Fire Robot Research Articles

Design and implementation of an autonomous fire-extinguishing robot with SMS alert functionality

Fire outbreak represents a formidable threat, capable of causing loss of life, property destruction, and permanent injuries. Firefighters bravely confront these hazards, placing themselves at serious risk to protect communities. Despite the inherent dangers, their selfless service remains vital. Among recent technological advancements, firefighting robots have emerged as significant tools for mitigating such risks. These robots utilize machine learning and cutting-edge sensor technologies to enhance fire detection accuracy, minimizing false alarms. To improve the performance of the fire robot, this study designed and implemented an Arduino UNO microcontroller based on the ATmega32 and developed using C++ language. In addition to equipping it with SMS capability that allows it to notify the concerned entity about an outbreak, the developed robot operates autonomously thereby minimizing human error in its operation. With the aid of the ultrasonic sensors, the robot navigates and avoids obstacles collision with high precision. Integrated with flame and smoke sensors controlled by the microcontroller ensures swift fire detection. By autonomously sprinkling water from a mounted container, it effectively suppresses fires. Through this innovative design, the study aims to bolster fire response capabilities, reducing reliance on human intervention and enhancing safety for both firefighters and civilians. From the performance evaluation carried out on the developed robot, it was observed that the robot has exhibited an effective performance in detecting and extinguishing fires using the various sensors.

Research on real-time fire detection and locating for automotive firefighting robot in factories based on Convolutional Neural Network

Automotive fire robots that are used in factories can carry out diverse operations in regard to patrolling, fire detection, and programmed fire rescue. An accurate detection of fire sources in factories is significantly crucial for unmanned firefighting robot in terms of building a reliable sensor system. An approach proposed by this paper to recognize the color and dynamic shape of varying flames based on HSV color algorithms and Convolutional Neural Network. As a comparison to traditional RGB image processing, this approach is more efficient in isolating colors in environment and more adaptive to a fire site that includes multiple noise factors. The research in this paper uses image processing algorithms that is trained by CNN to detect flames in simulated factory environments, followed by a HSV color locating algorithm to compute the coordinates of target fire to perform inverse kinematic analysis on an unmanned firefighting robot.

The role of investment in the development of industrial enterprises

Economic regulation of the processes of modernization of industrial production is a fundamental principle of industrial policy. It is noted that investments act as a mechanism that can launch the development of industrial enterprises and allow them to enter a trajectory of accelerated development. Particular attention is focused on current internal and external problems of industrial enterprises and ways to solve them. As an example of the development and implementation of an innovative development strategy under conditions of severe external restrictions, the activities of the limited liability company “Engineering Center for Fire Robotics “EFER” of the Republic of Karelia” are considered. Currently, the EFER Engineering Center occupies a leading position in the development and production of robotic fire extinguishing installations and fire robots in Russia, which could not be achieved without the development of the production base and without maintaining annual R&D costs in the amount of 5÷8% of the cost of production. Using the example of the EFER Engineering Center, the possibility of innovative development of an enterprise is demonstrated, subject to government support and investment. Conclusions are drawn about the need to attract additional finance, which will allow industrial enterprises to enter the trajectory of accelerated development. It is indicated that in order to create a favorable investment climate, an investment strategy is needed that determines the investment priorities of the region. The dynamics of attracted investments depend on the economic climate and investment attractiveness of the regions. The region’s investment strategy should provide for the development of a comprehensive plan that ensures the achievement of the strategic vision and development goals of the region, taking into account the stimulation of innovative industrial growth and the creation of new opportunities for investors. A favorable investment climate will create objective prerequisites for the development of competitive industrial enterprises capable of ensuring the technological sovereignty of the Russian Federation.

Study on Fire Suppression of Piloti Architecture Based on a Perception Survey of Fire Officials

This study aims to propose an effective fire suppression strategy for piloti buildings based on the fire hazard analysis of piloti building fires, analysis of prior research, and a perception survey of fire officials. The use of combustible building materials in piloti architecture poses a risk of rapid combustion, which may cause ground entrances to lose their evacuation function because of flames. Based on the results of this study, piercing applicators and cellar nozzles were suitable for use as a fire extinguishing strategy in pilotis with the aid of fireballs and thermal imaging cameras. Secondly, trios and quadruples were used to extinguish fires. Thirdly, fire suppression strategies based on the fourth industrial revolution, such as fire drones and fire robots, were used to extinguish fires.

