Fire Alarm System Research Articles

Ensuring the Correctness and Reliability of CBPS System Using Event‐B

ABSTRACTDuring the early phases of software system development, error detection can be challenging due to the complexity of both the requirements and the operating environments. This paper advocates for the utilization of formal modelling and verification throughout the first phases of systems development to promptly detect and correct errors. The formalism employed throughout is Event‐B, which is backed by the Rodin toolset. To conquer requirements complexity, the frameworks of set theory and first‐order logic are employed, which provide the necessary tools for formalizing and analysing the properties and behaviours associated with Event‐B. Also, we detail the way in which modelling may be used to achieve abstraction, as well as the way in which refinement can be used to manage complexity through layering. Furthermore, we emphasize the significance of model validation and verification in improving the precision of formal models and requirements in IoT communication systems. The model is exemplified using a Content‐Based Publish Subscribe System (CBPS), with a special emphasis on a fire alarm system as a motivating example.

Multi-Sensor Photoelectric Fire Alarm Device Implementation for Early Fire Detection in Campsites

With the growing popularity of leisure activities such as camping and glamping, the incidence of fires at camping sites has increased. This study focuses on improving the effectiveness of photoelectric fire alarm devices by incorporating temperature and humidity data for early fire detection in confined spaces, such as campsites. This study proposes a novel multi-sensor fire alarm system that dynamically adjusts fire detection threshold values based on temperature and humidity data collected by unmanned automatic weather observation systems. The prototype, which was implemented using Raspberry Pi and multiple sensors, demonstrated approximately 20% faster fire detection speed than existing photoelectric fire alarm systems, as verified through experiments in a simulated camping environment. The proposed approach is expected to advance fire alarm systems, enabling faster and more accurate fire detection in diverse environments, particularly at campsites.

IoT-Enabled Fire Alarm System with Cloud-Based Storage and Monitoring

Abstract: The purpose of a fire alarm system is to warn us of an emergency so that we can take precautions to safeguard ourselves, our employees, and the public. However, modern fire alarm systems require a significant amount of wiring and labor during installation. The most frequent issues that was encountered during monitoring commercial and residential fire alarm systems are false alarms, inappropriate installation, lost connections, malfunctioning or aged equipment, and careless maintenance that discouraged users from putting them in their houses as a result. Hence, the researcher developed an IoT-based fire alarm system connected to several types of sensors and micro-controller distributed over the building and house. Each of these nodes is made up of an Arduino microcontroller that is coupled with smoke, temperature, humidity, flame, methane, and carbon monoxide (CO) sensors. Thus, an innovative system is designed with the help of Internet of Things (IoT) that records live reading of sensors and stored in cloud interface which also lessens the investigation process of the authorities concerned. Results shows that majority of the evaluators responded to the functionality of the proposed system to be Superior and provide all the functionality required for the system to detect and prevent fire occurrences.

Automated image-based fire detection and alarm system using edge computing and cloud-based platform

To tackle the increasing wildfire challenges, this paper presents an automated image-based fire detection and alarm system utilizing edge computing and a cloud-based platform, specifically designed for urban building fire detection. The system captures both RGB and infrared images from thermal cameras and employs existing computer vision techniques to detect fire characteristics such as flames and smoke. By integrating edge computing, the system minimizes latency to enhance the accuracy of fire detection and alarm activation. The cloud platform supports extensive data storage, analysis, and remote monitoring, which can ensure data accessibility and scalable data management. The proposed system descriptions include a detailed system architecture design, data collection, and the selection and application of detection algorithms that leverage both RGB and thermal image data for fire detection. Using the campus building and surrounding risk-prone areas as a testbed, the proposed system demonstrated desired fire detection capabilities and a robust solution to quickly identify and respond to fire incidents within the urban area. The proposed system functionalities can be scaled and adapted to other fire risk-prone areas.

