Internet of things for disaster management: state-of-the-art and prospects

Disastrous events are cordially involved with the momentum of nature. As such mishaps have been showing off own mastery, situations have gone beyond the control of human resistive mechanisms far ago. Fortunately, several technologies are in service to gain affirmative knowledge and analysis of a disaster's occurrence. Recently, Internet of Things (IoT) paradigm has opened a promising door toward catering of multitude problems related to agriculture, industry, security, and medicine due to its attractive features, such as heterogeneity, interoperability, light-weight, and flexibility. This paper surveys existing approaches to encounter the relevant issues with disasters, such as early warning, notification, data analytics, knowledge aggregation, remote monitoring, real-time analytics, and victim localization. Simultaneous interventions with IoT are also given utmost importance while presenting these facts. A comprehensive discussion on the state-of-the-art scenarios to handle disastrous events is presented. Furthermore, IoT-supported protocols and market-ready deployable products are summarized to address these issues. Finally, this survey highlights open challenges and research trends in IoT-enabled disaster management systems. © 2013 IEEE

LoRaWAN Network for Fire Monitoring in Rural Environments

The number of forest fires that occurred in recent years in different parts of the world is causing increased concern in the population, as the consequences of these fires expand beyond the destruction of the ecosystem. However, with the proliferation of the Internet of Things (IoT) industry, solutions for early fire detection should be developed. The assessment of the fire risk of an area and the communication of this fact to the population could reduce the number of fires originated by accident or due to the carelessness of the users. This paper presents a low-cost network based on Long Range (LoRa) technology to autonomously evaluate the level of fire risk and the presence of a forest fire in rural areas. The system is comprised of several LoRa nodes with sensors to measure the temperature, relative humidity, wind speed and CO2 of the environment. The data from the nodes is stored and processed in a The Things Network (TTN) server that sends the data to a website for the graphic visualization of the collected data. The system is tested in a real environment and, the results show that it is possible to cover a circular area of a radius of 4 km with a single gateway.This work was partially supported by the “Ministerio de Ciencia, Innovación y Universidades” through the “Ayudas para la adquisición de equipamiento científico-técnico, Subprograma estatal de infraestructuras de investigación y equipamiento científico-técnico (plan Estatal I+D+i 2017-2020)” (project EQC2018-004988-P), by Universidad de Granada through the “Programa de Proyectos de Investigación Precompetitivos para Jóvenes Investigadores. Modalidad A jóvenes Doctores” of “Plan Propio de Investigación y Transferencia 2019” (PPJIA2019.10), by the Campus de Excelencia Internacional Global del Mar (CEI·Mar) through the “Ayudas Proyectos Jóvenes Investigadores CEI·Mar 2019”, (Project CEIJ-020), by the European Union through the ERANETMED (Euromediterranean Cooperation through ERANET joint activities and beyond) (Project ERANETMED3-227 SMARTWATIR)

Development of a long range wireless sensor platform

Wireless Sensor Networks have emerged as an exciting field in recent years. There have been numerous studies on how to improve and standardise different aspects of wireless sensor networks. This paper aims to develop a wireless sensor network suitable for environmental monitoring applications. More specifically this paper aims to address the limited communication range of the existing wireless sensor technology. In order to achieve the desired objectives, we have initially developed a hardware platform and then integrated the hardware with a long range RF radio module to achieve the goals. The system is further enhanced with mesh networking capabilities to increase the communication range and overall reliability of the network. The developed wireless sensor network is composed of sensors, microcontroller, RF radio module, antenna and expansion connectors for additional sensors and peripheral devices. The developed wireless sensor network has been rigorously tested under three different scenarios to ensure the correct operation of the mesh network, communication range and effect of environmental obstacles such as vegetation and trees. The developed wireless sensor network has been proven to be a suitable platform for environmental monitoring applications and the modular design has made it very easy to optimise it for different applications

Low-Power Pıc-Based Sensor Node Devıce Desıgn And Theoretıcal Analysıs Of Energy Consumptıon In Wıreless Sensor Networks

