Development in building fire detection and evacuation system-a comprehensive review

Fire is both beneficial to man and his environment as well as destructive and deadly among all the natural disasters. A fire Accident occurs very rarely, but once it crops up its consequences will be devastating. The early detection of fire will help to avoid further consequences and saves the life of people. During the fire accidents, it is also important to guide people within the building to exit safely. Because of this, the paper gives a review of literature related to recent advancements in building fire detection and emergency evacuation system. It is intended to provide details about fire simulation tools with features, suitable hardware, communication methods, and effective user interface

SEN-Iot: A Smart Emergency Notification System Suitable for Developing Countries using Internet of Things

Research has shown that disaster effects on properties and lives can be drastically reduced through wide dissemination of information on the impending danger to people at the appropriate time. Generally, the emergency alert systems are usually proactive systems; they are meant to gather data in surrounding using the necessary tools, alert the specified listeners about an impending danger and gives suggestion on the necessary actions to be taken in each situation. In addition, some emergency alert systems also activate automatic responses. Furthermore, the integration of Internet of things (IoT) technology with emergency notification systems is rapidly attracting new discovery in this domain. In this paper, an effective smart emergency notification system named SEN-IoT was design using IOT technology. SEN-IoT was modeled to manage domestic hazard with a scope of water, fire and gas leaks; by creating an emergence notification and immediate response systems. The SEN- IOT was implemented using arduino, sensors and the GSM module. The system was tested for maintainability, functionality, efficiency, usability and reliability, and results revealed that SEN-IoT can effectively handle domestic hazard

Design and Implementation of Real-Time Kitchen Monitoring and Automation System Based on Internet of Things

Automation can now be found in nearly every industry. However, home automation has yet to reach Pakistan. This paper presents an Internet of Things smart kitchen project that includes automation and monitoring. In this project, a system was developed that automatically detects the kitchen temperature. It also monitors the humidity level in the kitchen. This system includes built-in gas detection sensors that detect any gas leaks in the kitchen and notify the user if the gas pressure in the kitchen exceeds a certain level. This system also allows the user to remotely control appliances such as freezers, ovens, and air conditioners using a mobile phone. The user can control gas levels using their phone with this system. In this paper, the ESP32, DHT11 Sensor, 5 V Relay X 8, and MQ-135 gas sensors create a smart kitchen by controlling the temperature, managing humidity, and detecting gas leakage. The system was built on an Arduino board that is connected to the Internet. The hardware was integrated and programmed using an Arduino, and a user Android application was developed. The project’s goal is to allow any Android smartphone to remotely control devices. This method is commonly used in homes, businesses, and grocery stores. Users will be able to control all of their instruments from anywhere, including switches, fans, and lights. Furthermore, simulation was performed using Matlab2016b on multiple houses. In the simulation, not only was the kitchen considered, but also two, four, and six houses. Each house has two bedrooms, one living room, one guest room, two bathrooms, and one kitchen. The results revealed that using this system will have a scientifically significant impact on electricity consumption and cost. In the case of the houses, the cost was USD 33.32, 32.64, 22.32, and 19.54 for unscheduled, two, four, and six houses, respectively. Thus, it was observed that the cost and power are directly proportional to each other. The results reveal that the proposed solution efficiently reduces the cost as compared to that of unscheduled houses.publishedVersio

Named data networking for efficient IoT-based disaster management in a smart campus

