Intelligent Fire Suppression Devices Based on Microcapsules Linked to Sensor Internet of Things

Abstract

Most fire spread is caused by the absence of suppression means at the beginning of the fire. This results in the missed golden time. There are various factors that cause initial fires, such as electrical outlets, general distribution circuits, and oil–vapor–gas cluster spaces. In most cases, these places are out of reach of human hands or they lose the initial suppression time when a fire occurs, causing the spread of fire. This study implements an intelligent fire suppression device that connects sensor IoT based on microcapsules to secure initial fire suppression and golden time in the event of a fire in blind spots that cannot be seen by humans or at a time when it is difficult to recognize a fire. The microcapsule is a micro-collection unit that collects Novec 1230 gas generated in the semiconductor production process. The microcapsule is molded into a form with a fire suppression function and, when a fire occurs, the molded body explodes and absorbs ambient oxygen to suppress the fire. The complex-sensor IoT executes smoke and heat detection generated when a fire is suppressed within 10 s, which ensures the reliability of the detector by notifying of the fire and detecting the ignition point through communication linkages such as Ieee 485 and WiFi or LoRa.

1. Introduction

There are various factors that cause initial fires, such as electrical outlets, general distribution circuits, and oil–vapor–gas cluster spaces. In most cases, these places are out of reach of human hands or remote from human attention, causing the spread of fire by missing the initial suppression time in the event of a fire. In addition, the absence of suppression means in the early stages of a fire causes human and property disadvantages, missing the so-called golden time [1]. Figure 1 shows the drying electric furnace of a clothing weaving company, the electric distribution box, and the outlet terminal.

Accumulation of fine dust is very serious in the drying electric furnace of a clothing weaving company and, if the electric furnace device is left unattended for a long time, there is a very high possibility of fire due to the accumulated dust, and dust accumulated in the electric distribution box is often severely exposed to the risk of fire due to lightning or short circuits. The frequency of fire occurrence or monitoring function is very insufficient due to unfamiliar workers, non-majors, and turnover, and there are many cases in which it is turned into a large fire due to negligence of management.

Most of the cases in which a fire spreads occur in a remote place and are invisible. Buildings are often old or poorly managed, and it is very difficult to respond to fires that occur in underground distribution boards and outlets [2,3,4]. Figure 2 shows an intricately connected multi-tab. After a long period of use, dust accumulated in the multi-tab causes a short circuit, which causes a fire. In order to prevent this, the use of flame-retardant materials is mandatory, but it is difficult to block the spread of fire to surrounding flammable substances completely with flame-retardant materials.

Powder fire extinguishers are cheaper than other fire extinguishers but, if the fire spreads and the powder fire extinguisher continue to be used, secondary environmental pollution occurs due to the accumulated powder material. The CO₂ fire extinguisher is a cooling injection method, which is heavy in weight, making it inconvenient to move, and secondary damage occurs due to frostbite from the long-term spraying on the human body. Haron fire extinguishers are used in places with expensive facilities (i.e., a computer room, machine room, storage room, etc.), but most of them are used when a fire spreads [5,6]. As an environmental substance that destroys the ozone layer, production will be discontinued in the future due to the discontinuation of the substances used. Therefore, clean fire extinguishers are an expensive substitute for Haron, and the supply of materials is unstable.

Figure 3 shows a fire caused by an electric short circuit: (a) the 24th floor of Grenfell Tower, London, England, where 160 people died or went missing, 78 people were injured, and 17 were left in critical condition; (b) scenes of the fire inside the ESS device and the fire magnification; and (c) fire scene at Seomun Market in Daegu, Korea, where 679 stores were burned down due to an electric short circuit, and the initial response was delayed due to narrow vehicle roads due to the old traditional market structure.

Fire notifications and other alarm devices have many malfunctions, and it is often difficult for fire trucks to enter due to time and road conditions. Particularly, even if fire trucks have entered places such as traditional markets and bathhouses, there are considerable difficulties in initially suppressing them due to the concentration of shopping centers or complex internal structures of buildings [7].