Teknolojinin ilerlemesi, daha enerji verimli ve daha ucuz elektronik bileşenlerinin daha küçük üretilmesini sağlamıştır. Bu nedenle, daha önce mevcut birçok bilgisayar ve elektronik bilim-mühendislik fikirleri uygulanabilir hale gelmiştir. Bunlardan birisi de kablosuz sensör ağları teknolojisidir. Kablosuz algılayıcı ağlar, düşük enerji tüketimi ve gerekli teknik gereksinimlerin gerçekleşmesi ile uygulanabilir hale gelmiştir. Ayrıca, Kablosuz algılayıcı ağlarının tasarımında iletişim algoritmaları, enerji tasarruf protokolleri ve yenilenebilir enerji teknolojileri gibi diğer bilimsel çalışmalar zorunlu hale gelmiştir. Bu tez, mikroelektronik sistemler, kablosuz iletişim ve dijital elektronik teknolojisinin ilerlemesiyle uygulanabilir hale gelmiş sensör ağları teknolojisini kapsamaktadır. Birincisi, algılama görevleri ve potansiyel algılayıcı ağ uygulamaları araştırılmış ve algılayıcı ağlarının tasarımını etkileyen faktörlerin gözden geçirilmesi sağlanmıştır. Ardından sensör ağları için iletişim mimarisi ana hatlarıyla belirtilmiştir. Ayrıca, tek bir düğümün WLAN ile iletişim kurabilmesi için yeni donanım mimarisi tasarlanmış ve düğümlerde yenilenebilir enerji kaynakları kullanılmıştır. Bu tezde WSN, analitik bilim ve uygulamalı bilim açısından incelenmiştir. Düşük enerji tüketimi ve iletişim protokolleri arasındaki ilişki değerlendirilmiş ve bilimsel sonuçlara varılmıştır. Teorik analizler bilimsel uygulamalarla desteklenmiştir. Çalışmalar, düşük enerji ve maksimum verimlilik prensibinin gerçekleştirilmesine dayalı kablosuz sensör ağları üzerinde gerçekleştirilmiştir. Kablosuz sensör ağlari sistemi tasarlandıktan sonra; sensör düğümlerinin enerji tüketimi ve kablosuz ağdaki davranışları test ve analiz edilmiştir. Düşük enerji tüketimi ile sensör düğümleri arasındaki ilişki detaylı olarak değerlendirilmiştir. PIC Tabanlı mikro denetleyiciler sensör düğümlerinin tasarımında kullanılmış ve çok düşük maliyetli tasarım için ultra düşük güçte, nanoWatt teknolojisi ile desteklenen sensör düğümleri tasarlanmıştır. İşleme birimi, bellek birimi ve kablosuz iletişim birimi sensör viii düğümlerine entegre edilmiştir. Tasarlanan sensör düğümünün işletim sistemi PIC C dili ile yazılmıştır ve PIC işletim sistemi nem, sıcaklık, ışığa duyarlılık ve duman sensörü gibi farklı özelliklerin ölçülmesine izin vermiştir. Sensörlerden gelen verilerin merkezi bir konumdan kaydedilmesi ve izlenebilmesi için, C# programlama dili ile bilgisayar yazılımı geliştirilmiştir. Gelişmiş algılayıcı düğümler tarafından alınan kararların uygulanması için yazılım algoritması ve donanım modüllerini içeren karar verme sistemi tasarlanmıştır. Gelişmiş PIC Tabanlı sensör düğümleri, enerji üretimi ve enerji tasarrufu için, güneş enerjisi paneli, şarj edilebilir pil ve süper kapasitör gibi yenilenebilir enerji kaynakları ile benzersiz bir PIC Kontrollü voltaj birimi ile desteklenmiştir. Geliştirilmiş kablosuz sensör ağları sistemi, endüstri uygulamaları, akıllı fabrikalar ve akıllı evler gibi günlük hayat uygulamaları için de kullanılabilecektir. Kablosuz algılayıcı ağlar geniş bir aralıkta kullanılmak üzere tasarlanmıştır. Tezin sonuçları, özellikle yenilenebilir enerji kaynakları ile WSN'nin geliştirilmesine yardımcı olmayı amaçlamaktadır

Reliable Lifespan Evaluation of a Remote Environment Monitoring System Based on Wireless Sensor Networks and Global System for Mobile Communications