Automatic device arrangement and wiring for fire alarm systems in metro stations: A case study

Fire alarm systems in metro stations play an important role in safeguarding lives and properties. The design process for these systems is complex and time-consuming due to the diversity of device types, wide distribution of device locations, and numerous compulsory design codes. This paper proposes an automatic design framework for fire alarm systems aimed at enhancing design efficiency. The framework includes five automated processes: information preprocessing, device arrangement, system loop generation, device wiring, and result generation. By converting the computer-aided design (CAD) results into building information models (BIM), building information and related professional device information are obtained, addressing the need for fire alarm system (FAS) design to integrate with multiple disciplines. The process can also automatically arrange FAS devices according to design specifications. Optimization algorithms, such as Ant Colony Algorithm and Prim Algorithm, are used to determine the device connection order and solve the problems of obstacle avoidance and orthogonal connections between two points. Compared to traditional design methods, the proposed automatic design framework for fire alarm systems in metro stations can not only satisfy the mandatory design requirements but also avoid the cumbersome and repetitive design process, providing new solutions for designers. Additionally, it can reduce wire length and save on construction costs. Using a real metro station as a case study, it is calculated that the automatic design can save between 8 % and 48 % of the wire length.

A hierarchical k-out-of-n optimization model for enhancing reliability of fire alarm systems

Fire alarm systems are crucial for mitigating the risks and damages associated with fires in process industries. These systems heavily depend on the performance of fire detection sensors to provide early detection and warnings, facilitating prompt evacuation and intervention measures. In order to improve the reliability of sensor systems typically requires the use of redundancy allocation techniques, such as a k-out-of-n configuration. In k-out-of-n configuration, the signals from all sensors are directed to a voter, which compares them and transmits a final signal once at least k signals are matched. However, challenges arise due to diverse failure modes with distinct impacts on the system. Integrating sensors through a single-layer k-out-of-n configuration, when there is only one voter, fails to fully highlight the potential advantages of redundancy in sensor systems. This paper addresses the limitations of the conventional configurations by introducing a hierarchical k-out-of-n system in which sensors can be integrated across multiple layers. In the k-out-of-n hierarchical system, sensors are organized into distinct groups, each employing its own k-out-of-n sub-system. Subsequently, the outputs of these sensor groups can be integrated with other groups through their respective voters in higher layers of the hierarchy. Ultimately, at the top layer, all the voters from the preceding layers must be connected to a top voter to transmit a final signal. Furthermore, an optimization model is developed to minimize the system cost while maximizing reliability, considering the best selection of sensors and the system configuration. The proposed optimization model takes into account a multi-sensor system with two competing failure modes and incorporates the probability of sensors' failure modes in the system. The hierarchical k-out-of-n system provides an opportunity to validate sensors by comparing them within their designated groups, allowing for the identification of the location of a failure and the planning of appropriate actions accordingly. The proposed optimization model is applied to a case of a fire detection system in storage warehouse to demonstrate its advantages over the conventional model.

Solar Powered Smart Emergency Light with Fire Detection and Alarm System

Solar Powered Smart Emergency Light with Fire Detection and Alarm System

Gelatin-based ionic hydrogel for intelligent fire-alarm system with considerable toughness, flame retardancy, and thermoelectric performance

Temperature-responsive materials with excellent reliability, sensitivity, and flame-retardant properties have always been an urgent need in the field of intelligent fire protection. In this discourse, we introduce a novel thermosensitive ionic hydrogel coating (gelatin/poly(acrylamide-co-acrylic acid)/CaCl2/spindle-shaped aluminum hydroxide nanosheet/glycerol, HCA) synthesized via free radical polymerization. HCA not only demonstrates considerable mechanical properties with a fracture strain of up to 842.5 % and a maximum tensile strength of 0.77 MPa but also exhibits notable flame retardancy and adhesion. It effectively covers combustible surfaces, providing outstanding fire protection. Notably, HCA boasts a Seebeck coefficient of up to 10.1 mV/K, significantly surpassing conventional thermoelectric materials. The well-established linear relationship between the generated voltage and temperature variation enables HCA-based intelligent fire-alarm system to accurately emit continuous alerts during fire incidents and swiftly transmit alarm signals to terminal devices. The development of this intelligent fire-alarm system presents new avenues in intelligent fire-safety technologies.

Research on thermal runaway early warning algorithm of lithium battery based on improved particle swarm algorithm optimized BP neural network

Abstract In response to the issues of false alarms and missed alarms in traditional fire alarm systems for energy storage station fire prevention and control, this study proposes a fire alarm approach employing improved PSO-BP neural networks. Firstly, we set adaptive inertial weights and asymmetric learning factors on the PSO algorithm that are automatically optimized as fitness changes to improve the optimization accuracy and convergence speed of the algorithm. Secondly, the thresholds or weights are mapped to random particles for training to obtain the optimal value. Finally, utilizing the Pyrosim software, a model of the battery cabinet was established, and the thermal runaway data samples were input into the neural network model for training. The test consequence indicates that the improved PSO-BP model achieved a 5% and 3.75% rise in precision relative to the neural network and PSO-BP model, respectively, while the frequency of iterations declined by 55% relative to the PSO-BP.