In this study, in order to overcome the problems and limitations of existing topic detection technology or sensor products, it is designed to execute an automatic fire-extinguishing function in case of fire contact through a molding process encapsulating Novec 1230 gas, as shown in Figure 3. The smoke detection signal generated during the fire-extinguishing process is transmitted to the IoT terminal to access the national emergency contact network and perform fire suppression operations. At this time, a warning is given to fire departments, insurance companies, and related organizations by providing IP address information data that can identify the location of the fire-extinguishing point and by making it possible to know the ignition point or cause according to the IP sites. This makes it possible to effectively extinguish a fire by installing it in a place where many electric wires such as an electric outlet or a distribution panel are located or where a fire may ignite. Particularly, it implements a system that can effectively cope with the case of ignition taking advantage of sleeping time at night.

2. Implementation of IoT-Based Intelligent Microcapsule Composite Device

2.1. Microcapsule Composite Material

Microcapsule fire-extinguishing agents are manufactured in the form of microcapsules based on adhesive paste composites such as ABS and PC, which perform an immediate explosion and fire suppression operation within 10 s during fire contact. Despite various temperature ranges, it is manufactured to operate only at fire temperature and performs intelligent operation [8]. Figure 4 shows the form of capturing Novec 1230 gas in a microcapsule.

Figure 5 shows various types of applied molded articles using microcapsules. The microcapsule molded body is maintained for a long period of time, has a 90–95% fire-extinguishing function even when stored for several years, and has a high waterproof effect.

The microcapsule composition occupies more than 80% of the material and instantaneously explodes at a set temperature of 110 to 165 °C to suppress a fire.

Table 1. Material specifications constituting the microcapsule.

Sortation	Pad	Cord	Tube
Material quantity	2.5~40 g	25 g	10 g
Protective volume	3~60 L	150 L	2000 L
Storage temperature	50~80 °C
Activation temperature	120 °C	180 °C	120 °C

shows the material specifications constituting the microcapsule [8].

2.2. Sensor IoT Architecture and Gateway Communication Configuration

Figure 6 shows the control diagram for controlling the microcapsule in case of fire contact. The temperature at which the capsule bursts is 110~165 °C, which is the same as the fire temperature, and a heating wire is wound around the capsule and current flows to heat it to 200 °C or higher so that the capsule bursts. Nichrome wire is used as a heating wire, and it can generate heat at 200 °C or higher within 10 s, and it is implemented so that it can generate heat even when supplied with a lithium ion battery.

Figure 7 shows the implementation of an IoT circuit that processes signals detected from sensors. It consists of a microcontrol unit (MCU) that controls the received signal and SPI that connects the peripheral sensing function, GPIO, UART, and wireless LoRa. The program editor and downloader use the AVR Studio Programmer [9,10].

In Figure 7, the circuit unit that processes multiple sensor signals on the input side detects the fire temperature, CO₂, GAS, and smoke and collects sensor data. At this time, the sensor data conversion unit that checks the power required for each sensor and the transmission/reception unit that transmits and receives are followed. The MCU control unit (mesh network configuration) controls multi-sensor data control, network configuration between modules, risk warnings, and messages and manages the radio control unit that transmits messages wirelessly. The radio control unit transmits data through an antenna connection [11,12,13].

Figure 8 shows the configuration of the UART and the main MCU board in a form that can be combined or detached by a cable. It can be installed anywhere inside the distribution panel. It is also possible to prevent direct damage from fire by installing the main MCU board outside the distribution panel. UART is an integrated circuit that asynchronously communicates parallel data of the MCU as serial data. In the 8-bit data format, it is promised that synchronization signals can be found on the receiving side to process the start and end of the data in time [14].

