Multi-Sensor System for Land and Forest Fire Detection Application in Peatland Area

Forest fire has a dangerous impact on environments and humans because of haze and carbon emitted from it. A common technology to detect fire hotspots is to use satellite images and then process them to determine the number of hotspots and their location. However, satellite systems cannot penetrate in bad weather or cloudy condition. This research proposes a ground sensor system, which uses several sensors related to the indicators of fire, especially fire in peatland area with unique characteristics. Common parameters of fire, such as temperature, smoke, haze, and carbon dioxide, are applied in this system. Indicators are measured using special sensors. Results of every sensor are analyzed by implementing intelligent computer programming, and an algorithm to determine fire hotspots and locations is applied. The fire hotspot location and intensity determined by integrated multiple sensors are more accurate than those determined by a single sensor. Data collected from every sensor are kept in a database, and a graph is generated for reporting and recording. In case of sensor readings with parameters, potential of fire and hotspots detected can be forwarded to the representative department for corresponding actions

Design and Built a Prototype Kit for Fire Detection in a Peat Swamp Forest: A Preliminary Results

Peat forest fire detectors need to be developed immediately due to the frequency of peat forest fires in Malaysia during the summer is very high which can affect the life in the forest and the health of the surrounding population. Among them is the Ayer Hitam Muar Forest Reserve, Johor which is almost 50,000 acres in size and experiences fires every year. However, fire monitoring management methods still need to be improved in terms of speed, accuracy and systematic in channelling fire alerts. Apart from location and area factors, the main challenge of the early fire detection process is the lack of manpower for the purpose of monitoring and notification of fires. The conventional method through patrols and phone calls from farmers who see a fire is less effective because of the delay in notification received by the authorities. Initially, the work of identifying the location of the fire and measuring the signal strength of the telco service in the Forest Reserve was done with the help of rangers from the Muar district forestry department. This article proposes a propotype for detecting peat forest fires that is capable of monitoring and sending early fire notifications using a smartphone. The prototype uses an ESP32 microcontroller, GSM/GPRS modem and industry-standard sensors which include smoke, temperature, humidity and motion detectors. A total of five prototype units were developed as sensor nodes (SN) 1 to 5 with unique IDs that can send information to UTHM web servers simultaneously. Data from each SN is displayed in real time while notifications of smoke detection and motion alerts are sent to the authorities via Telegram application. Solar panels are used as a source of electricity supply while the authorities can access information via smartphones. This prototype was tested to see its stability and operational accuracy while the data obtained were recorded. The developed system can help the authorities detect fires at an early stage and the location of the fire can be known based on the SN information received on the smartphone screen

Fireground location understanding by semantic linking of visual objects and building information models

This paper presents an outline for improved localization and situational awareness in fire emergency situations based on semantic technology and computer vision techniques. The novelty of our methodology lies in the semantic linking of video object recognition results from visual and thermal cameras with Building Information Models (BIM). The current limitations and possibilities of certain building information streams in the context of fire safety or fire incident management are addressed in this paper. Furthermore, our data management tools match higher-level semantic metadata descriptors of BIM and deep-learning based visual object recognition and classification networks. Based on these matches, estimations can be generated of camera, objects and event positions in the BIM model, transforming it from a static source of information into a rich, dynamic data provider. Previous work has already investigated the possibilities to link BIM and low-cost point sensors for fireground understanding, but these approaches did not take into account the benefits of video analysis and recent developments in semantics and feature learning research. Finally, the strengths of the proposed approach compared to the state-of-the-art is its (semi -)automatic workflow, generic and modular setup and multi-modal strategy, which allows to automatically create situational awareness, to improve localization and to facilitate the overall fire understanding

