Selected Issues of Reliability and Availability in Marine Vessel Fire Alarm Systems

An automatic fire detection and alarm system based on Multi-modal information recognition technology is designed. The whole structure of the distributed fire alarm system is introduced in detail. The automatic fire detection and alarm net is established with the smoke-sensor detectors, blaze-sensor detectors, temperature-sensor detectors and manual alarm buttons. The signal is processed through the fuzzy control. The gang control system is made up of fire-proof rolling door, smoke-released fans, broadcasting system and water spray fire fighting system. The Multi-modal information recognition technology can extend the monitoring range of fire alarm system in time domain and space domain. And it also can raise the Sensitivity and reliability of the whole system.

In this thesis, the research are implemented to build a complete radio directional finding (RDF) and fire alarm systems. These architecture of Radio Directional Finding and fire alarm systems were composed of PIC18LF4520 microcontroller and RF transceiver module. The RFIC(CC1101) embedded in the RF transceiver module is equipped with the ability to dynamically update the content of the internal build received signal strength indicator(RSSI). This dissertation is divided into two sections. First section is Radio Directional Finding system bring about two phases. The first phase is the data communications are properly set through the 4-wire serial peripheral interfaces(SPI) through the PIC18LF4520 microcontrollers with 433MHz RF transceiver modules to complete wireless transmission ; in the second phase, the radio directional finding (RDF) system is integration of PIC18LF4520 microcontroller, RF transceiver modules and antenna make the system with integrity. The research conducted in this thesis integrated not only hardware but also firmware. This system uses the C language constructs program and microstrip antenna to replace the original omnidirectional antenna at the receiver. Finally, we determine the transmitter location through RF transceiver modules of the received signal strength indicator(RSSI) characteristics. The second section is fire alarm system. Digital thermometer installed in the transmitter. When the thermometer sensed data threshold is reached. The alarm system will be activated immediately. This system is intended to notify the building occupants to evacuate in the event of a fire.

Background: The hospital has a risk of fire. The availability of adequate fire protection systems as well as compliance with the standards is one of the effective prevention way to avoid and minimize the occurrence of fires and prevent casualties. Then with that probability of the risk, how the hospital addressing it. The objective of this study was to analyze the risk of fire in terms of active fire protection systems in Panembahan Senopati hospital. Method: This study was a qualitative descriptive with case study design through field observation, interviews and review of documents, then do a risk assessment of the probability ( likelihood ) and severity using a risk matrix model according to the AS/NZS 4360: 2004 guidelines . Results: 15 elements of fire alarm and detection systems were studied, there were 13 elements (80%) that appropriate and 2 elements (20%) were not. Then all of 7 elements of automatic sprinkler systems, there was no element (0%) that appropriate or all of elements (100%) were not. For 15 elements of APAR category there were 14 elements (93.33%) that appropriate and only 1 element (6.67%) was not. For 30 elements of standpipe system and fire hose box, there was no element (0%) that appropriate and all of elements (100%) were not. Then for 12 Fire Safety Management there were 11 elements (91.67%) that appropriate and only 1 element (8.33%) was not. Conclusion: For all of elements that were studied, there were 38 elements (48.10%) that appropriate and 41 (51.90%) were not appropriate to the application standard of the active fire protection systems. The risk level of fire spreading based on the appropriate of active fire protection system was classified as Moderate Risk category.

