IMPROVED REAL-TIME HOUSE FIRE DETECTION SYSTEM PERFORMANCE WITH IMAGE CLASSIFICATION USING MOBILENETV2 MODEL

The problem with the Ardunio microcontroller-based fire detection system with fire and smoke sensors is the detection distance. For example, in another research, it was stated that the maximum distance for fire detection on two pieces of paper that were burned was 140 cm. This means that if the fire point is at a farther distance, the system cannot detect a fire early, of course, this will be problematic if used in a wider room. Based on these problems, a system is needed that can detect fires in large rooms. A method that can be used is detection using image classification. MobileNetV2 is a real-time model for classifying or detecting an object in an image. In this study, the model was built using real-time based on the TensorFlow and Keras libraries. The system will use a laptop with an Nvidia GeForce MX130 GPU, a 48MP resolution smartphone camera, and the OpenCV library for the image classification process, as well as Telegram for sending fire notifications via the Re-quests library. The test results obtained on burnt 80/90 motorcycle tires, the most optimal detection distance is 7 meters with an accuracy of 99.91%. While testing on two sheets of paper that are burned, the most optimal detection distance is 3 meters with an accuracy of 99.75%. The average response time obtained varies greatly from 74.5 ms to 117.1 ms, which depends on the internet network connection

Study Of Pool Fire Heat Release Rate Using Video Fire Detection

To provide fire safety for high performance buildings, various types of fire/smoke detection systems are developed. Video fire detection is one of the important aspects in the development of fire detection system. It is particularly useful in large spaces with high headroom and buildings with cross ventilation design where traditional spot type smoke detection methods may not be effective. For the development of video fire detection system, spatial, spectral and temporal parameters are used to identify the fire source. One of the parameters captured by the video fire detection system is the flame height. With the information of flame height, real time heat release rate of fire can be estimated which is a very important parameter in determining the smoke generation rate and fire severity. Such information is very important in assisting evacuation and smoke control. In this study, experiments of pool fires with different pool diameters of 100mm, 200mm, 300mm and 400mm are conducted in the fire chamber of the laboratory in Department of Building Services Engineering, The Hong Kong Polytechnic University. The flame images, room temperatures and mass loss rates of the fuel are measured. The flame images are segmented using multi – threshold algorithm in a modified Otsu method and Rayleigh distribution analysis (modified segmentation algorithm). The algorithm use the optimum threshold values calculated to extract the pool fire images from a video sequence. After segmentation, flame height information can be obtained. In addition, other flame characteristics are also used for recognizing the flame region including flame color, flame light intensity, flame shape, and flicker frequency. Once the flame height is identified by the system, the heat release rate can be estimated using the equation developed by McCaffrey. The calculated heat release rates are then compared with measured heat release rate data. The results show that using flame height image for estimating real time heat release rate is promising

An Impulse Detection Methodology and System with Emphasis on Weapon Fire Detection

This dissertation proposes a methodology for detecting impulse signatures. An algorithm with specific emphasis on weapon fire detection is proposed. Multiple systems in which the detection algorithm can operate, are proposed. In order for detection systems to be used in practical application, they must have high detection performance, minimizing false alarms, be cost effective, and utilize available hardware. Most applications require real time processing and increased range performance, and some applications require detection from mobile platforms. This dissertation intends to provide a methodology for impulse detection, demonstrated for the specific application case of weapon fire detection, that is intended for real world application, taking into account acceptable algorithm performance, feasible system design, and practical implementation. The proposed detection algorithm is implemented with multiple sensors, allowing spectral waveband versatility in system design. The proposed algorithm is also shown to operate at a variety of video frame rates, allowing for practical design using available common, commercial off the shelf hardware. Detection, false alarm, and classification performance are provided, given the use of different sensors and associated wavebands. The false alarms are further mitigated through use of an adaptive, multi-layer classification scheme, leading to potential on-the-move application. The algorithm is shown to work in real time. The proposed system, including algorithm and hardware, is provided. Additional systems are proposed which attempt to complement the strengths and alleviate the weaknesses of the hardware and algorithm. Systems are proposed to mitigate saturation clutter signals and increase detection of saturated targets through the use of position, navigation, and timing sensors, acoustic sensors, and imaging sensors. Furthermore, systems are provided which increase target detection and provide increased functionality, improving the cost effectiveness of the system. The resulting algorithm is shown to enable detection of weapon fire targets, while minimizing false alarms, for real-world, fieldable applications. The work presented demonstrates the complexity of detection algorithm and system design for practical applications in complex environments and also emphasizes the complex interactions and considerations when designing a practical system, where system design is the intersection of algorithm performance and design, hardware performance and design, and size, weight, power, cost, and processing

