scholarly journals Applications of Artificial Intelligence in Fire Safety of Agricultural Structures

2021 ◽  
Vol 11 (16) ◽  
pp. 7716
Author(s):  
Chrysanthos Maraveas ◽  
Dimitrios Loukatos ◽  
Thomas Bartzanas ◽  
Konstantinos G. Arvanitis
Keyword(s):  
Artificial Intelligence ◽  
Neural Networks ◽  
Fire Safety ◽  
Smart Cities ◽  
Fire Retardant ◽  
Premature Death ◽  
Farm Animals ◽  
Fire Prevention ◽  
Smoke Movement ◽  
In Fire

Artificial intelligence applications in fire safety of agricultural structures have practical economic and technological benefits on commercial agriculture. The FAO estimates that wildfires result in at least USD 1 billion in agriculture-related losses due to the destruction of livestock pasture, destruction of agricultural buildings, premature death of farm animals, and general disruption of agricultural activities. Even though artificial neural networks (ANNs), genetic algorithms (GAs), probabilistic neural networks (PNNs), and adaptive neurofuzzy inference systems (ANFISs), among others, have proven useful in fire prevention, their application is limited in real farm environments. Most farms rely on traditional/non-technology-based methods of fire prevention. The case for AI in agricultural fire prevention is grounded on the accuracy and reliability of computer simulations in smoke movement analysis, risk assessment, and postfire analysis. In addition, such technologies can be coupled with next-generation fire-retardant materials such as intumescent coatings with a polymer binder, blowing agent, carbon donor, and acid donor. Future prospects for AI in agriculture transcend basic fire safety to encompass Society 5.0, energy systems in smart cities, UAV monitoring, Agriculture 4.0, and decentralized energy. However, critical challenges must be overcome, including the health and safety aspects, cost, and reliability. In brief, AI offers unlimited potential in the prevention of fire hazards in farms, but the existing body of knowledge is inadequate.

Simulation and Modelling in Fire Safety

2020 ◽  
pp. 232-262
Author(s):  
Tomaz Hozjan ◽  
Kamila Kempna ◽  
Jan Smolka
Keyword(s):  
Virtual Reality ◽  
Fire Safety ◽  
Rapid Development ◽  
Fire Spread ◽  
Practical Training ◽  
Smoke Movement ◽  
Fire Engineering ◽  
Limited Budget ◽  
Fire Scenarios ◽  
In Fire

Actual and future concerns in fire safety in buildings and infrastructure are challenging. Modern technologies provide rapid development in area of fire safety, especially in education, training, and fire-engineering. Modelling as a tool in fire-engineering provides possibility to design specific fire scenarios and investigate fire spread, smoke movement or evacuation of occupants from buildings. Development of emerging technologies and software provides higher possibility to apply these models with interactions of augmented and virtual reality. Augmented reality and virtual reality expand effectivity of training and preparedness of first (fire wardens) and second (firefighters) responders. Limitations such as financial demands, scale and scenarios of practical training of first and second responders are much lower than in virtual reality. These technologies provide great opportunities in preparedness to crisis in a safety way with significantly limited budget. Some of these systems are already developed and applied in safety and security area e.g. XVR (firefighting, medical service).

scholarly journals Fire retardant for expansion and linear joints in buildings and tunnels

2018 ◽  
Vol 239 ◽  
pp. 05010
Author(s):  
Vasiliy Prusakov ◽  
Marina Gravit ◽  
Yana Simonenko ◽  
Anna Minnullina ◽  
Alexandra Artyukhina
Keyword(s):  
Fire Safety ◽  
Fire Retardant ◽  
Fire Prevention ◽  
Complex Decision

The review of fire-prevention barriers of deformation seams both foreign, and domestic manufacturers is provided in article. It is shown that the fire-prevention barriers which are specially developed for application in deformation seams, guaranteed working at compression, stretching and shift of a seam are applied to protection of deformation seams at the fire it is established that production of innovative fireproof materials is one of the main objectives of fire safety, it and ways of consecutive transformation of the idea to the goods passing stages of researches, design developments, productions and realization in projects of civil and industrial function of buildings. The prime purpose – to pick up the complex decision providing the maximum satisfaction of requirements when performing fireproof works on protection of a deformation seam at impact of the fire.