Fire alarm systems have become increasingly an important lifesaving technology in many aspects, such as applications to detect, monitor and control any fire hazard. A large sum of money is being spent annually to install and maintain the fire alarm systems in buildings to protect property and lives from the unexpected spread of fire. Several methods are already developed and it is improving on a daily basis to reduce the cost as well as increase quality. An integrated Fire Detection and Alarm (FDA) systems with building automation was studied, to reduce cost and improve their reliability by preventing false alarm. This work proposes an improved framework for FDA system to ensure a robust intelligent network of FDA control panels in real-time. A shortest path algorithmic was chosen for series of buildings connected by fiber optic network. The framework shares information and communicates with each fire alarm panels connected in peer to peer configuration and declare the network state using network address declaration from any building connected in network. The fiber-optic connection was proposed to reduce signal noises, thus increasing large area coverage, real-time communication and long-term safety. Based on this proposed method an experimental setup was designed and a prototype system was developed to validate the performance in practice. Also, the distributed network system was proposed to connect with an optional remote monitoring terminal panel to validate proposed network performance and ensure fire survivability where the information is sequentially transmitted. The proposed FDA system is different from traditional fire alarm and detection system in terms of topology as it manages group of buildings in an optimal and efficient manner.Introduction

This paper outlines the design with Arduino based device by means of IoT of a home fire alarm. The project is intended for the protection of the home and business, where the main aim is to prevent fire incidents that have happened to people, businesses and property inside the city. It utilizes board Arduino Uno with chip ATmega328. The key controller used is definitely the ATmega328 which controls the fire alarm that is subjected to the temperature sensor at home and in industry. An LM35 temperature sensor is used to detect the heat from the burn. The machine must start fire suppression system, such as opening fire extinguishing valves for water. The device can also submit information over the network through IoT at the same time. This device will also alert the fire location administrator using the IoT system. Here we use Thing Speaks as an IOT platform. Two types of sensors would be used, such as temperature sensor, smoke sensor, for instance, by providing immediate reaction to accident prevention. It will also encourage users to also protect their lives and properties from the disaster. Keywords: Temperature sensor(LM35), Smoke sensor, IoT, OpenMP, Arduino Uno, Wi-Fi(ESP8266) Cite this Article Digambar. A. Jakkan, K.D. Patil. Fire Alarm and Monitoring System Using IoT. Recent Trends in Electronics & Communication Systems . 2020; 7(1): 10–20p.

Internet of Things (IoT) is an emerging technology that can be used to design smart systems without incurring lots of money. Although, the legislation forces to install an analog fire alarm system to every household in modern era, the system is not smart enough to send immediate notifications to the concerned individual. The analog fire alarm cannot avoid the immediate risk or damage of fire as no one stays at home all the time. The earlier the incident is reported to the concerned individual the better to reduce the fire damage. In this paper, we have proposed a smart fire-alarm system that consists of a smoke sensor and a sound sensor that can detect the smoke and the noise of the analog fire alarm system (with a view to detect whether the analog fire alarm system is working) respectively, and can notify the user about the status immediately. We have implemented the proposed smart fire-alarm system and conducted experiments to determine the effectiveness of the system. The results show that the system is reliable under various conditions of smoke and alarm noises.

Chapter 9 - Fire Alarm and Mass Notification Systems

This work introduces a fire Management system to track different kinds of fire attacks across industries. While traditional research mostly focuses on creating fire sensing. Fire alarm systems are only useful if they can reliably and quickly send out fire alerts that include the where abouts of the flames the quantity of fire damage and the length of time it takes to respond to different fire alarm systems are directly correlated. The interior environments of public buildings can be complicated and diverse, which makes it important to consider how to safeguard people in the event of a fire and get them to a safe place as fast as possible. Fire extinguishers, fire hydrants,, fire sprinklers, safety exit signals, smoke, fire pumps fire doors and temperature are just a few examples of the types of firefighting equipment that may be dynamically tracked and controlled using the Internet of Things. Recently, a few life-safety systems that integrate a smoke sensor and an alarm device have been created for fire warning and alarm systems. However, these fire alarm systems can make mistakes and respond to erroneous signals that aren’t actually fire signs. High-end, sophisticated fire alarm systems are necessary, and they must use a range of sensor values to identify actual fires, including a signal from smoke detector, heat sensor, and a flame detector.

