Pattern Recognition Techniques for the Identification of Activities of Daily Living Using a Mobile Device Accelerometer

The application of pattern recognition techniques to data collected from accelerometers available in off-the-shelf devices, such as smartphones, allows for the automatic recognition of activities of daily living (ADLs). This data can be used later to create systems that monitor the behaviors of their users. The main contribution of this paper is to use artificial neural networks (ANN) for the recognition of ADLs with the data acquired from the sensors available in mobile devices. Firstly, before ANN training, the mobile device is used for data collection. After training, mobile devices are used to apply an ANN previously trained for the ADLs’ identification on a less restrictive computational platform. The motivation is to verify whether the overfitting problem can be solved using only the accelerometer data, which also requires less computational resources and reduces the energy expenditure of the mobile device when compared with the use of multiple sensors. This paper presents a method based on ANN for the recognition of a defined set of ADLs. It provides a comparative study of different implementations of ANN to choose the most appropriate method for ADLs identification. The results show the accuracy of 85.89% using deep neural networks (DNN).This work is funded by FCT/MCTES through national funds, and when applicable, co-funded EU funds under the project UIDB/EEA/50008/2020 (Este trabalho é financiado pela FCT/MCTES através de fundos nacionais e quando aplicável cofinanciado por fundos comunitários no âmbito do projeto UIDB/EEA/50008/2020)

A Consolidated Review of Path Planning and Optimization Techniques: Technical Perspectives and Future Directions

In this paper, a review on the three most important communication techniques (ground, aerial, and underwater vehicles) has been presented that throws light on trajectory planning, its optimization, and various issues in a summarized way. This kind of extensive research is not often seen in the literature, so an effort has been made for readers interested in path planning to fill the gap. Moreover, optimization techniques suitable for implementing ground, aerial, and underwater vehicles are also a part of this review. This paper covers the numerical, bio-inspired techniques and their hybridization with each other for each of the dimensions mentioned. The paper provides a consolidated platform, where plenty of available research on-ground autonomous vehicle and their trajectory optimization with the extension for aerial and underwater vehicles are documented

Survey of Transportation of Adaptive Multimedia Streaming service in Internet

[DE] World Wide Web is the greatest boon towards the technological advancement of modern era. Using the benefits of Internet globally, anywhere and anytime, users can avail the benefits of accessing live and on demand video services. The streaming media systems such as YouTube, Netflix, and Apple Music are reining the multimedia world with frequent popularity among users. A key concern of quality perceived for video streaming applications over Internet is the Quality of Experience (QoE) that users go through. Due to changing network conditions, bit rate and initial delay and the multimedia file freezes or provide poor video quality to the end users, researchers across industry and academia are explored HTTP Adaptive Streaming (HAS), which split the video content into multiple segments and offer the clients at varying qualities. The video player at the client side plays a vital role in buffer management and choosing the appropriate bit rate for each such segment of video to be transmitted. A higher bit rate transmitted video pauses in between whereas, a lower bit rate video lacks in quality, requiring a tradeoff between them. The need of the hour was to adaptively varying the bit rate and video quality to match the transmission media conditions. Further, The main aim of this paper is to give an overview on the state of the art HAS techniques across multimedia and networking domains. A detailed survey was conducted to analyze challenges and solutions in adaptive streaming algorithms, QoE, network protocols, buffering and etc. It also focuses on various challenges on QoE influence factors in a fluctuating network condition, which are often ignored in present HAS methodologies. Furthermore, this survey will enable network and multimedia researchers a fair amount of understanding about the latest happenings of adaptive streaming and the necessary improvements that can be incorporated in future developments.Abdullah, MTA.; Lloret, J.; Canovas Solbes, A.; García-García, L. (2017). Survey of Transportation of Adaptive Multimedia Streaming service in Internet. Network Protocols and Algorithms. 9(1-2):85-125. doi:10.5296/npa.v9i1-2.12412S8512591-

