Automatic fire alarm and fire control linkage system in intelligent buildings

This research work provides an in-depth analysis of the fire alarm system, considered as a security tool for a variety of facilities, from industrial buildings to residential premises. Two key subsystems serve as the basis for the study: the fire alarm system, which is designed to detect and report the occurrence of fire, and the intrusion alarm system, whose task is to detect attempts at illegal intrusion. For each of these subsystems, their functions and components are investigated, their mechanism of action, principles of operation, and possible implementation options are described, depending on the specific conditions and security requirements. At the same time, emphasis is placed on three types of automatic fire alarm systems: threshold, addressable and addressable-analog, each of which has its own features, advantages and disadvantages. The article goes beyond theoretical analysis and presents the results of a practical study of the three main types of fire alarm systems: wired, wireless and addressable. The study is based on a specially designed training stand, which allows you to simulate the operation of fire alarm systems in conditions as close to reality as possible. The article demonstrates the connection schemes of detectors, explains their states in the "normal" and "alarm" modes. It is noted that the currents and voltages of alarm loops in different modes were measured. Dependency diagrams of these parameters are presented, and the alarm threshold levels are measured. The research presented in the paper provides a valuable contribution to the study and optimization of alarm and fire systems, providing meaningful data for the development and testing of these systems. The paper can be useful for fire and security professionals and those interested in improving the performance of these systems.

CMS Finalizes Revisions to Conditions to Participation

This report provides a summary of the fire protection and life safety features for UW Medicine Lake Union, a research and laboratory building, in accordance with Seattle Building Code (SBC), International Building Code (IBC), and Life Safety Code (NFPA 101). The objective of this report is to identify if UW Medicine Lake Union meets both the prescriptive and performance based code. The primary fire safety goal is to provide life safety system that reduced the risk of fire-related injuries and loss of life due to fire. The prescriptive analysis is used to identify the building integrity per code. This evaluates the egress capacity, fire detection, fire suppression and structural fire protection. The UW Medicine Lake Union includes numerous laboratories that regularly utilize various hazardous materials. According to the literature in the Architectural drawings, the design team worked with the university does that the chemical quantities in these areas would not exceed the limits set forth in the code. With these limits in place, portions of the facility did not need to be classified as hazardous occupancy, and the special provisions associated with a hazardous occupancy. Although its spaces are used in various ways, the building was able to be classified as business occupancy. Hazardous occupancy areas were not required because hazardous materials were limited to the code-defined exempt quantities. These details helped simplify the overall life safety and egress system, while providing appropriated levels of life safety. UW Medicine Lake Union Building is high rise building with seven story research and development laboratory and two levels of below grade parking garages. It includes testing and research laboratories, laboratory support, offices and conference room. It is approximately 317,382 square feet in gross area and a building height of 109 feet. It is classified as B occupancy classification. The facility is protected throughout by automatic sprinkler and fire alarm systems. The building was constructed in 2011 in accordance with the 2009 Seattle Building Code with a Type 1A construction. See 2.6 Type and Description of Construction. The total occupant load is 2797 occupants. See Table 4: Summary of Occupant Loads. The UW Medicine Lake Union building has six (6) exit discharge. The Main and Back Entrance exit door have 72” doors; P1 (Stair 1), Retail and South exit (stair 3) door have 36” doors, and the garage exit door (stair 4) have 44” door that leads to the public way. See Figure

Background: Fire is one of the potential dangers that threatens human activities more and more. Given that, this study sought to introduce the factors preventing the spread of fire in hospitals to policymakers through prioritization based on the techniques of applied mathematics (multi-attribute decision-making technique).
 Methods: This study consisted of two stages. In the first stage, through a comprehensive review of studies, factors preventing the spread of fire were identified, and then in the second stage, based on the experts’ opinions, the attributes affecting the prioritization and their weights were determined. Finally, based on the Simple Additive Weighting (SAW) model, the final prioritization was done for five types of hospital buildings.
 Results: Based on the literature review and experts’ opinions, seven factors and four attributes were identified. The most important factors were “the use of safety architecture and equipping with appropriate emergency exit accesses according to the standard” in highrise hospitals, “continuous firefighting training of the personnel” in wide hospitals, “use of fire extinguishing systems (automatic and manual)” in subsurface hospitals, “use of fire extinguishing systems (automatic and manual)” in combined hospitals, and “continuous firefighting training of the personnel” in portable hospitals.
 Conclusions: Fire safety is not limited to the installation of a manual fire extinguisher, but for fire safety, especially in hospitals, all aspects should be considered, including the architectural form of the building, how the materials and equipment in the building caught fire, fire behavior in terms of heat transfer, the firefighting training of the personnel, recognition, and application of modern and ready-made equipment for smoke ventilation systems and fire products, automatic and manual fire alarm systems, and extinguishing systems to prevent the spread of fire.