This work introduces a fire Management system to track different kinds of fire attacks across industries. While traditional research mostly focuses on creating fire sensing. Fire alarm systems are only useful if they can reliably and quickly send out fire alerts that include the whereabouts of the flames the quantity of fire damage Considering the time it takes for various fire alarm systems to respond directly correlated. The interior environments of public buildings can be complicated and diverse, which makes it important to consider how to safeguard people in the event of a fire and get them to a safe place as fast as possible. Fire faucets, fire pumps, hose reels, smoke alarms, safety exit signs, temperature gauges, and fire doors are just a few examples of the types of firefighting equipment that may be dynamically tracked and controlled using the Internet of Things. Recently, a few life-safety systems that integrate a smoke sensor and an alarm device have been created for fire warning and alarm systems. However, these fire alarm systems can make mistakes and respond to erroneous signals that aren’t actually fire signs. High-end, sophisticated fire alarm systems are necessary, and they must use a range of sensor values to identify actual fires, including a signal from smoke, heat, humidity, and flame sensors.

Chapter 8 - Central Alarm Stations and Dispatch Operations

The article presents basic issues regarding the operation process and analysis of the reliability of the fire alarm and transmission system in the distributed fire alarm system. Signals of fire and fault alarms generated from the fire alarm system (SSP) send fire monitoring. Fire monitoring consists of sending, with the confirmation, an automatic fire alarm and a fault signal to the appropriate alarm receiving centers (ACO). The reliability structure of the fire and fault alarm transmission system is presented. An analysis of reliability of independent SSP system information transmission paths was performed.

Aiming at the problems of low fire detection accuracy and high false alarm rate of the current intelligent camera fire accident alarm system, a fire accident alarm system based on fuzzy recognition algorithm is designed. By analyzing the structural principle of the fire detection and alarm system, selecting the CO gas, temperature and smoke sensor selection, designing the corresponding fire signal detection circuit, and designing the single-chip system circuit, including the single-chip clock circuit, reset circuit, power supply circuit and A/D conversion circuit design, on the basis of in-depth study of the Bluetooth communication protocol structure, the hardware design of the serial interface circuit of the single-chip microcomputer, PC and Bluetooth module has been completed. The fuzzy recognition algorithm is used to set the input and output, establish the control rule table and reasoning relationship, generate the input and output rule table, preprocess the sensor signal, and finally output the fire alarm model through the fuzzy inference system, so as to realize the fire accident alarm of the intelligent camera. The experimental results show that the fire detection accuracy of the proposed method is high, and can effectively reduce the false alarm rate and false alarm rate of the system.

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.

The objective of the paper is to study, analyze and design a fire detection and extinguisher system. This topic was acceptable because it covered a basic and important aspect in our modern life. The author has gained the valuable experience in the field of fire detection and alarm system from studying and conducting the project. The objectives of the project were to provide information on fire alarm system and the extinguishing techniques used in India and around the globe, to show the differences and similarity between the systems and the lack in existing systems used for fire detection. Secondly, in the practical part, the objective was to build a demo system to demonstrate how a basic fire alarm system works and the improvements can be added to it to make better systems to detect and extinguish fire in order to reduce the casualties and loss of capital. To achieve the purpose of this thesis, the author studied the main standards on fire detection and alarm systems in India and around the world. For the practical part, NodeMCU-ESP32 and Blynk Application are used as the control unit with other necessary components. Keywords Node MCU-ESP32, Blynk Application, Fire Detection, Fire Alarm System

To build an early fire alarm system, an important approach to detect whether a fire occurs is monitoring the fire characteristics parameters. Multi-sensor data fusion is the key technology to process the data collected by the sensors. In this paper, we present a data fusion method to process the data collected by distributed fire detectors. The method is based on rough sets and evidence theory. We explain the method and use an example to demonstrate its decision process under the Chinese standard on raked fire SH4 and smoldering fire SH1. The results prove that the method is fault-tolerant and stable.