B. Madhevan

Bio: B. Madhevan is an academic researcher from VIT University. The author has contributed to research in topics: Mobile robot & Firefighting. The author has an hindex of 2, co-authored 3 publications receiving 10 citations.

Modelling, Simulation and Mechatronics Design of a Wireless Automatic Fire Fighting Surveillance Robot

Abstract: The aim of this study is to design and develop an autonomous fire proof rescue robot. The robot is designed in such a way, that it can traverse through fire and hazardous situations. Further, it will sense and communicate information regarding these situations in real time with the server. The robot is fixed with multi-sensors and further, a driver circuit has been integrated for communication in these hazardous situations through Zigbee and a data acquisition system (DAQ). In mechanical design first, a 3D solid model is generated using Solid works software to understand the basic structure of robot which provides information regarding robotic platform, size and location of various components. The developed fire fighting robot is a predominately outdoor ground-based mobile robotic system with onboard subdual systems that can traverse autonomously in the hazardous environment. The robot is designed such that it can traverse into the fire and send information regarding the fire behaviour and also the images of the victim’s location by using a camera. Further, a mathematical model which describes the kinematics and dynamic behaviour of robot motion are done. V-REP is used to create the simulation of the robot in a fire simulated fire environment. Finally, for the path planning, various techniques are discussed such as V-REPs inbuilt path planning module, A*, Fuzzy logic and artificial potential fields.

A Novel Image Intelligent System Architecture for Fire Proof Robot

Abstract: The aim of this research is to design and analyze a fireproof firefighting robot that can enter into fire environment and navigate itself through the fire and send information about the fire behavior. This robot would help the fire rescue team to better understand the fire behavior and trapped person location and thus would be a critical advantage in term of time saving and rescue teams risk for their own life. In this paper, an image processing system and communication architecture for firefighting robot based on GSM technology and microcontroller is designed. Camera connected to microcontroller using serial cable will capture the image data and store it on a storage device. The processed image are sending to the predefined mobile number using GPRS technology. The encoder is used to improve the efficiency of compressed image. MATLAB software is used for the image processing which uses Fuzzy Coded Means to complete this process.

Integration of Internet-Accessible Resources in the Field of Mobile Robots

Abstract: The number and variety of mobile robot applications are increasing day by day, both in an industry and in our daily lives. First developed as a tool, nowadays mobile robots can be integrated as an entity in Internet-accessible resources. The present work is organized around four potential resources such as cloud computing, Internet of things, Big data analysis and Co-simulation. Further, the focus relies on integrating, analyzing and discussing the need for integrating Internet-accessible resources and the challenges deriving from such integration, and how these issues have been tackled. Hence, the research work investigates the concepts of the Internet-accessible resources from the aspect of the autonomous mobile robots with an overview of the performances of the currently available database systems. IaR is a world-wide network of interconnected objects, can be considered an evolutionary process in mobile robots. IaR constitutes an integral part of future Internet with data analysis, consisting of both physical and virtual things. Keywords—Internet-accessible resources, Cloud computing, Internet of things, Big data analysis and Co-simulation, Mobile robot.

Virtual and augmented reality technologies for emergency management in the built environments: A state-of-the-art review

Abstract: With the rapid technological advancements in recent decades, virtual reality (VR) and augmented reality (AR) technologies have been increasingly adopted to address various challenges in emergency management in the built environments. This paper presents a review of state-of-the-art applications in this rapidly evolving area. A total of 84 relevant articles are identified based on searching in the Web of Science Core Collection and snowballing. These papers are then organized based on a taxonomy developed in this study. Next, a range of VR/AR applications presented in these papers that are aimed to enhance various processes associated with pre-emergency preparedness, responses during emergency and post-emergency recovery are reviewed in detail. The existing VR/AR applications are also described from a human-computer interaction perspective. Finally, current research trends, knowledge gaps and directions for future research are discussed. The findings presented in this paper are expected to provide a synthetic and critical review of state-of-the-art VR/AR applications for emergency management in the built environment and facilitate further advancements in both research and practice in this area.

