Performance of a Protected Wireless Sensor Network in a Fire. Analysis of Fire Spread and Data Transmission

The paper deals with a Wireless Sensor Network (WSN) as a reliable solution for capturing the kinematics of a fire front spreading over a fuel bed. To provide reliable information in fire studies and support fire fighting strategies, a Wireless Sensor Network must be able to perform three sequential actions: 1) sensing thermal data in the open as the gas temperature; 2) detecting a fire i.e., the spatial position of a flame; 3) tracking the fire spread during its spatial and temporal evolution. One of the great challenges in performing fire front tracking with a WSN is to avoid the destruction of motes by the fire. This paper therefore shows the performance of Wireless Sensor Network when the motes are protected with a thermal insulation dedicated to track a fire spreading across vegetative fuels on a field scale. The resulting experimental WSN is then used in series of wildfire experiments performed in the open in vegetation areas ranging in size from 50 to 1,000 m2

Modelling of wireless sensor networks for detection land and forest fire hotspot

Indonesia located in South East Asia countries with tropical region, forest fires in Indonesia is one of big issue and disaster because it happens in almost of every year, this is because of some of region consist of peat land that high risk for fire especially in dry season. Riau Province is one of region that regularly incident of forest fire with affected the length and breadth of Indonesia. Propose development of Wireless Sensor Networks (WSNs) for detection of land and forest fire hotspot in Indonesia as well as one of the main consents in this research, case location in Riau province is at one of the regions that high risk forest fire in dry season. WSNs technology used for ground sensor system to collect environmental data. Data training for fire hotspot detection is done in data center to determine and conclude of fire hotspot then potential to become big fire. The deployment of sensors located at several locations that has potential for fire incident, especially as data shown in previous case and forecast location with potential fire happen. Mathematical analysis is used in this case for modelling number of sensors required to deploy and the size of forest area. The design and development of WSNs give high impact and feasibility to overcome current issues of forest fire and fire hotspot detection in Indonesia. The development of this system used WSNs highly applicable for early warning and alert system for fire hotspot detection

A Wireless Sensor Network Deployment for Rural and Forest Fire Detection and Verification

Forest and rural fires are one of the main causes of environmental degradation in Mediterranean countries. Existing fire detection systems only focus on detection, but not on the verification of the fire. However, almost all of them are just simulations, and very few implementations can be found. Besides, the systems in the literature lack scalability. In this paper we show all the steps followed to perform the design, research and development of a wireless multisensor network which mixes sensors with IP cameras in a wireless network in order to detect and verify fire in rural and forest areas of Spain. We have studied how many cameras, sensors and access points are needed to cover a rural or forest area, and the scalability of the system. We have developed a multisensor and when it detects a fire, it sends a sensor alarm through the wireless network to a central server. The central server selects the closest wireless cameras to the multisensor, based on a software application, which are rotated to the sensor that raised the alarm, and sends them a message in order to receive real-time images from the zone. The camera lets the fire fighters corroborate the existence of a fire and avoid false alarms. In this paper, we show the test performance given by a test bench formed by four wireless IP cameras in several situations and the energy consumed when they are transmitting. Moreover, we study the energy consumed by each device when the system is set up. The wireless sensor network could be connected to Internet through a gateway and the images of the cameras could be seen from any part of the world

A robot swarm assisting a human fire-fighter

Emergencies in industrial warehouses are a major concern for fire-fighters. The large dimensions, together with the development of dense smoke that drastically reduces visibility, represent major challenges. The GUARDIANS robot swarm is designed to assist fire-fighters in searching a large warehouse. In this paper we discuss the technology developed for a swarm of robots assisting fire-fighters. We explain the swarming algorithms that provide the functionality by which the robots react to and follow humans while no communication is required. Next we discuss the wireless communication system, which is a so-called mobile ad-hoc network. The communication network provides also the means to locate the robots and humans. Thus, the robot swarm is able to provide guidance information to the humans. Together with the fire-fighters we explored how the robot swarm should feed information back to the human fire-fighter. We have designed and experimented with interfaces for presenting swarm-based information to human beings

Wireless Sensor Networks for Fire Detection and Control

Due to current technological progress, the manufacturing of tiny and low price sensors became technically and economically feasible. Sensors can measure physical surroundings related to the environment and convert them into an electric signal. A huge quantity of these disposable sensors is networked to detect and monitor fire. This paper provides an analysis of utilisation of wireless sensor networks for fire detection and control

IoT-inspired Framework for Real-time Prediction of Forest Fire

Wildfires are one of the most devastating catastrophes and can inflict tremendous losses to life and nature. Moreover, the loss of civilization is incomprehensible, potentially extending suddenly over vast land sectors. Global warming has contributed to increased forest fires, but it needs immediate attention from the organizations involved. This analysis aims to forecast forest fires to reduce losses and take decisive measures in the direction of protection. Specifically, this study suggests an energy-efficient IoT architecture for the early detection of wildfires backed by fog-cloud computing technologies. To evaluate the repeatable information obtained from IoT sensors in a time-sensitive manner, Jaccard similarity analysis is used. This data is assessed in the fog processing layer and reduces the single value of multidimensional data called the Forest Fire Index. Finally, based on Wildfire Triggering Criteria, the Artificial Neural Network (ANN) is used to simulate the susceptibility of the forest area. ANN are intelligent techniques for inferring future outputs as these can be made hybrid with fuzzy methods for decision-modeling. For productive visualization of the geographical location of wildfire vulnerability, the Self-Organized Mapping Technique is used. Simulation of the implementation is done over multiple datasets. For total efficiency assessment, outcomes are contrasted in comparison to other techniqueS

LoRaWAN Network for Fire Monitoring in Rural Environments

The number of forest fires that occurred in recent years in different parts of the world is causing increased concern in the population, as the consequences of these fires expand beyond the destruction of the ecosystem. However, with the proliferation of the Internet of Things (IoT) industry, solutions for early fire detection should be developed. The assessment of the fire risk of an area and the communication of this fact to the population could reduce the number of fires originated by accident or due to the carelessness of the users. This paper presents a low-cost network based on Long Range (LoRa) technology to autonomously evaluate the level of fire risk and the presence of a forest fire in rural areas. The system is comprised of several LoRa nodes with sensors to measure the temperature, relative humidity, wind speed and CO2 of the environment. The data from the nodes is stored and processed in a The Things Network (TTN) server that sends the data to a website for the graphic visualization of the collected data. The system is tested in a real environment and, the results show that it is possible to cover a circular area of a radius of 4 km with a single gateway.This work was partially supported by the “Ministerio de Ciencia, Innovación y Universidades” through the “Ayudas para la adquisición de equipamiento científico-técnico, Subprograma estatal de infraestructuras de investigación y equipamiento científico-técnico (plan Estatal I+D+i 2017-2020)” (project EQC2018-004988-P), by Universidad de Granada through the “Programa de Proyectos de Investigación Precompetitivos para Jóvenes Investigadores. Modalidad A jóvenes Doctores” of “Plan Propio de Investigación y Transferencia 2019” (PPJIA2019.10), by the Campus de Excelencia Internacional Global del Mar (CEI·Mar) through the “Ayudas Proyectos Jóvenes Investigadores CEI·Mar 2019”, (Project CEIJ-020), by the European Union through the ERANETMED (Euromediterranean Cooperation through ERANET joint activities and beyond) (Project ERANETMED3-227 SMARTWATIR)