The use of wireless sensor networks (WSN) for monitoring physical and chemical variables in large areas allows density and frequency measurements which have been unavailable to date in classical measurement systems. To fully take advantage of this technology in a particular application, besides an accurate design and selection of all the components involved in its operation, it is essential to dispose of reliable lifetime estimation prior to deployment. This paper presents an experimental approach to determine the actual lifetime of such battery-operated systems, making use of a custom WSN architecture, and for different batteries technologies. To render a reliable evaluation, the energy consumption of the sensor nodes under their different operation modes, in correlation with the battery characteristics and the voltage regulation system, is jointly considered. The result is a complete and practical lifetime model, whose appropriate performance has been validated in a real deployment scenario

Federated Sensor Network architectural design for the Internet of Things (IoT)

An information technology that can combine the physical world and virtual world is desired. The Internet of Things (IoT) is a concept system that uses Radio Frequency Identification (RFID), WSN and barcode scanners to sense and to detect physical objects and events. This information is shared with people on the Internet. With the announcement of the Smarter Planet concept by IBM, the problem of how to share this data was raised. However, the original design of WSN aims to provide environment monitoring and control within a small scale local network. It cannot meet the demands of the IoT because there is a lack of multi-connection functionality with other WSNs and upper level applications. As various standards of WSNs provide information for different purposes, a hybrid system that gives a complete answer by combining all of them could be promising for future IoT applications. This thesis is on the subject of `Federated Sensor Network' design and architectural development for the Internet of Things. A Federated Sensor Network (FSN) is a system that integrates WSNs and the Internet. Currently, methods of integrating WSNs and the Internet can follow one of three main directions: a Front-End Proxy solution, a Gateway solution or a TCP/IP Overlay solution. Architectures based on the ideas from all three directions are presented in this thesis; this forms a comprehensive body of research on possible Federated Sensor Network architecture designs. In addition, a fully compatible technology for the sensor network application, namely the Sensor Model Language (SensorML), has been reviewed and embedded into our FSN systems. The IoT as a new concept is also comprehensively described and the major technical issues discussed. Finally, a case study of the IoT in logistic management for emergency response is given. Proposed FSN architectures based on the Gateway solution are demonstrated through hardware implementation and lab tests. A demonstration of the 6LoWPAN enabled federated sensor network based on the TCP/IP Overlay solution presents a good result for the iNET localization and tracking project. All the tests of the designs have verified feasibility and achieve the target of the IoT concept