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

Internet of things for disaster management: state-of-the-art and prospects

Disastrous events are cordially involved with the momentum of nature. As such mishaps have been showing off own mastery, situations have gone beyond the control of human resistive mechanisms far ago. Fortunately, several technologies are in service to gain affirmative knowledge and analysis of a disaster's occurrence. Recently, Internet of Things (IoT) paradigm has opened a promising door toward catering of multitude problems related to agriculture, industry, security, and medicine due to its attractive features, such as heterogeneity, interoperability, light-weight, and flexibility. This paper surveys existing approaches to encounter the relevant issues with disasters, such as early warning, notification, data analytics, knowledge aggregation, remote monitoring, real-time analytics, and victim localization. Simultaneous interventions with IoT are also given utmost importance while presenting these facts. A comprehensive discussion on the state-of-the-art scenarios to handle disastrous events is presented. Furthermore, IoT-supported protocols and market-ready deployable products are summarized to address these issues. Finally, this survey highlights open challenges and research trends in IoT-enabled disaster management systems. © 2013 IEEE

University of Southern California Heritage Hall- Fire Protection and Life Safety Analysis

This fire protection and life safety analysis is submitted in partial fulfillment of the requirements for the Master of Science Degree from California Polytechnic State University, San Luis Obispo. The study was performed on the University of Southern California’s Heritage Hall, which includes both a code-determined prescriptive examination and a performance-based analysis. The purpose of this review is to evaluate the Heritage Hall address based on compliance with all applicable codes and standards, as well as the determined occupant tenability criteria. The prescriptive examination of Heritage Hall consisted of the evaluation of all structural fire protection, egress analysis and design, water-based fire suppression, and fire alarm systems. This analysis was primarily performed by utilizing the 2013 edition of California Building Code and the 2013 editions of all applicable NFPA codes and standards. The structural fire protection overview provided an in-depth prescriptive analysis of the conversions made for Heritage Hall during the 2012 renovation project. The latest recapitalization expanded the lower level and added more spaces for student athletes, thus converting those locations to the A-3 occupancy classification. Per CBC Table 601, non-bearing walls and partitions were not required to be fire-rated. The structural update complied with all updated building codes due to a water curtain installed per Section 404.6 of the CBC, which allowed the center museum’s atrium not to be separated by a 1-hour fire barrier. Instead, both glass walls surrounding the atrium were used to create smoke partitions to meet standards. The egress analysis and design was utilized to determine new occupant loads for each floor, remove the B-2 occupancy classification, the creation of a new area of refuge. Per CBC Table 1018.1, corridor walls and ceilings were not required to be fire resistance rated due to the building being fully sprinklered. Only the area of refuge at the lower level was provided with a 1-hour fire rated separation, and existing 1-hour separations, such as the lower level’s exit access corridor, remained intact. Using the Life Safety Code, a building evacuation analysis was performed at Heritage Hall’s lower level. The average evacuation time of all lower level occupants was determined to be 5.43 minutes, with a range of 2.74-8.13 minutes depending on whether occupants used the exit corridor or the stairways. All egress components and occupancy classification were deemed acceptable. The water-based suppression analysis was performed by primarily using NFPA 13 and NFPA 25 codes and standards. A complete analysis of the building’s risers, sprinklers, and system demand calculations provided acceptable criteria for the water-based fire protection system installed. The outside overhang was chosen not to have sprinklers installed due to the large amount of remaining asbestos at the interstitial level near the ceiling. The overhang is made of concrete and directly exposed to the outside. The building’s fire alarm system was installed in 2012, with all new fire detection devices, notification appliances, fire alarm control panel, and a mass notification system. The fire alarm system design was analyzed using NFPA 72, with all spacing and location requirements deemed acceptable for the devices installed. All spot-type smoke and heat detectors are ceiling-mounted in accordance with the open ceiling plan at the lower level, which contains both ceiling and wall-mounted sprinklers. The performance-based analysis was performed using Fire Dynamics Simulator (FDS), a fire modeling program provided by NIST, and the SFPE Handbook of Fire Protection Engineering. Two unique design fire performance scenarios were established for Heritage Hall: a workstation fire in the first floor atrium and a stacked-chairs fire near the lower level exit corridor that prevents its use. In order to establish a basis for analysis and comparison, various tenability criteria were determined for the building’s occupants. The performance criteria consisted of visibility, toxicity, and tenability requirements for the facility, which were compared with modeling simulations created using FDS. The simulations allowed for the determination of the available safe egress time (ASET). Occupant behavior and characteristics were paired with Thunderhead Engineering’s Pathfinder program to provide a required set egress time (RSET) for each fire scenario. While the lower level corridor fire scenario met all tenability requirements, the atrium’s fire scenario simulation did not provide an acceptable ASET, and therefore did not pass the critical occupant visibility requirements for safe evacuation. Recommendations were provided to establish a legitimate smoke barrier per CBC Section 404.6, or an appropriate door separation for each side entrance to the atrium per CBC Section 715.1