All safety measures have costs and benefits associated to them. A social cost-benefit analysis (SCBA) therefore ideally is a part of fire safety policy decision-making. This chapter introduces the concept of SCBA and its constituting elements. A CBA case study on automatic fire alarm systems is presented to show how an SCBA can be computed. In this case study, the safety benefits of these systems do not outweigh the costs. The SCBA was basis for a policy decision to limit the number of objects for which an automatic fire alarm system is obligatory. Part of the input for any SCBA is insight into the value that the public attributes to aspects such as the presence of the fire service or the value of lives saved by fire safety measures. For the aspect of ‘lives saved’ in the context of fire safety, an estimate of the value of a statistical life (VOSL) is relevant. Not much research has been done to get insight into these values specifically for fire safety. We report on the outcome of an experiment to obtain these values in the Dutch context. Interesting enough, the fire VOSL was found to be a magnitude higher than the road safety VOSL.

The fire detection system combines the simultaneous measurements of smoke, carbon monoxide, and carbon dioxide. The security of campus against intruders moving in laboratories, class rooms, staffrooms or washrooms. The fire alarm system consists of Fire detectors (with can be smoke detector, heat, or Infra-Red detectors), control unit and alarm system. A fire detection system is developed based on the simultaneous measurements of temperature and smoke. The fire detection system with the alarm algorithm detected fires that were not alarmed by smoke sensors, and alarmed in shorter times than smoke sensors operating alone. Previous fire detection algorithms used data from sensors for temperature, smoke, and combustion products. The smoke sensor alarms when the analog output signal exceeds or equal the threshold value. The node includes analog sensors to measure smoke, carbon monoxide (CO) and temperature. A fire alarm system should reliably and in a timely way notify building occupants about the presence of fire indicators, such as smoke or high temperatures.

Chapter 6 - Fire Alarm Systems

This study attempts to address the technical challenges of early fire detection and rapid remote verification in unattended locations. A fire image transmission method based on the data bus of Automatic Fire Alarm System (AFAS) is proposed. The Gaussian difference algorithm is used to extract feature parameters of background image and fire image. Difference regions are accurately identified by comparing the feature extrema of these two images. An encoding strategy is adopted to perform compression encoding only on the difference regions instead of the full fire image. This significantly reduces the transmitted data volume and improves the transmission efficiency, enabling remote transmission of fire image via the existing data bus of AFAS. Experimental results show that the remote transmission time of fire image is mainly affected by the resolution of the image acquisition module, the proportion of the difference region, and the transmission distance. By adjusting the resolution of the acquisition module and the layout position of the detector, the effective transmission distance could be extended. The proposed method requires neither modifying the wiring of the existing AFAS nor building a new dedicated image transmission line, thus offering significant application advantages.

Commercial buildings are considered as high‐risk units in fire due to the existence of expensive equipment and large presence of people with different ages. Therefore, the present study aimed to assess the fire risk of commercial and shopping centers in Kashan using the fire risk assessment method for engineering (FRAME). This cross‐sectional study was conducted using FRAME in 15 commercial and shopping centers in Kashan, Iran. The risk assessment data and FRAME checklist were collected by observation and interviews. Data analysis was conducted using Excel and Geographic Information System (GIS) software. The results of 46 checklists showed that the mean score of fire risk R for property was equal to 3.12, for people 3.81 and for activities 1.86. Also, the lowest risk for the property, people and activities belongs to Golestan Center with a score of 1.40, Valiasr with a score of 1.25 and Ataee with a score of 1.15, and the highest risk for the property, people and activities belongs to Mir Seyfi Center with a score of 5.80, Shafagh with a score of 9.96 and Sabz was 2.62, respectively. The present study showed the lack of proper ventilation system, lack of emergency exits, and lack of automatic fire alarm and extinguishing system were the factors affecting fire risk. Therefore, in order to prevent disasters and uncontrollable critical conditions, it is necessary to review the equipment of these buildings and to design and implement fire detection and alarm equipment and different ways of fire control in these centers.