IoT and Sensor Networks in Industry and Society

The exponential progress of Information and Communication Technology (ICT) is one of the main elements that fueled the acceleration of the globalization pace. Internet of Things (IoT), Artificial Intelligence (AI) and big data analytics are some of the key players of the digital transformation that is affecting every aspect of human's daily life, from environmental monitoring to healthcare systems, from production processes to social interactions. In less than 20 years, people's everyday life has been revolutionized, and concepts such as Smart Home, Smart Grid and Smart City have become familiar also to non-technical users. The integration of embedded systems, ubiquitous Internet access, and Machine-to-Machine (M2M) communications have paved the way for paradigms such as IoT and Cyber Physical Systems (CPS) to be also introduced in high-requirement environments such as those related to industrial processes, under the forms of Industrial Internet of Things (IIoT or I2oT) and Cyber-Physical Production Systems (CPPS). As a consequence, in 2011 the German High-Tech Strategy 2020 Action Plan for Germany first envisioned the concept of Industry 4.0, which is rapidly reshaping traditional industrial processes. The term refers to the promise to be the fourth industrial revolution. Indeed, the first industrial revolution was triggered by water and steam power. Electricity and assembly lines enabled mass production in the second industrial revolution. In the third industrial revolution, the introduction of control automation and Programmable Logic Controllers (PLCs) gave a boost to factory production. As opposed to the previous revolutions, Industry 4.0 takes advantage of Internet access, M2M communications, and deep learning not only to improve production efficiency but also to enable the so-called mass customization, i.e. the mass production of personalized products by means of modularized product design and flexible processes. Less than five years later, in January 2016, the Japanese 5th Science and Technology Basic Plan took a further step by introducing the concept of Super Smart Society or Society 5.0. According to this vision, in the upcoming future, scientific and technological innovation will guide our society into the next social revolution after the hunter-gatherer, agrarian, industrial, and information eras, which respectively represented the previous social revolutions. Society 5.0 is a human-centered society that fosters the simultaneous achievement of economic, environmental and social objectives, to ensure a high quality of life to all citizens. This information-enabled revolution aims to tackle today’s major challenges such as an ageing population, social inequalities, depopulation and constraints related to energy and the environment. Accordingly, the citizens will be experiencing impressive transformations into every aspect of their daily lives. This book offers an insight into the key technologies that are going to shape the future of industry and society. It is subdivided into five parts: the I Part presents a horizontal view of the main enabling technologies, whereas the II-V Parts offer a vertical perspective on four different environments. The I Part, dedicated to IoT and Sensor Network architectures, encompasses three Chapters. In Chapter 1, Peruzzi and Pozzebon analyse the literature on the subject of energy harvesting solutions for IoT monitoring systems and architectures based on Low-Power Wireless Area Networks (LPWAN). The Chapter does not limit the discussion to Long Range Wise Area Network (LoRaWAN), SigFox and Narrowband-IoT (NB-IoT) communication protocols, but it also includes other relevant solutions such as DASH7 and Long Term Evolution MAchine Type Communication (LTE-M). In Chapter 2, Hussein et al. discuss the development of an Internet of Things message protocol that supports multi-topic messaging. The Chapter further presents the implementation of a platform, which integrates the proposed communication protocol, based on Real Time Operating System. In Chapter 3, Li et al. investigate the heterogeneous task scheduling problem for data-intensive scenarios, to reduce the global task execution time, and consequently reducing data centers' energy consumption. The proposed approach aims to maximize the efficiency by comparing the cost between remote task execution and data migration. The II Part is dedicated to Industry 4.0, and includes two Chapters. In Chapter 4, Grecuccio et al. propose a solution to integrate IoT devices by leveraging a blockchain-enabled gateway based on Ethereum, so that they do not need to rely on centralized intermediaries and third-party services. As it is better explained in the paper, where the performance is evaluated in a food-chain traceability application, this solution is particularly beneficial in Industry 4.0 domains. Chapter 5, by De Fazio et al., addresses the issue of safety in workplaces by presenting a smart garment that integrates several low-power sensors to monitor environmental and biophysical parameters. This enables the detection of dangerous situations, so as to prevent or at least reduce the consequences of workers accidents. The III Part is made of two Chapters based on the topic of Smart Buildings. In Chapter 6, Petroșanu et al. review the literature about recent developments in the smart building sector, related to the use of supervised and unsupervised machine learning models of sensory data. The Chapter poses particular attention on enhanced sensing, energy efficiency, and optimal building management. In Chapter 7, Oh examines how much the education of prosumers about their energy consumption habits affects power consumption reduction and encourages energy conservation, sustainable living, and behavioral change, in residential environments. In this Chapter, energy consumption monitoring is made possible thanks to the use of smart plugs. Smart Transport is the subject of the IV Part, including three Chapters. In Chapter 8, Roveri et al. propose an approach that leverages the small world theory to control swarms of vehicles connected through Vehicle-to-Vehicle (V2V) communication protocols. Indeed, considering a queue dominated by short-range car-following dynamics, the Chapter demonstrates that safety and security are increased by the introduction of a few selected random long-range communications. In Chapter 9, Nitti et al. present a real time system to observe and analyze public transport passengers' mobility by tracking them throughout their journey on public transport vehicles. The system is based on the detection of the active Wi-Fi interfaces, through the analysis of Wi-Fi probe requests. In Chapter 10, Miler et al. discuss the development of a tool for the analysis and comparison of efficiency indicated by the integrated IT systems in the operational activities undertaken by Road Transport Enterprises (RTEs). The authors of this Chapter further provide a holistic evaluation of efficiency of telematics systems in RTE operational management. The book ends with the two Chapters of the V Part on Smart Environmental Monitoring. In Chapter 11, He et al. propose a Sea Surface Temperature Prediction (SSTP) model based on time-series similarity measure, multiple pattern learning and parameter optimization. In this strategy, the optimal parameters are determined by means of an improved Particle Swarm Optimization method. In Chapter 12, Tsipis et al. present a low-cost, WSN-based IoT system that seamlessly embeds a three-layered cloud/fog computing architecture, suitable for facilitating smart agricultural applications, especially those related to wildfire monitoring. We wish to thank all the authors that contributed to this book for their efforts. We express our gratitude to all reviewers for the volunteering support and precious feedback during the review process. We hope that this book provides valuable information and spurs meaningful discussion among researchers, engineers, businesspeople, and other experts about the role of new technologies into industry and society