Design and Implementation of an Intelligent Safety and Security System for Vehicles Based on GSM Communication and IoT Network for Real-Time Tracking

In recent years, the surge in car theft cases, often linked to illicit activities, has become a growing concern. Simultaneously, countries grappling with oil shortages have shifted towards converting vehicles to run on liquid propane gas, presenting new safety challenges for car owners. This paper introduces a novel integrated intelligent system designed to address the challenges of car theft and safety concerns associated with gas-based vehicles. By seamlessly integrating these concerns into a single system, it aims to achieve significantly improved performance compared to traditional alarm systems. The proposed system consists of three primary parts: the car security subsystem, an Internet of Things (IoT)-based real-time car tracking subsystem, and the car safety subsystem. Utilizing key technologies such as the Arduino Microcontroller, Bluetooth module, vibration sensor, keypad, solenoid lock, GSM module, NodeMCU microcontroller, GPS module, MQ-4 gas sensor, flame sensor, temperature sensor, and Bluetooth module, the system aims to provide a comprehensive solution for the mentioned issues. Furthermore, the vibration sensor plays a crucial role in identifying unauthorized vehicle operations. Its significance lies in detecting the vibrations emanating from the running engine. Concurrently, other modules and sensors are utilized for real-time tracking and enhancing vehicle safety. These measures include safeguarding against incidents like fire outbreaks or gas leaks within the gas container. Finally, after assembling the system, a practical test was conducted, yielding favourable performance results. This paper describes a meaningful step towards improving the protection and safety for the cars, simultaneously addressing the stealing prevention and gas-related accident alleviation

Autonomous environmental protection drone

During the summer, forest fires are the main reason for deforestation and the damage caused to homes and property in different communities around the world. The use of Unmanned Aerial Vehicles (UAVs, and also known as drones) applications has increased in recent years, making them an excellent solution for difficult tasks such as wildlife conservation and forest fire prevention. A forest fire detection system can be an answer to these tasks. Using a visual camera and a Convolutional Neural Network (CNN) for image processing with an UAV can result in an efficient fire detection system. However, in order to be able to have a fully autonomous system, without human intervention, for 24-hour fire observation and detection in a given geographical area, it requires a platform and automatic recharging procedures. This dissertation combines the use of technologies such as CNNs, Real Time Kinematics (RTK) and Wireless Power Transfer (WPT) with an on-board computer and software, resulting in a fully automated system to make forest surveillance more efficient and, in doing so, reallocating human resources to other locations where they are most needed.Durante o verão, os incêndios florestais constituem a principal razão do desflorestamento e dos danos causados às casas e aos bens das diferentes comunidades de todo o mundo. A utilização de veículos aéreos não tripulados (VANTs), em inglês denominados por Unmanned Aerial Vehicles (UAVs) ou Drones, aumentou nos últimos anos, tornando-os uma excelente solução para tarefas difíceis como a conservação da vida selvagem e prevenção de incêndios florestais. Um sistema de deteção de incêndio florestal pode ser uma resposta para essas tarefas. Com a utilização de uma câmara visual e uma Rede Neuronal Convolucional (RNC) para processamento de imagem com um UAV pode resultar num eficiente sistema de deteção de incêndio. No entanto, para que seja possível ter um sistema completamente autónomo, sem intervenção humana, para observação e deteção de incêndios durante 24 horas, numa dada área geográfica, requer uma plataforma e procedimentos de recarga automática. Esta dissertação reúne o uso de tecnologias como RNCs, posicionamento cinemático em tempo real (RTK) e transferência de energia sem fios (WPT) com um computador e software de bordo, resultando num sistema totalmente automatizado para tornar a vigilância florestal mais eficiente e, ao fazê-lo, realocando recursos humanos para outros locais, onde estes são mais necessários