The Multiple smart infrastructures have reported fire incidents, requiring rapid detection, precise localization, and smart decision support for mitigating risks to lives and property. This paper proposes an advanced fire alarm and fire location tracking system based on smart IoT technology, Artificial Intelligence/Machine Learning (AI/ML) integration and 5G networks. The system detects environmental changes, such as increases in temperature and fluctuations in smoke, and gas concentration, using an extensive network of IoT environmental sensors. Ai/ML algorithms are applied to the model system to predict fires, detect anomalies, and reduce the incidence of false positives before fire events are detected. The system generates localized alerts and transmits real-time environmental data and fire event detection data to cloud servers and emergency responders using high-speed, and low latency, 5G networks. The fire location tracking system uses emergency response unit GPS coordinates and fire location tracking to reduce emergency response time. Experimental evaluations have shown improved detection accuracy, minimum response time, and sustainable real-time communication. The fire location tracking system is an innovative, intelligent, and cost-effective technology to ensure fire safety in smart buildings, industrial domains, and smart cities.

With the rapid growth of the economy, air pollution becomes increasingly serious and environment protection has attracted more attention. It is a fact that ships produce enormous air pollution emissions with high energy consumption and research has been constantly carried out on clean energy applications. LNG as an alternative clean marine fuel to run on ships is still at an initial stage. Different from traditional energy resources, LNG may generate risks in the process of application. Security alarm control system will effectively monitor risk sources preventing the occurrence of danger. Based on the deep analysis of the pros and cons of the existing structure and mode of security alarm control system of LNG-fueled vessels combined with the work and risk characteristics of marine engine, storage tanks and gas supply piping which have different danger sources, design a new type security alarm control system to optimize the structure design and logic control mode and implement functions of automatic detection, alarm and device control of combustible gas from risk sources. The system is stable and reliable with easy operation effectively reducing the risks of LNG-fueled ships.

Smart buildings are equipped with computer systems that monitor and control diverse services such as air conditioning, indoor transportation, physical access control, and many others. Critical infrastructures like hospitals, airports, and data centers, leverage on such services to support their daily operations. However, the current popularity of smart buildings is founded on a decades-long history. Smart building systems have evolved from isolated networks using proprietary protocols to IT-integrated systems that use standardized communication protocols. They might even be connected to the Internet to allow remote building management. This transition has exposed smart buildings to a whole new set of security threats. For instance, there have been documented cases where attackers have managed to remotely disrupt the environmental conditions and physical access control of smart buildings. Due to the crucial role that smart buildings play in supporting organizations and the serious threat of cyber attacks against them, there is a pressing need to investigate how to improve their current security posture.<br/>The transfer of mature IT security solutions to smart building systems seems a natural approach to enhance their security, however, the fundamental differences between both domains often require significant adaptation effort or to develop completely new solutions. For this reason, in recent years, a growing body knowledge about smart buildings security has been developed. However, most of these solutions have focused on intrusion detection and little efforts have been made to prevent cyber attacks. An effective way to prevent cyber attacks against smart buildings is by preemptively handling security weaknesses in customized applications and configurations that run the system. Unfortunately, this is often overlooked by smart building administrators due to, e.g., lack of specialized tools, staff, and training. We identify not only a research gap regarding this important task, but also an urgent need to provide (semi-) automated tools that help overcome the limitations faced by smart building administrators. The implementation of these tools requires sophisticated methods that incorporate technical and business-related insights to handle weaknesses according to the organization’s best interest.<br/>In this thesis, we investigate how to implement the first stages of a vulnerability management process for smart building applications and configurations. Beyond just vulnerabilities, we consider the weaknesses that give rise to vulnerabilities. In particular, our contributions address the identification and assessment of security weaknesses for later remediation. These are two key activities to preemptively strengthen the security of smart buildings. The identification of weaknesses is the basis of any vulnerability management process as it provides the first insights about the current security state of a system. This is a challenging task because a deep understanding of the system’s inner workings is often needed to obtain meaningful findings. We propose two approaches to identify security weaknesses; one focused on smart building applications and another on smart building configurations. In the first case, we model the application as a graph data structure comprised of sensors, setpoints, actuators, and control function nodes. The relationships among these components reveal the architecture of the system, which can then be analyzed in the search for security weaknesses. In the second case, we look for component misconfigurations that can be observed in their behavior, i.e., the way they interact with other components in the system. Leveraging official documentation from the components’ manufacturers, we create a model of valid behavior for each of them, which is then compared with their actual behavior as observed in the network traffic. After identifying security weaknesses, we assess the sensitivity of the affected components, which is an important factor to prioritize weaknesses for later remediation. We propose a comprehensive approach to assess the sensitivity of smart building components based on technical and business-related features. The proposed methods are evaluated in real smart buildings and additional experiments are performed in testbeds and comparable simulated environments. These evaluations confirm the feasibility and effectivity of our (semi-) automated weakness identification and assessment approaches.