Sequential Monte Carlo Localization Methods in Mobile Wireless Sensor Networks: A Review

The advancement of digital technology has increased the deployment of wireless sensor networks (WSNs) in our daily life. However, locating sensor nodes is a challenging task in WSNs. Sensing data without an accurate location is worthless, especially in critical applications. The pioneering technique in range-free localization schemes is a sequential Monte Carlo (SMC) method, which utilizes network connectivity to estimate sensor location without additional hardware. This study presents a comprehensive survey of stateof-the-art SMC localization schemes. We present the schemes as a thematic taxonomy of localization operation in SMC. Moreover, the critical characteristics of each existing scheme are analyzed to identify its advantages and disadvantages. The similarities and differences of each scheme are investigated on the basis of significant parameters, namely, localization accuracy, computational cost, communication cost, and number of samples. We discuss the challenges and direction of the future research work for each parameter

Advanced Topics in Systems Safety and Security

This book presents valuable research results in the challenging field of systems (cyber)security. It is a reprint of the Information (MDPI, Basel) - Special Issue (SI) on Advanced Topics in Systems Safety and Security. The competitive review process of MDPI journals guarantees the quality of the presented concepts and results. The SI comprises high-quality papers focused on cutting-edge research topics in cybersecurity of computer networks and industrial control systems. The contributions presented in this book are mainly the extended versions of selected papers presented at the 7th and the 8th editions of the International Workshop on Systems Safety and Security—IWSSS. These two editions took place in Romania in 2019 and respectively in 2020. In addition to the selected papers from IWSSS, the special issue includes other valuable and relevant contributions. The papers included in this reprint discuss various subjects ranging from cyberattack or criminal activities detection, evaluation of the attacker skills, modeling of the cyber-attacks, and mobile application security evaluation. Given this diversity of topics and the scientific level of papers, we consider this book a valuable reference for researchers in the security and safety of systems

Sulautettu ohjelmistototeutus reaaliaikaiseen paikannusjärjestelmään

Asset tracking often necessitates wireless, radio-frequency identification (RFID). In practice, situations often arise where plain inventory operations are not sufficient, and methods to estimate movement trajectory are needed for making reliable observations, classification and report generation. In this thesis, an embedded software application for an industrial, resource-constrained off-the-shelf RFID reader device in the UHF frequency range is designed and implemented. The software is used to configure the reader and its air-interface operations, accumulate read reports and generate events to be reported over network connections. Integrating location estimation methods to the application facilitates the possibility to make deploying middleware RFID solutions more streamlined and robust while reducing network bandwidth requirements. The result of this thesis is a functional embedded software application running on top of an embedded Linux distribution on an ARM processor. The reader software is used commercially in industrial and logistics applications. Non-linear state estimation features are applied, and their performance is evaluated in empirical experiments.Tavaroiden seuranta edellyttää usein langatonta radiotaajuustunnistustekniikkaa (RFID). Käytännön sovelluksissa tulee monesti tilanteita joissa pelkkä inventointi ei riitä, vaan tarvitaan menetelmiä liikeradan estimointiin luotettavien havaintojen ja luokittelun tekemiseksi sekä raporttien generoimiseksi. Tässä työssä on suunniteltu ja toteutettu sulautettu ohjelmistosovellus teolliseen, resursseiltaan rajoitettuun ja kaupallisesti saatavaan UHF-taajuusalueen RFID-lukijalaitteeseen. Ohjelmistoa käytetään lukijalaitteen ja sen ilmarajapinnan toimintojen konfigurointiin, lukutapahtumien keräämiseen ja raporttien lähettämiseen verkkoyhteyksiä pitkin. Paikkatiedon estimointimenetelmien integroiminen ohjelmistoon mahdollistaa välitason RFID-sovellusten toteuttamisen aiempaa suoraviivaisemin ja luotettavammin, vähentäen samalla vaatimuksia tietoverkon kaistanleveydelle. Työn tuloksena on toimiva sulautettu ohjelmistosovellus, jota ajetaan sulautetussa Linux-käyttöjärjestelmässä ARM-arkkitehtuurilla. Lukijaohjelmistoa käytetään kaupallisesti teollisuuden ja logistiikan sovelluskohteissa. Epälineaarisia estimointiominaisuuksia hyödynnetään, ja niiden toimivuutta arvioidaan empiirisin kokein

Construcción de un modelo eficiente de predicción de heladas en entornos locales mediante técnicas del análisis inteligente en contextos IoT.