The 14 GPIO operates in real time on the user connection unit, the PC operation unit, and the 32 KHz oscillator. The SPI is connected to a wireless communication antenna using the Lora module. These functions are processed by a command processor linked by a communication protocol. Figure 9 shows a fire detection fastener protocol between a fire breaking news machine and a long-distance IoT.

The communication protocol initially consists of control statement signals (Start of Text, STX), module address, system status, alarm status, cycle error check (CRC), and end of text (ETX). The operation of the configuration bits will be described through the data bits performing each function. In addition, flame-retardant PBT, PC/ABS, etc., are used as a protective measure against high temperatures and, since the heat deflection temperature is 70–130 °C, it can last more than 2 min after the fire detection judgment is made, and communication and fire extinguishing are possible between them. Insulation such as aerogel is used in the IoT-based intelligent fire suppression unit using the internal microcapsule to design it to withstand more heat when the enclosure is insufficient. In addition, capacitors and IC components are selected and designed as products with strong heat resistance. Normally, the power of the product is supplied through an adapter and the battery is charged at the same time and, when the power supply is cut off in the event of a power outage, the battery operates to supply power.

In the case of IoT node failure or intermittent long-distance network connections, local fault tolerance needs to be considered to preserve the system state locally at the edge. To address this issue, we implement a new fault tolerance architecture IoT for IoT applications based on the IoT interworking monitoring computer owned by customers and the cloud interworking technology operated by the national fire safety net. The Edge-IoT architecture consists of three layers: (i) application isolation, (ii) data transport, and (iii) multi-cluster man-administration layer. Based on this tiered design, the architecture allows computing deployment at the edge or cloud without modifying the source code [15]. IoT architecture is designed to provide fault tolerance to both edge and cloud-side clusters and to provide integrated multi-cluster management that enables failover in large interconnected networks. Furthermore, IoT’s separate clusters for edge and cloud allow edge devices to operate independently even when they are separated from the cloud. Thus, this architecture operates in degraded mode even when cloud connectivity is lost. This architecture is logically constructed from underlying technologies with three abstraction layers [16]. Figure 10 shows an application with application separation, data transfer, and multi-cluster management layers and four processing steps, PC.1, PC.2, PC.3, and PC.4. Here, the PC processing container, ET edge topic, CT cloud topic, EN edge node, and CN cloud node are described.

Edge-IoT’s Application Isolation layer wraps individual processes into separate, independent blocks and configures them to act as a single isolated application for transferring data from source to destination. This wrapping is achieved by providing application isolation for convenient software distribution and by adopting Linux containers that allow the processing of data streams regardless of physical hardware. The data transport layer of Edge-IoT provides a pub/sub-messaging framework in which data streams are buffered and replicated across clusters. This allows the architecture to have a logical data flow in the form of a containerized process that uses pub/subtopics as a transmission medium.

Figure 11 shows the functional configuration of the communication network based on Figure 7, Figure 8, Figure 9 and Figure 10. Data communication is performed between the IoT middleware in Figure 8 and the gateway in Figure 9, and the edge IoT architecture of Figure 10, such as application separation, data transfer, and multi-cluster management layer and PC.1, PC.2, PC.3, and PC.4, is programed according to processing steps. Based on this, a program is implemented to achieve edge and cloud according to the sensor data operation. The IoT Wan server performs the publishing function between the MQTT publisher and the LORA server, and the MQTT publisher stores messages, and the Laura server performs the query function through local DB or device registration. The Laura server performs MQTT broker, package analysis, redundancy check and error check, and registration check. When the Laura server pops up the IoT middleware (M/W) monitor, the IoT gate middleware exchanges UI and API Call. In this case, the IoT gate middleware function is programed to perform MQTT subscribers, message queues, data collection, device management, I/O management, alarm alerts, legacy APIs, and real-time processing. A user interface (UI) monitors, operates users, operates programs, and operates menus through a dashboard.