Modelling, Simulation and Mechatronics Design of a Wireless Automatic Fire Fighting Surveillance Robot

Abstract: The aim of this study is to design and develop an autonomous fire proof rescue robot. The robot is designed in such a way, that it can traverse through fire and hazardous situations. Further, it will sense and communicate information regarding these situations in real time with the server. The robot is fixed with multi-sensors and further, a driver circuit has been integrated for communication in these hazardous situations through Zigbee and a data acquisition system (DAQ). In mechanical design first, a 3D solid model is generated using Solid works software to understand the basic structure of robot which provides information regarding robotic platform, size and location of various components. The developed fire fighting robot is a predominately outdoor ground-based mobile robotic system with onboard subdual systems that can traverse autonomously in the hazardous environment. The robot is designed such that it can traverse into the fire and send information regarding the fire behaviour and also the images of the victim’s location by using a camera. Further, a mathematical model which describes the kinematics and dynamic behaviour of robot motion are done. V-REP is used to create the simulation of the robot in a fire simulated fire environment. Finally, for the path planning, various techniques are discussed such as V-REPs inbuilt path planning module, A*, Fuzzy logic and artificial potential fields.

KutralNet: A Portable Deep Learning Model for Fire Recognition

Abstract: Most of the automatic fire alarm systems detect the fire presence through sensors like thermal, smoke, or flame. One of the new approaches to the problem is the use of images to perform the detection. The image approach is promising since it does not need specific sensors and can be easily embedded in different devices. However, besides the high performance, the computational cost of the used deep learning methods is a challenge to their deployment in portable devices. In this work, we propose a new deep learning architecture that requires fewer floating-point operations (flops) for fire recognition. Additionally, we propose a portable approach for fire recognition and the use of modern techniques such as inverted residual block, convolutions like depth-wise, and octave, to reduce the model’s computational cost. The experiments show that our model keeps high accuracy while substantially reducing the number of parameters and flops. One of our models presents 71% fewer parameters than FireNet, while still presenting competitive accuracy and AUROC performance. The proposed methods are evaluated on FireNet and FiSmo datasets. The obtained results are promising for the implementation of the model in a mobile device, considering the reduced number of flops and parameters acquired.

Lightweight and efficient octave convolutional neural network for fire recognition

Abstract: Fire recognition from visual scenes is a demanding task due to the high variance of color and texture. In recent years, several fire-recognition approaches based on deep learning methods have been proposed to overcome this problem. However, building deep convolutional neural networks usually involves hundreds of layers and thousands of channels, thus requiring excessive computational cost, and a considerable amount of data. Therefore, applying deep networks in real-world scenarios remains an open challenge, especially when using devices with limitations in hardware and computing power, e.g., robots or mobile devices. To address this challenge, in this paper, we propose a lightweight and efficient octave convolutional neural network for fire recognition in visual scenes. Extensive experiments are conducted on FireSense, CairFire, FireNet, and FiSmo datasets. In overall, our architecture comprises fewer layers and fewer parameters in comparison with previously proposed architectures. Experimental results show that our model achieves higher accuracy recognition, in comparison to state-of-the-art methods, for all tested datasets.

An automated water dispensing system for controlling fires in coal yards

Abstract: Abstract In spite of recent moves to wean the world of fossil fuels, coal remains the main source of power in many countries. Coal yards are prone to spontaneous ignition, a problem faced in every country that stores or transports coal. Depending on the environment-temperature, ventilation, and the rank of the coal-heating and self-ignition can be a longer or shorter process, but the possibility can never be entirely dismissed. A plethora of studies have modelled this oxidation behavior and proposed countermeasures. Most often, human intervention is necessary, which is both slow and dangerous for the firefighters involved. In this study, we propose to build a complete firefighting solution which is mounted on a number of towers sufficient to cover the area of an open coal yard, complete with redundancy. Each tower includes an inexpensive infrared detector, a water dispenser and a controller programmed to identify areas of elevated temperature, and actuate the dispenser. The heat direction algorithm calculates the parameters to position the water dispenser so that it covers the area. A prototype has been built from inexpensive components to demonstrate the effectiveness at detecting and extinguishing arising fires, and a solution has been costed for the coal yard in the case study. This work has been conducted in collaboration with the managers of the coal yard of a power plant.