Real-time fire detection algorithms running on small embedded devices based on MobileNetV3 and YOLOv4

AimFires are a serious threat to people’s lives and property. Detecting fires quickly and effectively and extinguishing them in the nascent stage is an effective way to reduce fire hazards. Currently, deep learning-based fire detection algorithms are usually deployed on the PC side.MethodsAfter migrating to small embedded devices, the accuracy and speed of recognition are degraded due to the lack of computing power. In this paper, we propose a real-time fire detection algorithm based on MobileNetV3-large and yolov4, replacing CSP Darknet53 in yolov4 with MobileNetV3-large to achieve the initial extraction of flame and smoke features while greatly reducing the computational effort of the network structure. A path connecting PANet was explored on Gbneck(104, 104, 24), while SPP was embedded in the path from MobileNetV3 to PANet to improve the feature extraction capability for small targets; the PANet in yolo4 was improved by combining the BiFPN path fusion method, and the improved PANet further improved the feature extraction capability; the Vision Transformer model is added to the backbone feature extraction network and PANet of the YOLOv4 model to give full play to the model’s multi-headed attention mechanism for pre-processing image features; adding ECA Net to the head network of yolo4 improves the overall recognition performance of the network.ResultThese algorithms run well on PC and reach 95.14% recognition accuracy on the public dataset BoWFire. Finally, these algorithms were migrated to the Jeston Xavier NX platform, and the entire network was quantized and accelerated with the TensorRT algorithm. With the image propagation function of the fire robot, the overall recognition frame rate can reach about 26.13 with high real-time performance while maintaining a high recognition accuracy.ConclusionSeveral comparative experiments have also validated the effectiveness of this paper’s improvements to the YOLOv4 algorithm and the superiority of these structures. With the effective integration of these components, the algorithm shows high accuracy and real-time performance.

Implementation of Solar Powered Autonomous Fire Fighting Robot

The creation of a remote-controlled fire robot is the primary objective of this project. The water tank and wireless pump on this robot both spray water. A Peripheral Interface Controller (PIC) microcontroller performs the functionality offered. The transmitter button sends instructions to the receiver, telling it to move the robot in front, back, left, and right. To run the DC motor through the motor controller Integrated Circuit (IC) for the necessary duty, the decoder decodes the data before sending it to another microcontroller. The remote control has a decent range of up to 100 metres with the right antenna. The water tank and water pump linked to the robot body are operated by the microcontroller's output in conjunction with the appropriate signal from the transmitter. An Arduino Uno series microprocessor controls the entire operation.

Design and Fabrication of Automated Fire Fighting Robot

Abstract: Flames can cause critical harm and death toll, and it is pivotal to have powerful measures to control and douse them. The utilization of robots for firefighting activities has become progressively famous, provided their capacity to work in risky and testing conditions. In this paper, we present a point-by-point concentrate on the plan, improvement, and execution of a putting out fire robot. The putting out fires robot Is intended to explore through jumbled and temperamental conditions and furnished with sensors and cameras to identify and screen the fire. It is additionally equipped for conveying and sending firefighting gear, for example, quenchers and water hoses. The plan includes choosing the suitable sensors, actuators, and power sources to accomplish the ideal usefulness. The robot’s motion framework is intended to empower it to travel through lopsided territory and flotsam and jetsam, and it has a controller arm to get and work firefighting gear. The execution includes building the actual equipment and fostering the product that controls its activities. The equipment might be created utilizing a blend of off-the-rack parts and specially constructed parts. The product is intended to empower the robot to work independently in a putting out fires situation, utilizing Al calculations to identify and group various sorts of flames and select proper reactions in view of the seriousness of the circumstance. The robot is additionally intended to speak with human administrators, empowering them to screen the robot’s activities and settle on choices in view of the data given by the sensors

Research on Automatic Flame Recognition and Tracking of Intelligent Fire Robot Based on STC89C52

Research on Automatic Flame Recognition and Tracking of Intelligent Fire Robot Based on STC89C52

Evaluating the Effectiveness of Fire Robots for the Protection of Transport Infrastructure Facilities

The paper considers a methodology for modeling fire dynamics when evaluating the effectiveness of fire robots to protect various objects of transport infrastructure with a high fire load on the example of an aircraft hangar. It is shown that the simulation of fire protection means with varying parameters can distort the results of the evaluation obtained on the basis of simulation. A comparative analysis of different ways of simulating the work of fire robots in the simulation of a fire resulting from the spill and ignition of aviation fuel in an area of 200 sq. m., in a hangar has been carried out.