Teaching Fire Safety Education: Strategies to Support Safety

2017 ◽  
pp. 71-82
Author(s):  
David J. Kolko ◽  
Eric M. Vernberg
Keyword(s):  
Fire Safety ◽  
Safety Information ◽  
Fire Prevention ◽  
Teaching Skills ◽  
Safety Education ◽  
Important Addition ◽  
The Subject ◽  
Practical Information ◽  
Safety Knowledge ◽  
In Fire

This chapter continues the subject of fire safety education with practical information on the dangers of fires and ways to avoid it that includes teaching skills to help the child reduce exposure to fire and prevent injuries or other damages by responding effectively to it. It provides additional materials for families to support children in fire prevention, including a home project. Sections include emphasis on fire as a tool, not a toy; reporting a fire, extinguishers, evacuation, and the stop-drop-roll technique. Also discussed is how to review the child’s fire-safety knowledge and provide suggestions to apply what has been learned. An important addition addresses how to prepare a babysitter or other caregiver with all necessary fire safety information.

scholarly journals Policing for security of Fire Safety in Ural (1862–1917)

2021 ◽  
Vol 21 (2) ◽  
pp. 142-148
Author(s):  
Sergey M. Ryazanov ◽  
Keyword(s):  
Fire Safety ◽  
Police Officers ◽  
General Structure ◽  
Fire Prevention ◽  
Important Place ◽  
Archival Documents ◽  
Prevention Activities ◽  
In Fire

The article examines the policing to prevent and extinguish fires in the second half of the 19th – early 20th centuries in the Ural provinces. Based on archival documents, materials from periodicals and regulatory legal acts, it demonstrates the place of control over fire safety in the general structure of administrative and supervisory functions of the Ural police. The conclusions is made that the institute of country police officers occupied an important place in fire prevention activities, and the police assumed leadership functions in the process of extinguishing fires.

scholarly journals Organizational and managerial issues of improving the fire safety of the protected objects

2021 ◽  
pp. 25-28
Author(s):  
Arina S. Netrebina ◽  
Valeriya A. Bokova ◽  
Dmitriy V. Totskiy
Keyword(s):  
Artificial Intelligence ◽  
Fire Protection ◽  
Fire Safety ◽  
Safety Management ◽  
Scientific Research ◽  
Legal Regulation ◽  
Fire Prevention ◽  
Basic Information ◽  
Problem Statement ◽  
Protection Systems

Introduction. The paper considers the issues of modernization in the field of fire safety. It is noted that insufficient attention is paid to the tasks of fire safety management of the protected objects, and this negatively affects the overall level of security in the regions. The most relevant and effective method of improving the fire safety of the protected objects is the active introduction of robotics and artificial intelligence. Problem Statement. The objectives of this study are to develop proposals to improve fire prevention and fire protection systems, as well as to create a set of measures aimed at ensuring fire safety. Theoretical Part. The works of scientists on the topic of this study are used as basic information. The system of fire safety organization, legal regulation and state measures in the field of fire safety have been studied. Conclusions. The results of the study can be used in practice to ensure the fire safety of the protected objects, as well as for further scientific research.

Deep Learning

2021 ◽  
pp. 171-196
Author(s):  
Semra Erpolat Taşabat ◽  
Olgun Aydin
Keyword(s):  
Artificial Intelligence ◽  
Machine Learning ◽  
Neural Networks ◽  
Deep Learning ◽  
Deep Neural Networks ◽  
Smart Cities ◽  
Key Technology ◽  
Smart Systems ◽  
Advantages And Disadvantages

Deep learning (DL) is a rising star of machine learning (ML) and artificial intelligence (AI) domains. Until 2006, many researchers had attempted to build deep neural networks (DNN), but most of them failed. In 2006, it was proven that deep neural networks are one of the most crucial inventions for the 21st century. Nowadays, DNN are being used as a key technology for many different domains: self-driven vehicles, smart cities, security, automated machines. In this chapter, brief information about DL theory is given, advantages and disadvantages of deep learning are discussed, most used types of DNN are mentioned, popular DL architectures and frameworks are glanced and aimed to build smart systems for the finance and real estate domains. Finally, a case study about image recognition using transfer learning is developed.