Decreased Smoke Detector Performance Functionon MV. Sarah S

Ships are vessels used for transporting passengers and goods across bodies of water, such as rivers and seas, using canoes or smaller boats. Fires on ships can occur due to various reasons, including interference with electrical and electronic equipment, as well as flammable liquids like gasoline, grease, and gas leaks. This study adopts a descriptive qualitative approach, utilizing data collection methods such as direct field observation, in-depth interviews with involved parties, and documentation/library research. The research findings highlight two main points: 1) The factors leading to decreased functionality of fire alarm sensors are the lack of maintenance and repair of the system; and 2) A decreased fire alarm system may fail to detect fire or smoke in specific areas, potentially leading to accidents or severe damage to the ship.

Integration of Dual Fire Alarm Self-Powered System: Leveraging Intelligent Wearable Flame-Retardant Hydrophobic Cotton Fabric

In the realm of smart textiles, an area garnering significant research attention and demonstrating vast developmental potential, we have conceived and fabricated a multifunctional smart textile with a fire dual-warning function. This innovation integrates thermoelectric performance, triboelectric nanogenerator (TENG), flame retardancy, and hydrophobic functionalities into a cohesive entity. Employing a straightforward impregnation method, we successfully infused cotton fabric (CF) with a novel flame retardant (named AA). Additionally, CF/PPA is modified by incorporating poly(3,4-ethylene dioxythiophene)-poly(styrene sulfonate) (PEDOT:PSS) and polydimethylsiloxane (PDMS) as separate layers, with the former providing thermoelectric properties and the latter enabling TENG functionality in smart textiles. This configuration exhibits excellent voltage output performance, generating a thermoelectric effect of 221 mV under a temperature differential of 76 K and achieving voltage output as high as 138 V at a vertical contact-separation frequency of 5 Hz. The superior dual-warning function, flame-retardant properties, and hydrophobicity of CF/PPA can be integrated into firefighting apparel, thereby establishing fire-alarm systems with remote signal transmission capabilities to enhance personnel safety. Furthermore, CF/PPA holds promising dual warning application prospects in the field of wearable flame-retardant and fire-alarm systems, thus paving new avenues for the utilization of smart textiles in the realm of the Internet of Things (IoT).

Robust and ultra-sensitive self-powered fire warning sensor based on polyimide thermoelectric fibers for temperature sensing and intelligent fire safety monitoring

Fire warning sensors is crucial to effectively prevent fire accidents in a variety of modes and meet the needs of the connected age. Nevertheless, there is still a formidable challenge in fabricating self-powered fire warning sensors that are flexible and can be integrated in combustible materials. In this work, flexible high-fireproof polyimide (PI)/hydroxyapatite (HAP)/Ag2Se composite aerogel fiber (PHA-AF) was fabricated by specific wet spinning technology. The extraordinary thermoelectric effect of Ag2Se enabled PHA-AF to achieve precise temperature sensing over a wide temperature range of 100 °C–500 °C. Simultaneously, the PHA-AF-based fire alarm sensor could trigger a fire alarm system in 1.9 s and respond continuously for 14 s under flame attack, while generating output voltage of up to 5.9 mV in self-powered mode. Notably, PI as a flame-retardant material could be formed the 3D networks with HAP, as well as the skeleton support effect provided by Ag2Se nanorods enabled PHA-AF based fire alarm sensors with superior breaking tenacity (2.9 MPa), strong heat stability (maximum weight loss rate at 550 °C) and flame retardancy (LOI = 35.8 %), further highlighting its authenticity, repeatability, and reliability in fire. This work offers potential for the preparation of fiber-based self-powered early fire alarm sensors for long-term continuous using in harsh fire environment.