&lt;p&gt;In recent years, there have been numerous forest fires, and fire identification technology has become increasingly influential in both academic and industrial fields. At present, most automatic fire alarm systems are limited to identification by sensors such as temperature, smoke, and infrared optics. One of the existing solutions is the method of image feature extraction, which does not need to rely on specific sensors and can be easily embedded in different devices. However, this method has the disadvantage that it is difficult to extract features from image data. To attack this issue, this paper proposes a lightweight convolutional neural network for forest fire recognition. Firstly, three-channel color images of three scenes are constructed as the input of the convolutional neural network, and the initial data are pre-processed and enhanced. Secondly, a deep convolutional neural network with multiple layers of convolution and pooling layers is constructed. Finally, the Softmax function is used to classify the fire recognition scenes. The experimental results show that our approach outperforms these selected techniques in the effectiveness and accuracy.&lt;/p&gt; &lt;p&gt;&amp;nbsp;&lt;/p&gt;

Fire can really be devastating to properties if improperly managed, it is due to this problem that the fire detection and alarm systems were sought for. However, traditional fire alarm system is based on a wiring network which have drawbacks and limitations such as inflexibility of the FDAS layout plan during building construction, and difficulties in renovation where the removal and relocation of traditional FDAS requires additional amount of work. To address these problems, a fire detection and alarm system that is based on wireless sensor network was developed. The FDAS is mainly composed of a fire detection node, a fire alarm node, and a fire alarm control panel. The wireless communication of the nodes was achieved using XBee as the wireless transceiver. The significant characteristic of XBee is the mesh routing protocol which helps the system to be more robust and flexible. The fire alarm control panel is a LabVIEW based program that utilizes the state machine architecture which follows the detect-evaluate-store algorithm. In evaluating the overall system, results illustrate the network of nodes adapts to its location and connects to other nodes whenever it is within their range. Furthermore, the average response time of each detection node with respect to the fire alarm control panel is below the standard of 10-second as stated by the National Fire Alarm and Signaling Code.

Aim: The aim of this paper is to present the construction and principle of operation of condensed aerosol generators, as well as a review of their selected characteristics, confirmed in the process of assessment and verification of constancy of performance. The paper describes selected laboratory tests, including those specific to Group A, B and C fires. Introduction: Fixed firefighting systems, in addition to detection systems (fire alarm system) and alarm systems (voice evacuation systems), are one of the pillars of the safety of today's erected, increasingly complex buildings. However, unlike these detection and alarm systems, fire extinguishing systems based on condensed aerosol generators focus on providing an adequate level of protection for property, as they are dedicated to spaces that are not normally occupied. For this reason, emphasis is placed on the reliability of the generators, whose only task is to trigger appropriately at a specific time and fill the protected area with aerosol. Methodology: The theoretical research, such as analysis of literature and legal documents, synthesis, generalisation, inference, comparison and analogy, was used in the development of the paper. A review of selected characteristics validated in the process of assessment and verification of constancy of performance of the analysed products was carried out. Research processes relating to selected parameters of the generators and inherent in the conformity assessment of construction products are presented. Conclusions: It should be noted that, irrespective of their main purpose, condensed aerosol generators, which are a key component of aerosol fire extinguishing kits, can be crucial not only with regard to the safety of the buildings themselves, but also of their users, influencing the containment of a fire in the extinguishing zone where they are installed. Also, important is the awareness of owners and managers of building structures equipped with condensed aerosol generators. Their particular attention should be directed to the specifics of the generator itself and their knowledge of its operating principles. In the next stages of the work, it will be crucial to define the basics related to the connection of the generators to the installation forming a fixed firefighting system, to identify and describe issues related to design, installation and maintenance, and to identify the risks related to the potential exposure of the users of built structures to the extinguishing aerosol.