scholarly journals ARTIFICIAL INTELLIGENCE ON THE IDENTIFICATION OF DIABETES-RELATED OSTEOMETABOLIC DISORDERS

2021 ◽  
Vol 06 (01) ◽  
pp. 73-74
Author(s):  
Sain Safarova Sain Safarova
Keyword(s):  
Artificial Intelligence ◽  
Diabetes Mellitus ◽  
Neural Networks ◽  
Artificial Neural Networks ◽  
Clinical Practice ◽  
Premature Death ◽  
Diabetic Patients ◽  
New Therapeutic Approaches ◽  
Patients With Diabetes ◽  
Artificial Neural

Introduction: Complications of diabetes mellitus (DM) are of great medical and social importance, as they cause severe disability and premature death of patients with diabetes mellitus. Bone remodeling disorders occurring in diabetes increase the risk of fractures and move the problem of diabetic osteopathy beyond the narrow specialty, making it the subject of extensive scientific research [1-3]. However, osteopathy remains an underestimated complication and is not considered in most diabetes guidelines. The fact that diabetic osteopathy is often asymptomatic leads to the fact that diabetic patients turn their attention to this pathology late and turn to a specialist, as a rule, already having a high degree of progression of this complication. One of the important issues is the timely detection and prediction of bone changes in diabetes mellitus. The introduction of artificial intelligence technologies (AIT) into clinical practice is one of the main trends in world medicine [4]. AIT and Artificial Neural Networks (ANN) can fundamentally change the criteria for diagnosis and prognosis, which will contribute to the development of new therapeutic approaches, improve the efficiency of medical care and reduce costs [5]. The prospects for using ANN can potentially provide almost limitless technical possibilities. Considering the possibilities of using these technologies in clinical practice, we came to the conclusion that the development and implementation of forecasting systems based on the construction of a model of an intelligent decision support system based on the apparatus of artificial neural networks is able to analyze clinical and laboratory indicators of patients with diabetes mellitus (DM) in order to predict the values of qualitative and quantitative indicators assessing the state of bone tissue.

scholarly journals Training Convolutional Neural Networks to Score Pneumonia in Slaughtered Pigs

Animals ◽  
2021 ◽  
Vol 11 (11) ◽  
pp. 3290
Author(s):  
Lorenzo Bonicelli ◽  
Abigail Rose Trachtman ◽  
Alfonso Rosamilia ◽  
Gaetano Liuzzo ◽  
Jasmine Hattab ◽  
...  
Keyword(s):  
Artificial Intelligence ◽  
Neural Networks ◽  
Convolutional Neural Networks ◽  
High Throughput ◽  
Microbial Contamination ◽  
Farm Animals ◽  
Food Hygiene ◽  
Enzootic Pneumonia ◽  
Repetitive Tasks ◽  
Slaughtered Pigs

The slaughterhouse can act as a valid checkpoint to estimate the prevalence and the economic impact of diseases in farm animals. At present, scoring lesions is a challenging and time-consuming activity, which is carried out by veterinarians serving the slaughter chain. Over recent years, artificial intelligence(AI) has gained traction in many fields of research, including livestock production. In particular, AI-based methods appear able to solve highly repetitive tasks and to consistently analyze large amounts of data, such as those collected by veterinarians during postmortem inspection in high-throughput slaughterhouses. The present study aims to develop an AI-based method capable of recognizing and quantifying enzootic pneumonia-like lesions on digital images captured from slaughtered pigs under routine abattoir conditions. Overall, the data indicate that the AI-based method proposed herein could properly identify and score enzootic pneumonia-like lesions without interfering with the slaughter chain routine. According to European legislation, the application of such a method avoids the handling of carcasses and organs, decreasing the risk of microbial contamination, and could provide further alternatives in the field of food hygiene.

Advances in fire retardant materials

2008 ◽  
Author(s):  
A. R. Horrocks ◽  
D. Price
Keyword(s):  
Fire Retardant ◽  
In Fire
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