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An Overview of the Internet of Things Technologies Focusing on Disaster Response

Reinaldo Padilha Fran да

Communications Department (DECOM) - Faculty of Electrical and Computer Engineering (FEEC),

State University of Campinas (Unicamp)

Ana Carolina Borges Monteiro

Communications Department (DECOM) - Faculty of Electrical and Computer Engineering (FEEC),

State University of Campinas (Unicamp)

Rangel Arthur

Department of Telecommunications Engineering - Faculty of Technology (FT), State University of Campinas (Unicamp)

Yuzo lano

Communications Department (DECOM) - Faculty of Electrical and Computer Engineering (FEEC),

State University of Campinas (Unicamp)

Introduction

The big change that the Internet of Things (IoT) brings to people’s lives is beyond the ease of preparing a coffee, scheduling a hot bath or saving on electricity, giving objects connectivity, and making room for intelligent commands on countless everyday tasks. But not only that, IoT means increasing work productivity, improving urban mobility and public and private safety conditions, streamlining processes, as these technologies range from sensors to algorithms capable of reading and analyzing the information captured, providing reliable data for risk management and disasters [1].

There are several types of natural phenomena in which they configure normal events generated by movement, be it water, earth, air, space, which interfere in the vital structure of society; however, these disasters are usually not responsible, often caused by the reaction of nature, since they are natural phenomena and represent the change of cycle on Earth, and nowadays, these occurrences have increased significantly, leading to further studies regarding statistics and research on the environment [2].

Although many disasters have occurred because the planet Earth is suffering more and more, with global warming and the greenhouse effect, it leads to an increase in natural disasters, caused by the imbalance of nature, which generate several impacts on society. There are also environmental disasters caused by humans, which are responsible for causing damage to the environment, the damage that does not only affect plants and animals but also causing a negative impact on soil, water, and air. Since due to the evolution of society, the human being when carrying out an activity must be aware that it can have a negative impact on the environment, which must take necessary accident prevention measures; however, the problem occurs when these measures fail or are not considered important [3].

In turn, with regard to nature and natural disasters, they have an effect on helping to renew and maintain ecosystems, supply natural water sources, and create relief, among others. Some common examples are storms, earthquakes, and tsunamis, hurricanes, cyclones and typhoons, floods, landslides, endemics, epidemics, pandemics, erosion, volcanic eruption, tropical cyclone, fires (when not caused by human action), flood, fall of a meteor, volcanic eruptions, among others. However, as much as man is able to evolve, accumulate wealth, develop technologies, build cities, nothing is capable of overcoming nature. Thus, Natural Disasters represent a set of phenomena that are part of terrestrial geodynamics; therefore, the nature of the planet, which can bring catastrophic consequences for people and as much as the technology in the area, is advanced; many natural disasters can be predictable [3,4].

Natural disasters are a major problem for industries, and until recently, there was no way to deal with them. Backups to ensure access to data, building secure structures to install business machinery, and purchasing products such as insurance were all that could be done to reduce risks, now with the use of drones, it is possible to capture very high-resolution images, adding the use of computer vision and artificial intelligence (AI), which can help in identifying structural faults with superhuman precision [5].

Technology is making an impact and lets us know about risks and disasters long before they can happen, which is a competitive advantage, with the help of devices that work under less than optimal conditions, where so there is little or very little wireless connection and energy sources used to screen and accurately detect the onset of tectonic activities, for example. It is also with IoT technology that we can now accurately monitor earthmoving on sloping hills and slopes. Rainfall data collection platforms and humidity sensors gather information on the amount of accumulated rainfall and water in the soil. Equipment transfers data over the Internet directly to control centers, where decisions are made to mitigate the impacts of natural disasters [2,6].

AI is associated with intelligent objects to make disaster prevention a much more accurate task, where new technologies are being used in organizations so that they can identify situations and act preventively, preventing the loss of assets and resources. Using robots, sensors, and drones is a way to better coordinate actions in hazardous areas and ensure that service providers can understand the situations in which they are placed faster. The fire department, for example, can process heat areas in a building with computer vision and intelligent software to map out more efficient routes and reach victims [7].

This chapter is motivated to provide a scientific contribution related to an overview and current discussion about the essentiality of IoT technologies focusing on disaster response and management, addressing their key points and their importance, which are a complex and heterogeneous concept but which through technology’s potential showing integrations and successful relationship.

This research aims to show the importance of IoT technologies with a focus on disaster response and management, having as specific objectives to discuss and analyze its essentiality in a modern context exemplifying how certain natural disasters could be mitigated or avoided through their applicability. Contributing to enhancing the view of the novice reader about this technology, in this sense, the authors of this chapter hope that this work will be useful to the novice reader by learning the pillars and technology’s potential and stimulating their interest in research and approaches to advanced thematic.

Therefore, this chapter aims to provide an updated overview of IoT technologies as well as focusing on disaster response and management, showing its relationship and integrations approaching, with a concise bibliographic background, categorizing, and synthesizing the potential of both technologies.

Artificial Intelligence

AI is a branch of technology that aims to simulate the capacity of human thinking, that is, it makes the machines are programmed with algorithms that learn and modify according to the analyzed data and, from that, manage to “think” logically. AI is also known as machine learning, since based on it, devices are able to adapt according to the data they receive, carrying out a process that diverges directly from the system of common computers which always follow the same logical commands [8].

Through AI, cognitive computing and deep learning algorithms collect data, analyze, learn, and make information available for decision-making, making recommendations for more efficient use, and this advance has enabled already routine applications, such as word processing, facial, and voice recognition [9].

With regard to natural language processing, it is an arm of AI that is dedicated to the translation of human languages for the machine, going beyond the simple transcription of voice by words, this area studies details of human dialog, such as the double meaning in words, the tone of voice, among other aspects that involve the diversity of natural language. Considering that this linguistic processing is present in the analysis of large volumes of voice data, in which virtual intelligence machines learn to identify accents, expressions, vocabulary patterns, with double meaning, tones, and other properties of speechflO],

Big Data is a resource focused on describing the huge amount of data that are generated by current technologies, taking into account that most of the time, these data are unstructured, which at first glance does not make sense. Besides derived from the importance of data for obtaining information, collecting references about users’ routines and data, extracting useful knowledge without AI can be time-consuming in some cases, which would be counterproductive, in this sense through the internet which brought the ease of collecting this data, and together with resources such as processing in Cloud Computing and AI, since Big Data is a computing model focused on processing and storing information in high volume, the solution that stores and processes data automatically and in practically real time; being allied with AI with a primary focus on data and image processing, with the aim of making the device or technology more intelligent and capable of reproducing human skills; that is, there is an intersection between AI and Big Data in relation to the AI algorithms that run in the Big Data environment and establish an effective communication between these two fields, which at the same time are different and complementary, that is, AI would be as a powerful digital human brain, which is able to store and process the information it receives from human experience such as reading, travel, crisis situations, among others, and based on this processing, it can suggest solutions on its own [II].

Today, the main advantage of using AI to capture information in Big Data is to be able to identify insights and patterns faster than human analysis, reducing the time spent on this procedure, being crucial in guaranteeing competitive advantages to any type of analysis of scenarios and contexts [12,13].

 
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