Моделирование траектории струи огнетушащего средства из пожарного лафетного ствола при возмущающих воздействиях

One of the important stages in the development of fire safety systems and determining the area of efficient fire extinguishing of robotic fire extinguishing installations using remotely controlled fire monitors is a calculation of the trajectory of the fire extinguishing agent jet. In the absence of disturbing influences, the jet trajectory is well described by mathematical models built based on the empirical data. However, in the presence of wind action in open space and automatic control mode, significant disturbing factors are introduced into the calculation of the jet trajectory, which make it difficult to construct the required trajectory of the fire extinguishing agent. To solve this problem, the algorithms were developed to simulate the movement of a jet under disturbing influences using the methods of computational fluid dynamics and verification based on the results of field tests. Algorithms of the computational fluid dynamics based on numerical methods for solving the equations of gas-hydrodynamics of flows (equations of conservation of energy, momentum, continuity, state, etc.) allow to model the corresponding processes with high accuracy. Based on the simulation results, the jet trajectory was obtained, and its comparison with the results of field experiments indicates that the use of computational fluid dynamics methods in particular the k–ε model (mass density and turbulence kinetic energy dissipation rate) allows to describe the jet trajectory from the fire monitor with a sufficiently high accuracy under disturbing influences. The obtained calculation methods can be used in the development of algorithms for automatic control of fire robots operating under wind load conditions, including for solving the problem of determining its identification by the deviation of the jet from the calculated trajectory.

A Thermal Imaging Flame-Detection Model for Firefighting Robot Based on YOLOv4-F Model

Fire robots are an effective way to save lives from fire, but their limited detection accuracy has greatly hampered their practical applications in complicated fire conditions. This study therefore proposes an advanced thermal imaging flame detection model of YOLOv4-F based on YOLOv4-tiny. We replaced the Leaky ReLU activation function with the Mish activation function in the YOLOV4-tiny feature extraction network. A Spatial Pyramid Pooling (SPP) was also added to increase the receiving range of the feature extraction network. To improve the feature fusion efficiency between multi-scale feature layers, a Path Aggregation Network (PANet) was adopted to replace the YOLOv4-tiny Feature Pyramid Network (FPN) with full use of feature information; a high-quality dataset containing 14,757 thermal imaging flame images was built according to the PASCAL VOC 2007 dataset standard. The results show that, when compared to the YOLOv4-tiny, YOLOv5-s, and YOLOv7-tiny models, the average detection accuracy of the proposed YOLOv4-F model is 5.75% higher, the average mAP of the five IOU cases rises by 7.02%, and the average detection confidence of three scaled flames shows a 18.09% gain. The proposed YOLOV4-F meets the requirements of fire robots on real-time responses and accurate flame detection, offering an important tool to improve the performance of the current fire robots.

Design of Home-use Fire Fighting Robots and Research on Automatic Control System

Responding quickly to fires, reducing secondary disasters and ensuring the safety of life and property are important issues in firefighting. With the progress of science and technology, firefighting robots have entered people’s sight. Based on this, this paper proposes a home-based firefighting robot to reduce fire losses. The home-type firefighting robot is equipped with a walking system and a clamping device. ANSYS software is used to perform finite element analysis on key components to verify the rationality of the structural design. The program mainly uses the PWM module in the K60 chip, and the I/O module is designed. CCD is used for image acquisition and K60 microprocessor. The classical PID control algorithm is still used to make the fire robot achieve the effect of smooth and fast movement. The incremental PID algorithm is used to realize the fast response of the motor.

