hydrant","monitorValue":"100" ,"type":1,"monitorState":"1","companyID":"984376280408838145","monitorType":"400001","monitorUnit":"%","systemType":"500005","unitID":"987410646563225600","location":"Tuha Oil Base, Building 3, Block 9, Oil Base, Oil New Town Street, Yizhou District, Hami City","minThresholdValue":20,"happenTime":"2025-06-25T00:00:01.071+08:00","resourceType":"600007"},{"resourceID":"1099015937377193985","resourceSerial":"860586062822827","unitName":"Bo Run Yuan Tong","companyName":"xx Information Technology Co., Ltd.","monitorPhase":0, "remark":"{\"eclValue\":0,\"pciValue\":301,\"snrValue\":5,\"rsrpValue\":-99}","resourceName":"Fire hydrant in dormitory building","monitorValue":"2", "type":1,"monitorState":"1","companyID":"984376280408838145","monitorType":"400002","monitorUnit":"","systemType":"500005","unitID":"987410646563225600","location":"Tuha Oil Base, Building 3, Block 9, Oil Base, Oil New Town Street, Yizhou District, Hami City", "happenTime":"2025-06-25T00:00:01.071+08:00","resourceType":"600007"},{"resourceID":"1099015937377193985","resourceSerial":"860586062822827","unitName":"Bo Run Yuan Tong","companyName":"Xinjiang Wen Teng Information Technology Co., Ltd.","monitorPhase":0,"resourceName":"Dormitory Building Fire hydrant","monitorValue":"0.15","type":1,"monitorState":"0","companyID":"984376280408838145","monitorType":"400004","monitorUnit":"MPa","systemType":"500005","unitID":"987410646563225600","location":"Tuha Oil Base, Building 3, Block 9, Oil Base, Oil New Town Street, Yizhou District, Hami City", "happenTime":"2025-06-25T00:00:01.071+08:00","resourceType":"600007"}],"dataType":"980008101"}}]}}.

[0022] Original data 3: Private data format: 0300002F2AE00000000000436F6F6B69653A206D737473686173683D41646D696E697374720D0A0100080003000000.

[0023] Raw data 1 and 3 are used to collect signals from the fire host and forward them to the server. The data types include heartbeat packets, fire alarm packets, fault signal packets, etc.

[0024] Raw data 2 is the data from the level meter and pressure gauge, including water depth, pressure, communication signal strength, and power.

[0025] Real-time status monitoring: Through the heartbeat packet mechanism (detecting the device's online status every 10 seconds) and historical data judgment, device status tags (online / offline / fault / fire alarm) are generated in real time and stored in a distributed database in seconds;

[0026] Historical data judgment:

[0027] 1. Hikvision wireless pressure gauges and liquid level meters will report signal strength and battery power each time they are reported. Based on the historical power data, maintenance personnel can be notified to replace the gauge before the battery runs out.

[0028] 2. The data reported by the user often contains fault data packets. The failure cycle of a certain component can be determined based on historical data. For example, the smoke detector in the kitchen often generates false alarms and failures due to oil smoke problems. Based on historical data, a maintenance plan can be formulated and regular cleaning can be carried out to ensure that the system and components are in normal working condition.

[0029] Real-time device status tag generation: Based on the reported data, wireless devices may have low battery / low signal tags, which means the device needs to replace the battery, or may occasionally lose reported data due to poor signal;

[0030] The components on the fire control host will have labels such as normal / fault / shield / supervision / feedback / startup. Maintenance personnel can only check and repair faulty / shielded sensors without having to check all components.

[0031] Fast data processing: The computing unit uses JDK21 virtual threads, which can complete the analysis in a short time with less computing power. At the same time, multiple sets of analysis nodes are deployed with Docker, achieving the analysis and output of large amounts of data (original data packet -> analysis -> writing to the database) in less than 100 milliseconds.

[0032] The above parsing process includes:

[0033] 1. Usage transmission: Each brand's usage transmission is received by nginx using a fixed port and forwarded to the corresponding parsing unit. The parsing unit is written according to the corresponding data structure document. Usually, this type of data complies with the gb26875.3 standard and is a hexadecimal TCP data packet.

[0034] 2. Wireless devices:

[0035] 1) Hikvision Fire Cloud actively pushes HTTP JSON. Nginx needs to open a location and forward all request data to the corresponding HTTP processing unit. Due to different events and different devices, the format nesting within JSON may vary. Key data needs to be extracted and converted to a unified format.

[0036] 2) OneNet receives MQTT data and can receive JSON data packets, which contain raw data in base64 format. You need to write code according to the manufacturer's documentation to convert the raw data into readable information

[0037] A large amount of data includes all the data mentioned above. The transmission is mainly used to report the sensor data that can be connected to the fire host, including smoke detectors, hand alarms, fire shutters / telephones / broadcasts, sounders, etc., while wireless equipment is mainly fire auxiliary facilities. Liquid level meters are used to monitor fire water tanks, pressure gauges are used to monitor sprinkler pipe networks and outdoor fire hydrants, and anemometers monitor smoke exhaust fans and air supply fans. Auxiliary equipment is usually not enabled, but it is necessary to ensure that the equipment can work normally. For example, smoke detectors and hand alarms cannot be triggered once a day to prove that they can work normally. The monitoring report of the fire host should be the main method, supplemented by regular inspections to ensure that the equipment is working properly.

[0038] The determination and analysis of equipment status includes:

[0039] Online / offline: The transmitter can be configured to send a heartbeat packet at a minimum interval of 7 seconds. Some wireless devices can configure the data reporting time, while others cannot. Instead, they report every 20 hours. Therefore, the time of the last data report and the current time can be used to determine whether the device is online.

[0040] Fire alarms are usually reported by transmission, and all fault devices can report them, but the data formats are different.

[0041] It should be noted that, in this document, the term "comprises" or any other variant thereof is intended to cover non-exclusive inclusion, so that a process, method, article, or apparatus that includes a series of elements includes not only those elements, but also includes other elements not explicitly listed, or also includes elements inherent to such process, method, article, or apparatus. In the absence of further limitations, an element defined by the phrase "comprises a ..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes the element.

[0042] The above are only preferred embodiments of the present invention and are not intended to limit the patent scope of the present invention. Any equivalent structure or equivalent process transformation made using the description of the present invention, or directly or indirectly applied in other related technical fields, are also included in the patent protection scope of the present invention.

Claims

1. A method for analyzing fire sensor data in an integrated manner, characterized in that: The method comprises: Multi-protocol compatible parsing: Using a universal adapter with a built-in protocol engine, raw data from devices from different manufacturers is converted into a unified JSON format, solving the "data island" problem; Real-time status monitoring: Through the heartbeat packet mechanism and historical data judgment, device status tags are generated in real time and stored in a distributed database in seconds; Fast data processing: The computing unit uses JDK 21 virtual threads to complete parsing, and multiple parsing nodes are deployed using Docker, achieving data parsing output time of less than 100 milliseconds.

2. The method for analyzing fire sensor data according to claim 1, characterized in that: The protocol engines in the multi-protocol compatibility parsing step include LwM2M, MQTT, and GB26875.3-2011.

3. The method for analyzing fire sensor data according to claim 1, characterized in that: The JSON format contains standardized fields for device ID, data type, and value.

4. The method for analyzing fire sensor data according to claim 1, characterized in that: The heartbeat packet mechanism detects the device online status every 10 seconds.

5. The method for analyzing fire sensor data in an integrated manner according to claim 1, characterized in that: The device status tags include online, offline, fault and fire alarm.