Edge core software (Edge-D.N.01) is installed on the user’s edge device, and the core device created in the cloud through this refers to the user’s edge device. Core devices can connect to various IoT devices through certificates issued by the cloud IoT core, and the devices connected in this way are called client devices. When a message is sent from a client device to a core device, edge core software receives the message after verifying that it is a trusted user. After checking the message in real time, it can be immediately sent (issued) to another client device. In addition, messages can be exchanged with the cloud IoT core through bridge service distribution, and codeless services such as cloud functions can be executed on the core device. Edge core devices must be constantly connected to the cloud through a public network.

Edge core software is program that is installed on core devices and provides security authentication, local message brokers, bridge services, local cloud functions services, connection information update, and distribution functions. Boyne authentication authenticates a trusted device by connecting to a core device through a certificate issued by the cloud IoT core from various IoT devices. When the local message broker installs Edge core software, it basically provides a message broker that supports the MQTT protocol. Messages can be sent and received by identifying trusted client devices through certificate security.

Figure 12 constitutes the entire fire alarm network. The automatic fire fastener first contacts the fire car station in the event of a fire, controls the emergency opening and closing of the building, and issues a fire occurrence alarm signal through the siren [17,18,19].

Recently, buildings have been equipped with GR-type complex receivers. Most buildings are managed by building management monitoring, and GR complex receivers are also mounted. An automatic fire detection device is attached to the fire hydrant on each floor inside the building to indicate the occurrence of a fire and warn of an emergency. With the development of the national emergency contact network, drones play the role of observing and guiding complex topography and, recently, they have performed tasks to observe fire occurrence areas in high-rise buildings [20,21].

3. Experimental Results

3.1. Smoke and Heat Sensing Performance Experiments

When the fire suppression device is installed close to the fire area of the distribution panel, fire will occur within 10 s in case of a fire. It suppresses ash. Pad and cord-type fire-extinguishing products can be easily installed in a narrow space (2~3 mm) without special facilities or construction and can be applied to various targets. Particularly, it is easy for the public to install, and it can be used not only for new facilities but also for various exposures to old industrial sites, public places, buses, and schools with high risk factors. Figure 13 shows a configuration example in which the main MCU PCB is installed with the sensor position within the electric distribution panel.

Figure 14 models a rectangular parallelepiped-shaped distribution panel case with a width of 80 cm, a length of 25 cm, and a height of 160 cm as a fire model. Three rows are hung from the ceiling of the distribution panel at equal intervals, and three temperature sensors are installed evenly at equal intervals in each row, and the detector is installed on the upper left [22,23].

The light is on at the bottom of the left spherical box. The numbers in the second spherical box are marked from 1 to 9 with pad-type materials at the bottom. The fire at the bottom instantly burns the pad and emits smoke when the two boxes are stacked to make them an enclosed space. The attached smoke sensor and heat sensor detect the generated smoke and heat, transmit data through the IoT, and send an alert to the mobile device at the same time as a warning to the monitoring control screen.

Figure 15 shows the changes in temperature and smoke concentration over time. In the implemented system, an experiment is conducted to measure the air temperature inside the distribution panel using a hot air fan under the distribution panel. The temperature of the hot air fan was set to 630 °C, and the initial temperature inside the distribution panel was set to 26 °C. It took about 7 min for the temperature to rise to 60 °C, and a temperature increase curve was recorded and used to set the temperature increase width of the difference sensor [20].

Figure 16 shows the temperature change for each sensor position No.1~9 in Figure 14. Here, the temperature at positions 7 and 4 is the highest. After that, 8, 1, and 2 were high, and the temperature at positions 3, 6, and 9 on the right was the lowest. Through this, it can be assumed that, although the combustible material is located in the center inside the distribution panel, in the convection phenomenon by heat, the heated air tilts to the left and rises and falls to the right. It can be seen that the temperature in the detector rises steadily with an S-shaped conversion curve at a rate of about 48 s to 2 °C/min for about 3 min and then falls again after a high point.