Simulation and Design of an Intelligent Mobile Robot for Fire Fighting

The application of traditional frangible glass panel and automatic system such as smoke detector or heat detector requires a human response to realise the existence of fire and to perceive and determine its severity. However, fire-fighting system such as sprinkler causes the damage of the property and also injury and panic due to the water sprayed out when the system trigged. Thus to avoid such incident, a mobile robot with fire detection capability and fire fighting system to perform fire-fighting purpose is a new technology to reduce subsequent damage and secure life before the fire engine to attend. A navigation system base on fuzzy logic controller (FLC) is developed for the mobile robot in an ambiguous situation for fire fighting purpose. A method of Path Recognition Algorithms (PRA) providing robots the autonomous ability to judge purpose of action likes human base on the input sensors from the environment. Multiple fuzzy behaviours by fuzzy logic method have been developed to allow the robot over come some of the possible obstacles and resistances for the robot to navigate in unknown environment. Behaviours have been integrated with arbitration strategy to determine the appropriate behaviours by priority method with preset data. An ultrasonic sensor and an infrared thermal sensor were mounted on a 360 degree rotated stepper motor to scan distance between the robot and its immediate obstacles and fire source around its environment. A fuzzy base computer animation in virtual reality is developed to simulate a simple in-door environment for fire fighting purpose and a systematic implementation of real-time simulation of the mobile robot is presented. However traveling in such region to the target location, there exist some unknown obstacles for the mobile robot especially in real-world environment with unknown map and unpredictable obstacle location, thus the control algorithms must be able to promptly react upon the unpredictable. The simulation result of this study indicated that application of FLC in mobile robot could be a suitable system for fire detection and fire fighting task in an unknown environment. More comprehensive study in behaviour coordination will be the major focus to ensure smoother robot navigation and more effective fire detection capability. Keywords: (Fuzzy logic control, mobile robot, part recognition algorithms

A feasibility study: Forest Fire Advanced System Technology (FFAST)

The National Aeronautics and Space Administration/Jet Propulsion Laboratory and the United States Department of Agriculture Forest Service completed a feasibility study that examined the potential uses of advanced technology in forest fires mapping and detection. The current and future (1990's) information needs in forest fire management were determined through interviews. Analysis shows that integrated information gathering and processing is needed. The emerging technologies that were surveyed and identified as possible candidates for use in an end to end system include ""push broom'' sensor arrays, automatic georeferencing, satellite communication links, near real or real time image processing, and data integration. Matching the user requirements and the technologies yielded a ""strawman'' system configuration. The feasibility study recommends and outlines the implementation of the next phase for this project, a two year, conceptual design phase to define a system that warrants continued development