Disasters are uncertain occasions that can impose a drastic impact on human life and building infrastructures. Information and Communication Technology (ICT) plays a vital role in coping with such situations by enabling and integrating multiple technological resources to develop Disaster Management Systems (DMSs). In this context, a majority of the existing DMSs use networking architectures based upon the Internet Protocol (IP) focusing on location-dependent communications. However, IP-based communications face the limitations of inefficient bandwidth utilization, high processing, data security, and excessive memory intake. To address these issues, Named Data Networking (NDN) has emerged as a promising communication paradigm, which is based on the Information-Centric Networking (ICN) architecture. An NDN is among the self-organizing communication networks that reduces the complexity of networking systems in addition to provide content security. Given this, many NDN-based DMSs have been proposed. The problem with the existing NDN-based DMS is that they use a PULL-based mechanism that ultimately results in higher delay and more energy consumption. In order to cater for time-critical scenarios, emergence-driven network engineering communication and computation models are required. In this paper, a novel DMS is proposed, i.e., Named Data Networking Disaster Management (NDN-DM), where a producer forwards a fire alert message to neighbouring consumers. This makes the nodes converge according to the disaster situation in a more efficient and secure way. Furthermore, we consider a fire scenario in a university campus and mobile nodes in the campus collaborate with each other to manage the fire situation. The proposed framework has been mathematically modeled and formally proved using timed automata-based transition systems and a real-time model checker, respectively. Additionally, the evaluation of the proposed NDM-DM has been performed using NS2. The results prove that the proposed scheme has reduced the end-to-end delay up from 2% to 10% and minimized up to 20% energy consumption, as energy improved from 3% to 20% compared with a state-of-the-art NDN-based DMS

A smart fire detection system using iot technology with automatic water sprinkler

House combustion is one of the main concerns for builders, designers, and property residents. Singular sensors were used for a long time in the event of detection of a fire, but these sensors can not measure the amount of fire to alert the emergency response units. To address this problem, this study aims to implement a smart fire detection system that would not only detect the fire using integrated sensors but also alert property owners, emergency services, and local police stations to protect lives and valuable assets simultaneously. The proposed model in this paper employs different integrated detectors, such as heat, smoke, and flame. The signals from those detectors go through the system algorithm to check the fire's potentiality and then broadcast the predicted result to various parties using GSM modem associated with the system. To get real-life data without putting human lives in danger, an IoT technology has been implemented to provide the fire department with the necessary data. Finally, the main feature of the proposed system is to minimize false alarms, which, in turn, makes this system more reliable. The experimental results showed the superiority of our model in terms of affordability, effectiveness, and responsiveness as the system uses the Ubidots platform, which makes the data exchange faster and reliable

THE INTERNET OF THINGS (IOT) IN DISASTER RESPONSE

Disaster management is a complex practice that relies on access to and the usability of critical information to develop strategies for effective decision-making. The emergence of wearable internet of things (IoT) technology has attracted the interests of several major industries, making it one of the fastest-growing technologies to date. This thesis asks, How can disaster management incorporate wearable IoT technology in operations and decision-making practices in disaster response? How IoT is applied in other prominent industries, including construction, manufacturing and distribution, the Department of Defense, and public safety, provides a basis for furthering its application to challenges affecting agency coordination. The critical needs of disaster intelligence in the context of hurricanes, structural collapses, and wildfires are scrutinized to identify gaps that wearable technology could address in terms of information-sharing in multi-agency coordination and the decision-making practices that routinely occur in disaster response. Last, the specifics of wearable technology from the perspective of the private consumer and commercial industry illustrate its potential to improve disaster response but also acknowledge certain limitations including technical capabilities and information privacy and security.Civilian, Virginia Beach Fire Department / FEMA - USAR VATF-2Approved for public release. Distribution is unlimited

Smart Home Systems Based on Internet of Things

Smart home systems achieved great popularity in the last decades as they increase the comfort and quality of life. Most smart home systems are controlled by smartphones and microcontrollers. A smartphone application is used to control and monitor home functions using wireless communication techniques. We explore the concept of smart home with the integration of IoT services and cloud computing to it, by embedding intelligence into sensors and actuators, networking of smart things using the corresponding technology, facilitating interactions with smart things using cloud computing for easy access in different locations, increasing computation power, storage space and improving data exchange efficiency. In this chapter we present a composition of three components to build a robust approach of an advanced smart home concept and implementation