Figure 17 shows that the smoke density gradually increased from 48 s in an irregular shape and reached more than five times the initial smoke density after about 20 s, after which it converged to the high point uniformly. It is examined whether the flame sensor (infrared sensor) of the complex sensor installed in one upper corner of the distribution panel fire model can detect the flame generated from the fire source normally. Since the flame of the fire is detected by the complex sensor 6 s after the measurement begins and the flame sensor operates in the on–off contact method, it is possible to confirm the occurrence of the fire. Rather, it is reasonable to accept that there is a high possibility of fire due to the occurrence of sparks due to static electricity or short circuits.

The smoke sensor and temperature sensor test standards apply to the type approval and technical standards of the Korea Fire Protection Testing Institute (Fire Service Notice No. 2019-10), and the sensitivity test of the constant temperature sensor in Article 16 and the sensitivity test of the ionization sensor in Article 18 are applied mutatis mutandis. The temperature sensor malfunction test shall satisfy the performance conditions because it does not operate within 10 min at a temperature 10 °C lower than the nominal operating temperature.

Table 2. Results of the malfunction test of the temperature sensor and the smoke sensor.

Test Items			Test Results	Performance Requirements
Fire detection capability (Sensitivity test)	Temperature	Operation test	3 s	Operation within 34 s
		Nonoperatopn test	Inoperative within 10 min	Inoperative within 10 min
	Smoke	Operation test	9 s	Operation within 30 s
		Nonoperatopn test	Inoperative within 5 min	Inoperative within 5 min
Notice time	Temperature		3 s	Notification within 20 s
	Smoke		9 s

shows the results of the malfunction test of the temperature sensor and the smoke sensor.

The communication speed of IoT devices is mostly 100 Mbps and, in this study, the important evaluation factor is to detect high temperature or smoke and to notify the fire alarm within 10 s due to the explosion of microcapsules in the event of a fire. Therefore, Table 2 was found to satisfy the performance requirements, especially by showing the test results notifying the alarm test within 10 s. The certification of the fire occurrence alarm within 10 s reflects the results of the Honagyeong experiment in Korea Test Laboratory (KTL) and the Korea Fire Institute (KFI), which certifies fire experiment. Therefore, in the development of research papers, the operation of announcing the alarm at a high speed of 10 s can be of great significance.

The smoke sensor malfunction test shall not operate within t minutes in wind speed V cm/s airflow containing a concentration smoke with a current change rate of 0.65 k. The smoke sensor operation test condition is 1.35 K = 1.35 × 0.24 = 0.324, and the test concentration (5~10%/m) = 100 × (0.324 − 0.19) + 5 = 11.165%/m, and the operation test condition is 0.65 K = 0.65 × 0.24 = 0.156. It is calculated as the test concentration (0–5%/m) = 26.3 × 0.156 = 4.1028%/m. Therefore, for the ionization transformation rate of change to the smoke concentration (%/m) in the smoke sensor non-operation test, the performance condition within 5% is satisfied with 4.1028%/m.

3.2. Mobile Performance Evaluation by Sensor Behavior

Figure 18 is a flowchart of a program implementing an app for setting a number index and a location of a sensor and an IoT installation location. In (a), device information is set by reading individual IoT module authentication and data installed on the distribution board (node). In (b), messages necessary for the mobile device after inputting location information to be installed and the phone number of the person in charge are shown. They handle module authentication and registration, module location, remote control, and information management necessary for control.

Figure 19 shows the design of the communication module allocated for fire fighting and the frequency chamber test. The specifications of the frequency 447 Mhz_Sub-G module allocated for fire fighting are shown in

Table 3. Specifications of 447 Mhz_Sub-G Module development.