Esta tesis doctoral se asienta sobre una hipótesis inicial dividida en un conjunto de objetivos, que describimos y detallamos a continuación. Dichos objetivos son las bases sobre la que se construye la tesis doctoral y sobre los que se consigue alcanzar y validar la hipótesis planteada. La hipótesis fundamental de esta tesis doctoral es la modelización del comportamiento de las temperaturas dentro una parcela agrícola. A partir de ahí predecir las heladas para poder activar con tiempo las técnicas antiheladas y así evitar la pérdida de la cosecha con las consiguientes pérdidas económicas. Dicha hipótesis se deriva en los siguientes objetivos: Objetivo 1. Implementar una arquitectura IoT de captura de datos. Inicialmente se propone la implementación y el despliegue de un sistema IoT de recogida de información mediante la tecnología LoRa, con sensores de medición de temperatura y humedad del aire, así como velocidad del viento. • Objetivo 2. Diseñar e implementar el pre-procesamiento de datos. En la recogida de datos se pueden producir errores en los mismos, que posteriormente pueden provocar modelos incorrectos o con un rendimiento inferior al esperado. Para evitar esta problemática se aborda en esta tesis la detección y corrección de outliers para crear conjuntos de datos válidos. • Objetivo 3.Diseñar e implementar un modelo de predicción de heladas. Con los conjuntos de datos validados y corregidos tras el pre-procesamiento de los mismos, diseñar e implementar un modelo de predicción de la temperatura del aire que permita inferir si se producirá una helada. • Objetivo 4. Validar el modelo de predicción tanto en entornos Cloud como en el Edge. Las condiciones de aislamiento de muchas parcelas agrícolas no permiten tener una conectividad suficiente para estar en contacto directo con un servidor en Internet, por tanto, es necesario validar que el modelo predictivo puede ser ejecutado, tanto en entornos Cloud como en entornos Edge. En este último escenario, mediante un uso eficiente de la energía. • Objetivo 5. Evaluación de un modelo de predicción de heladas univariable frente a uno multivariable. La aparición de una helada, además de por la temperatura, está condicionada por otras variables. Diseñar e implementar un modelo multivariable para compararlo con el univariante y verificar que se obtiene una predicción más exacta.Ingeniería, Industria y Construcció