Analysis of the possibility of increasing the level of reliability of fire alarms systems through integration with video-based flame detection system

Classic Fire Alarm Systems (FAS) are characterized by a high level of false alarms in relation to the number of confirmed reports. To increase the level of reliability of operation of this type of system, it was proposed to integrate it with a Video-Based Flame Detection System (VBFDS). For this purpose, a video-based fire detection algorithm was designed. In addition, methods popular in the literature for increasing the reliability of such systems, such as color filtering, the Tracking Growth Object (TGO) factor, and the use of the Naive-Bayes (NB) classifier, were tested. The purpose of the article is to analyze these methods in comparison with the basic version of the algorithm, as well as the possibility of integrating Video-Based Flame Detection System (VBFDS) with classic FAS.

ИСПОЛЬЗОВАНИЕ СОЛНЕЧНЫХ ПАНЕЛЕЙ ДЛЯ ПОВЫШЕНИЯ НАДЕЖНОСТИ СИСТЕМ ЭЛЕКТРОСНАБЖЕНИЯ СРЕДСТВ АВТОМАТИКИ И СИГНАЛИЗАЦИИ

The use of solar panels to provide uninterrupted power supply to automatic fire alarm systems is considered, which not only increases the reliability of their power supply, but is also advisable due to the low current consumption of these systems

The Dynamic Change in the Reliability Function Level in a Selected Fire Alarm System during a Fire.

This article discusses fundamental issues associated with the functional reliability of selected fire alarm systems (FASs) in operation during building fires. FASs operate under diverse external or internal natural environmental conditions, and the operational process of FAS should take into account the impacts of physical phenomena that occur during fires. Their operation is associated with the constant provision of reliability. FAS designers should also consider the system's reliability when developing fire control matrices, tables, algorithms, or scenarios. All functions arising from an FAS control matrix should be implemented with a permissible reliability level, RDPN(t), prior to, as well as during, a fire. This should be assigned to the controls saved in the fire alarm control unit (FCP). This article presents the process by which high temperatures generated during a fire impact the reliability of FAS functioning. It was developed considering selected critical paths for a specific scenario and the control matrix for an FAS. Such assumptions make it possible to determine the impact of various temperatures generated during a fire on the reliability of an FAS. To this end, the authors reviewed that the waveform of the R(t) function changes for a given FAS over time, Δt, and then determined the fitness paths. The critical paths are located within the fire detection and suppression activation process, using FAS or fixed extinguishing devices (FEDs), and the paths were modeled with acceptable and unacceptable technical states. The last section of this article defines a model and graph for the operational process of a selected FAS, the analysis of which enables conclusions to be drawn that can be employed in the design and implementation stages.

Ultrastrong and Thermo‐Remoldable Lignin‐Based Polyurethane Foam Insulation with Active‐Passive Fire Resistance

AbstractFoam thermal insulators are indispensable for prevailing energy‐saving engineering, however their widespread use brings intractability such as unsustainability, “white pollution”, and fire hazards. The emergence of bio‐based foams is highly appreciated, but the fabrication approaches are economically unattractive and/or the product properties are inferior, making their large‐scale implementation unviable. Herein, a versatile, thermally remoldable phosphate‐containing polyurethane composite foam (LPU‐G) is constructed from natural lignin and expanded graphite flakes via an atmospheric pressure and scalable one‐pot strategy. The optimal LPU‐G exhibits exceptional mechanical strength, capable of supporting over 6000 times its weight without significant deformation. Moreover, the LPU‐G demonstrates the desired multifunctionality in handling extreme circumstances, including humidity‐tolerant thermal insulation, superb water vapor barrier, and withstanding ≈1200 °C flame without ignition. Based on the “expansion‐conductivity” micro‐mechanism, LPU‐G is the first foam material to be constructed as a sensitive fire alarm system with an ultra‐long alarm time (>1800 s). Surprisingly, LPU‐G can be rapidly upcycled into recyclable bulk composites for a second life through simple thermo‐molding processes rooted in the multi‐dynamic behavior of the phosphate, carbamate, and hydrogen bonds. The easy‐to‐scale LPU‐G represents a new generation of thermal insulators that address concerns regarding unsustainability, high cost, fire risk, and inferior mechanical properties.