Items	Design Specification	Remarks
Frequency used and Channel	447.2625~447.5625, 25 h
Physical hierarchy (FHY)	IEEE 802.15.4.4 g
Modulation methods	FSK, 4FSK, MSK, OOK
Chip set	Silicon, Labs, EZR32LG	32 bit core
Maximin Power	10 dBm below
Maximum reception sensitivity	133 dBm above

[17], and the electrical specifications are shown in

Table 4. Electrical specifications of the product.

Symbol	Minimum	Type	Maximum	Unit
VCC	2.7	3.0	3.6	V
Leakage current	0.3	-	3.0	µA

. Based on Table 3 and Table 4, a card slotted wireless communication (RF 447 MHz) module that can communicate with the gateway is implemented.

Hardware configuration utilizes an ARM CORE-TEX M3-based radio-only RF MCU and the communication section takes place at a distance of 500 m to 1 km. The utilization frequency range supports 447.8 MHz to 447.9 875 MHz BAND for 11-channel data transmission and 447.2 MHz to 447.5 MHz BAND for 25-channel safety systems. The Media Access Control (MAC) protocol of IoT devices supports minimum transmission latency and power consumption through dynamic scheduling methods, channel hopping methods, and dynamic slot allocation that can communicate with neighboring nodes in groups.

Table 5. Experimental Results between Sensors, IoT, and modules.

Evaluation Items	Evaluation Methods	Experimental Results
Fire detection capability	Temperature and smoke detection time	Temp.: 3 s, smoke: 9 s.
Temperature resistance	Fire-free holding temperature time	−10~50 °C
Time to reach the operating temperature of the microcapsule	Fire reaction time of microcapsules after fire breaks out	4 s or less
Wireless test distance	Open field test	More than 500 m
Software Response Speed	Measuring the software’s response speed at the same time as fire detection	1.12 s or less

conducts a fire test based on the sensor points in Figure 13 and Figure 14, and it shows the results of the communication test through the module in Figure 19.

Figure 20 shows a test that informs the mobility of fire information sent from the fire location when a fire occurs. In the event of a fire, the communication test between the gateway and the fixed IoT location installed between residential areas or buildings is tested through the mobile device. It provides a way to access through rapid connection between the location of the fire and the fire-fighting vehicle.

But, where buildings are concentrated, there is a limit to the medium distance, so the surrounding Wi-Fi or Bluetooth interworking is possible. Smooth communication was achieved when the opening area or the height of the building was low [23]. The use of the state-run fire safety net has many advantages in tracking the location of the fire but, in the case of recent 5G communication, more changes and implementations are needed depending on the communication environment

4. Conclusions

Most of the property damage caused by fires is due to the absence of initial fire suppression means, narrow vehicle entry, and complex internal structures, missing the golden time of fire suppression. If a person is unable to reach or is far from attention, the location of the fire is initially identified to implement a system that can track the location of the fire along with the identification of the cause.

In this study, a Novec 1230-based microcapsule is used, and the standalone-type microcapsule built-in paste that can be automatically extinguished in the event of a fire through the development of an IoT sensing convergence module is constructed. It is effective in installing a convergence device that can be easily applied to the expected location of the fire and suppressing the fire risk in the shaded area where the human view is not secured and the fire in the local fire occurrence location.

The technical standards for type approval and product inspection of the Control Test Research Institute detector (Fire Service Notice No. 2019-10) were applied to the smoke sensor and temperature sensor test standards, and the sensitivity test of the constant temperature sensor and the sensitivity test of the ionization sensor of Article 18 were applied.

The temperature sensor nonoperation test satisfies the performance condition because it does not operate within 10 min at a temperature 10 °C lower than the nominal operating temperature. When the ionization conduction change rate is converted into smoke concentration (%/m) under the smoke sensor nonoperation test condition, it is 4.1028%/m, which satisfies the performance condition within 5%. The wireless communication module that communicates with the IoT sensor fusion device has an indoor wireless distance of about 20 to 50 m in the 447 MHz band and can communicate more than 1 km outdoors (open field).