An autonomous positioning method for fire robots with multi-source sensors

The present technology, based on laser and visual SLAM navigation and positioning, does not apply to the event of a fire in a room where there is a large amount of smoke, for its increasingly obvious defects. In addition, traditional track deduction technology based on photoelectric encoder has accumulated error, and noise disturbance exists in the INS inertial navigation measurement technology, and the UWB positioning technology is vulnerable to NLOS disturbance caused by site occlusion. To solve the problem of accurate positioning of Autonomous Mobile fire-fighting robot in smoke scenes, the system design is optimized by adopting the following methods: using IMU-assisted residual chi-square criterion to detect whether there is NLOS in UWB, introducing IMU instantaneous compensation positioning data and adopting Chan algorithm fitting of the second multiplication to ensure the stability and accuracy of UWB data; meanwhile, a tight combination model of navigation and positioning is designed: via the improved Kalman filter algorithm, fused with the magnetic encoder track estimation pose, UWB absolute and IMU heading angle pose to realize the accurate positioning of the fire robot in the smoke scene. Finally, the fusion simulation model and algorithm are verified by MATLAB, as it shows, the method has an average positioning accuracy of 98.63% in the X-axis direction, 99.52% in the Y-axis direction, and 97.24% in the heading angle, which solves the inherent physical defects of a single positioning sensor and serves as a reliable and accurate solution for indoor robot positioning.

Design and Development of Intelligent Fire-fighting Robot Based on STM32

With the rapid growth of economy, fires occur frequently in various dangerous places. According to the investigation, in the ancient tragic fire cases, the number of intelligent mobile fire-fighting equipment is very small, and ordinary fire extinguishers and fire-fighting trains can’t put out the fire in time and quickly. As a kind of robot, intelligent fire-fighting robot plays an increasingly important role in fire-fighting and rescue. In this paper, the design of fire robot is studied. Intelligent fire-fighting robot is mainly composed of fire-fighting movement system, fire-fighting water spray system, fire-fighting control system and other components. All parts cooperate with each other and work together to complete the fire-fighting task.

An Improved Near-Field Computer Vision for Jet Trajectory Falling Position Prediction of Intelligent Fire Robot.

An improved Near-Field Computer Vision (NFCV) system for intelligent fire robot was proposed that was based on our previous works in this paper, whose aims are to realize falling position prediction of jet trajectory in fire extinguishing. Firstly, previous studies respecting the NFCV system were briefly reviewed and several issues during application testing were analyzed and summarized. The improved work mainly focuses on the segmentation and discrimination of jet trajectory adapted to complex lighting environment and interference scenes. It mainly includes parameters adjustment on the variance threshold and background update rate of the mixed Gaussian background method, jet trajectory discrimination based on length and area proportion parameters, parameterization, and feature extraction of jet trajectory based on superimposed radial centroid method. When compared with previous works, the proposed method reduces the average error of prediction results from 1.36 m to 0.1 m, and the error variance from 1.58 m to 0.13 m. The experimental results suggest that every part plays an important role in improving the functionality and reliability of the NFCV system, especially the background subtraction and radial centroid methods. In general, the improved NFCV system for jet trajectory falling position prediction has great potential for intelligent fire extinguishing by fire-fighting robots.

Multi-sensor information fusion detection system for fire robot through back propagation neural network.

ObjectiveTo reduce the danger for firefighters and ensure the safety of firefighters as much as possible, based on the back propagation neural network (BPNN) the fire sensor multi-sensor information fusion detection system is investigated.MethodAccording to previous studies, the information sources and information processing methods for the design of this study are first explained. Then, the basic structure and flowchart of the research object in this study are designed. Based on the structure diagram and flowchart, the BPNN is selected to fuse the feature layers in this study, and the fuzzy control is selected to fuse the decision layers in this study. The multi-sensor information fusion detection system collects information for the sensors first, processes the collected information, and sends it to the processor of the robot. The processor analyzes and processes the received signal, and transmits the obtained information to the control terminal through the wireless communication system.ResultsThrough the tests in this study, it is found that when the number of hidden layer nodes of the BPNN is 7, the optimal training result is obtained. On this basis, the test of BPNN in this study is performed. The test results show that after 127 iterations, the error of the BPNN reaches the lowest target value, indicating that the BPNN achieves an excellent level of accuracy. The trained BPNN has a running time of 0.0276 s and a mean square error of 0.0013. The smaller the mean square error value is, the higher the accuracy of the BPNN is, which shows that the BPNN meets the high precision requirements of this study.ConclusionThe research on the multi-sensor information fusion detection system of fire robots in this study can provide theoretical support for the research on forest fire detection in China. Since the proposed BPNN-based robot is applied to the inspection and processing of forest remaining fire, the results are applicable to the forests of various countries, with a wide range of applications.