Proposed Changes to the Inspection Strategy for Fire Alarm Systems: Empirical Analysis of Weak Points and Technical Influencing Factors

Fire alarm systems are an important part of the safety concept in complex buildings. For this reason, there are high availability requirements for the systems, which must be sustained by a maintenance concept. A shortage of skilled workers and rising costs in the construction and operation of buildings are pushing these concepts ever further. This study deals with proposed changes to the maintenance strategies to achieve cost and time savings in addition to an improvement in quality. As a first part of the work, the current state of research on developments in fire alarm systems and their maintenance and inspection concepts is analyzed within a literature review. The results serve as a basis for further research, which is based on a qualitative content analysis of expert interviews and standardized surveys to identify the weaknesses in current inspection strategies and future factors influencing the methods and technology of inspections through technical innovations. As a data basis for this study, expert interviews were conducted with experts from manufacturers, industry associations, and standards bodies in order to determine the possible influencing factors. To determine their relevance for the inspection, more than 40 experts were surveyed about testing the systems. The presented results show that new technical risks, such as cyber threats and networked plant structures, are insufficiently covered by current inspection strategies. Furthermore, inspection steps can be substituted by new technologies. The most important influencing factors that can be identified here are automatic self-test functions of components and remote inspection techniques of the systems. Finally, the results are discussed within the framework of a PESTEL analysis. In conclusion, it can be stated that the integration of identified impacts in future inspection strategies brings time and efficiency benefits in the operation of systems.

Optimal layout scheme of fire detectors and operation condition monitoring technology in urban integrated substation

Aiming at the problem that it is difficult to obtain the life cycle law and detection coverage of fire detectors and the low reliability of fire alarm process in urban integrated substation, an optimal layout scheme and operation condition monitoring technology of fire detectors based on local outlier factor and neural network are proposed. Divide fire zones by equipment functions, calculate the number of fire detectors required by using ground area and indoor height, and integrate building automation system to create substation fire alarm system; The signal noise of fire detector equipment is eliminated by wavelet transform, the fuzzy characteristic analysis model of fire detector operation state is established, the local outlier factor is simulated as abnormal data, the past operation data is trained by BP(Back propagation) neural network, the difference between the current state and the normal operation state is obtained, and the detector operation state monitoring is completed. The operation reliability of fire detector is analyzed from the aspects of temperature and smoke perception. The simulation results show that the proposed technology can successfully obtain the life cycle law and detection coverage of fire detector, and ensure the safe use of urban integrated substation. In addition, through a series of experiments, the feasibility and effectiveness of this technology in practical applications are verified.The maximum time consumption of detector working condition monitoring in this method is only 3.3 s. The fitting degree of the method in this paper is 5.7 ml/m3, and the fitting degree of the actual smoke curve is 5.7 ml/m3. The temperature of the method in this paper is lower than 33 °C. In the future development, the introduction of more advanced self-diagnosis technology can be real-time monitoring and analysis of the status of the detector itself, timely detection of faults or anomalies, and automatic alarm or notification of maintenance personnel for repair and maintenance.

The role of FAS in the context of raising building safety standards

The paper presents the role of fire alarm systems in buildings and proposes a framework for an application supporting the operation and maintenance of fire alarm systems (FAS). FAS should be properly maintained from the first day of commissioning. The state of readiness during operation should be maintained at the initial level. However, during the working time, the properties of the systems deteriorate, which is related to factors such as: failures, human activity, hidden defects, faulty assembly or external factors. FAS malfunction is a potential threat to the safety of people, property and the environment. The implication of the solution will reduce risk and improve fire protection activities in buildings. The proposed plan to maintain the efficiency of FAS will also allow for the standardization of procedures and the increase in the overall safety of property, health and life, as well as the natural environment.

Analysis of Failure in The Fire System Alarm on The Ship KL.02 Sultan Hasanuddin

Abstract International Maritime Organization (IMO) has set regulations governing the installation of fire alarm systems on ships. The basic principle of the control system is to control the system output by comparing the actual output with the desired output. This study aims to determine the causes of false alarms on the fire alarm system on ships and to describe recommendations and solutions for failures in the fire alarm system on ships. This type of research uses a mix of methods by utilizing primary and secondary data. The data is processed by quantitative analysis and qualitative research. The results of this study indicate that the cause of the False Alarm on the Fire Alarm System is caused by the MFCA, Smoke Detector, and Cable Installation. The case that occurred in KL. 02 Sultan Hasanuddin there is no correlation between false alarms on the Fire Alarm System. The Smoke Detector correlation data with the False Alarm Fire Alarm System shows that there is a correlation with the Pearson Correlation of 0.857 > 0.4973.