Aerial Forest Fire Detection and Monitoring Using a Small UAV

In recent years, large patches of forest have been destroyed by fires, bringing tragic consequences for the environment and small settlements established around these regions. In this context, it is essential that fire fighting teams possess an increased situational awareness about the fire propagation, in order to promptly act in the extinguishing process. Recent advances in UAV technology allied with remote sensing and computer vision techniques show very promising UAVs applicability in forest fires detection and monitoring. Besides presenting lower operational costs, these vehicles are able to reach regions that are inaccessible or considered too dangerous for fire fighting crews operations. This paper describes the application of a real-time forest fire detection algorithm using aerial images captured by a video camera onboard    an Unmanned Aerial Vehicle (UAV). The forest fire detection algorithm consists of a rule-based colour model that uses both RGB and YCbCr colour spaces to identify fire pixels. An intuitive targeting system was also developed, allowing the detection of multiple fires at the same time. Additionally, a fire geolocation algorithm was developed in order to estimate the fire location in terms of latitude (φ),  longitude     (λ) and altitude (h). The geolocation algorithm consists of applying two coordinates systems transformations between the body-fixed frame, North-East-Down frame (NED) and Earth-Centered, Earth Fixed (ECEF) frame. Flight tests were performed during  a controlled burn in order to assess the fire detection algorithm performance. The algorithm was able to detect the fire with few false positive detections. Keywords: Aerial fire detection algorithm, Aerial fire monitoring, Forest fire, UAV, Remote sensin

A semi-empirical cellular automata model for wildfire monitoring from a geosynchronous space platform

The environmental and human impacts of wildfires have grown considerably in recent years due to an increase in their frequency and coverage. Effective wildfire management and suppression requires real-time data to locate fire fronts, model their propagation and assess the impact of biomass burning. Existing empirical wildfire models are based on fuel properties and meteorological data with inadequate spatial or temporal sampling. A geosynchronous space platform with the proposed set of high resolution infrared detectors provides a unique capability to monitor fires at improved spatial and temporal resolutions. The proposed system is feasible with state-of-the-art hardware and software for high sensitivity fire detection at saturation levels exceeding active flame temperatures. Ground resolutions of 100 meters per pixel can be achieved with repeat cycles less than one minute. Atmospheric transmission in the presence of clouds and smoke is considered. Modeling results suggest fire detection is possible through thin clouds and smoke. A semi-empirical cellular automata model based on theoretical elliptical spread shapes is introduced to predict wildfire propagation using detected fire front location and spread rate. Model accuracy compares favorably with real fire events and correlates within 2% of theoretical ellipse shapes. This propagation modeling approach could replace existing operational systems based on complex partial differential equations. The baseline geosynchronous fire detection system supplemented with a discrete-based propagation model has the potential to save lives and property in the otherwise uncertain and complex field of fire management

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

Real-time image and video processing for advanced services on-board vehicles for passenger transport

The paper exploits the video camera available on-board vehicles for public transport, such as trains, coaches, ferryboats, and so on, to implement advanced services for the passengers. The idea is implementing not only surveillance systems, but also passenger services such as: people counting, smoke and/or fire alarm, automatic climate control, e-ticketing. For each wagon, an embedded acquisition and processing unit is used, which is composed by a video multiplexer, and by an image/video signal processor that implements in real-time algorithms for advanced services such as: smoke detection, to give an early alarm in case of a fire, or people detection for people counting, or fatigue detection for the driver. The alarm is then transmitted to the train information system, to be displayed for passengers or the crew staff

Automatic Early Warning System Design with Firefighter Synchronization Based on Internet of Things (IoT)

The fire department or DamKar is one of the important agencies which is highly needed by Indonesian people, especially when a fire occurs. However, DamKar is often judged to be late in arriving at the location because help comes to the fire when the fire has already take a set. One of the reasons why delay happens in DamKar is because the report is received late by the DamKar officer. One of the fire prevention measures is to take the preventive action or early prevention from indications of a fire. Automatic early detection is needed in an emergency and requires speed and accuracy in overcoming the problem. designs an early detection system for fires that directs to DamKar and warehouse owners. This system can detect and provide temperature information in real time. This system works if there is a drastic change in temperature and there is a puff as soon as detected by the sensor The information is in the form of a notification "Excessive CO gas detected" if the temperature is in the range of 25 °C and the gas content is 100 PPM, if the temperature exceeds 35°C and the gas content is 500 PPM there will be a notification "The warehouse temperature is too hot", then a danger notification " indicated fire above”. From the experimental results, it is found that the mesh communication system can work properl