Structural and intelligent scheme of navigation system of a ground-based mobile robot for forming a traffic route

At the beginning of Russian studies on the task of creating mobile ground fire robots for use in extreme situations in late 1980, it was justified by the fact that firefighters need protection when dealing with the consequences of accidents in areas with high levels of radioactive pollution. The use of fire robotics was increase because of a large number of technogenic accidents. There was a need for use of fire ground robots, where emergency situations, fire, and technogenic accidents arise because it’s dangerous for the life and health of firefighters and people. Fire mobile ground robot is an automated self-propelled technical device which does given commands of human and other actions without human. People use this robot at the accident on area, where is dangerous for the health of firefighters things are situated like oil, nuclear, chemical objects. Now we are considering a structural and intelligent navigation system of fire mobile ground robot, in which a structure of fire robot must create a good way to the center of ignition, control parameters of motions, track own location for safe navigation and improvement tactical of opportunities of the firefighters. The introduction of a fire mobile ground robotics device is needed for an increase in the tactical capabilities of fire detachments during the extinguishing of the fire. The goal is to the definition of tasks and development structural and intelligent scheme of the navigation system of fire mobile robot for the shortest path to fire and extinguish a fire.

Protection of turbine halls of power plants from exposure to high temperatures in fire conditions

There are numerous cases when fires in power plant turbine halls causes the collapse of roof metal structures. The use of conventional firefighting equipment in high-bay facilities has proved to be ineffective or unacceptable. In this situation fire robots are the most feasible option. Today the best variant is a fire robot that is based on a traditional fire monitor and equipped with infrared fire seat detectors. Some specific advantages of fire robots include their ability to operate under low visibility with high smoke generation conditions that are typical of a fire in a turbine hall. The program of roof structures cooling down is designed and tested in advance so that fire robots can perform their functions in automatic mode. Fire robots can be included into permanent-type fire safety systems that are designed taking into account specific construction features of a facility and temperature conditions in case of a fire. Such composite system is a multifunctional complex that is able to perform versatile fire protection functions. The most appropriate fire robot types to be used in such complex fire protection system are fire robots based on conventional fire monitors, as they have some notable advantages compared with mobile robots or androids. One of them is their ability to protect big areas starting from 5 and up to 15 thousand square meters with fire suppressing media flow rate range just 20-60 l/sec correspondingly. Water or foam can be delivered via air exactly to the fire seat instead of spraying over the total designed area. Moreover, wetting intensity can be maintained at a level that corresponds to fire seat intensity.

P PENGAPLIKASIAN TEKNOLOGI SMARTPHONE DALAM PENGONTROLOAN ROBOT DALAM PENCARIAN TITIK API

Pemanfaatan Teknologi Smartphone dalam penelitian ini bertujuan untuk mengontrol Robot dalam mencari titik api sehingga kita bisa mengetahui titik api dari sudut mana pun. Dan Robot bisa di atur secara otomatis dalam pencarian titik api tanpa harus dikendalikan. Apabila robot menemukan titik api maka robot akan memberitahukan ke Smartphone bahwa api ditemukan. Untuk jalur komunikasi Robot dan Smartphone menggunakan Bluetooth HC-05.
 Penelitian ini bertujuan untuk mempermudah manusia menemukan titik api didalam ruangan yang sempit dan yang susah untuk dilewati. Sehingga pencegahan pun cepat dilakukan agar tidak merambat ke yang lebih besar. Dalam hasil penelitian ini menunjukkan bahwa Robot yang dibuat berfungsi dengan baik dan dapat dikembangkan untuk skala yang lebih besar.

Smartphone Application Technology In Control Robot In Search Focal Point (Pengaplikasian Teknologi Smartphone Dalam Pengontrolan Robot Dalam Pencarian Titik Api)

Smartphone Technology Utilization in this research aims to control the robot in finding hotspots so that we can know the point of fire from any angle. And the robot can be set automatically in the search for hotspots without having to be controlled. When the robots find fire robot will notify to the Smartphone that fire was found. For communication lines and Smartphone Robot uses HC-05 Bluetooth.This study aims to facilitate human find fire in the room is cramped and difficult to pass. So prevention was quickly taken not to spread to a larger one. In the results of this study indicate that the robot is made to function properly and can be expanded to a larger scale.