Business impact, risks and controls associated with the internet of things

Thesis (MCom)--Stellenbosch University, 2017.ENGLISH SUMMARY : Modern businesses need to keep up with the ever-evolving state of technology to determine how a change in technology will affect their operations. Adopting Internet of Things to operations will assist businesses in achieving the goals set by management and, through data integration, add additional value to information. With the Internet of Things forming a global communication network, data is gathered in real time by sensor technologies embedded in uniquely identifiable virtual and physical objects. This data gathered are integrated and analysed to extract knowledge, in order to provide services like inventory management, customised customer service and elearning as well as accurate patient records. This integrated information will generate value for businesses by, inter alia, improving the quality of information and business operations. Business may be quick to adopt the Internet of Things into their operations because of the promised benefits, without fully understanding its enabling technologies. It is important that businesses acquire knowledge of the impact that these technologies will have on their operations as well as the risks associated with the use of these technologies before they deploy the Internet of Things in their business environment. The purpose of this study was to identify the business impact, risks and controls associated with the Internet of Things and its enabling technologies. Through the understanding of the enabling technologies of Internet of Things, the possible uses and impact on business operations can be identified. With the help of a control framework, the understanding gained on the technologies were used to identify the risks associated with them. The study concludes by formulating internal controls to address the identified risks. It was found that the core technologies (smart objects, wireless networks and semantic technologies) adopt humanlike characteristics and convert most manual business operations into autonomous operations, leading to increased business productivity, market differentiation, cost reduction and higher-quality information. The identified risks centred on data integrity, privacy and confidentiality, authenticity, unauthorised access, network availability and semantic technology vulnerabilities. A multi-layered approach of technical and non-technical internal controls were formulated to mitigate the identified risks to an acceptable level. The findings will assist information technology specialists and executive management of industries to identify the risks associated with the implementation of Internet of Things in operations, mitigate the risks to an acceptable level through controls as well as assist them to determine the possible uses and its impact on operations.AFRIKAANSE OPSOMMING : Moderne ondernemings moet tred hou met die voortdurende ontwikkeling van tegnologie om te bepaal hoe ʼn verandering in tegnologie hulle bedrywighede sal beïnvloed. Inkorporering van Internet van Dinge in bedrywighede sal besighede help om die doelwitte wat deur bestuur gestel is te bereik en, deur data integrasie, additionele waarde te voeg tot inligting. Met Internet van Dinge wat ʼn globale kommunikasienetwerk vorm, word data in regte tyd versamel deur ensortegnologieë wat ingebed is in unieke identifiseerbare virtuele en fisiese voorwerpe. Hierdie versamelde data word geïntegreer en ontleed om kennis te onttrek om sodoende dienste te lewer, soos voorraadbestuur, pasgemaakte kliëntediens en e-leer sowel as akkurate pasiënt rekords. Hierdie geïntegreerde inligting sal waarde genereer vir ondernemings deur, inter alia, die gehalte van inligting en sakebedrywighede te verbeter. Ondernemings mag vinnig Internet van Dinge in hulle bedrywighede inkorporeer as gevolg van die beloofde voordele, sonder om die instaatstellende tegnologieë ten volle te verstaan. Dit is belangrik dat ondernemings kennis inwin oor die impak wat hierdie tegnologieë sal hê op hulle bedrywighede sowel as die risiko’s wat geassosieer word met die gebruik van hierdie tegnologieë voordat Internet van Dinge in hulle sakeomgewings ontplooi word. Die doel van hierdie studie was om die besigheidsimpak, risko’s en kontroles wat geassosieer word met Internet van Dinge en die instaatstellende tegnologieë te identifiseer. Deur die instaatstellende tegnologieë van Internet van Dinge te verstaan, kan die moontlike gebruike en impak daarvan op sakebedrywighede geïdentifiseer word. Met behulp van ʼn kontroleraamwerk, is die begrip van die tegnologieë gebruik om die risiko’s wat geassosieer word met hulle te identifiseer. Die studie sluit af met die formulering van interne kontroles om die geïdentifiseerde risko’s aan te spreek. Daar is gevind dat die kerrntegnologiekomponente (slim voorwerpe, draadlose netwerke en semantiese tegnologieë) menslike eienskappe aanneem en die meeste handsakebedrywighede omskakel na outonome bedrywighede, wat lei tot verhoogte sakeproduktiwiteit, markdifferensiasie, kostebesparing en hoërgehalte-inligting. Die geïdentifiseerde risiko’s is toegespits op data integriteit, -privaatheid en - vertroulikheid, egtheid, ongemagtigde toegang, netwerkbeskikbaarheid en semantiese tegnologiekwesbaarhede. ʼn Multilaagbenadering van tegniese en nie-tegniese interne kontroles is geformuleer, om sodoende die geïdentifiseerde risiko’s tot ʼn aanvaarbare vlak te versag. Die bevindinge sal inligtingstegnologie-spesialiste en uitvoerende bestuur van industrieë help om die risiko’s verbonde aan implementering van Internet van Dinge te identifiseer, risko’s te versag tot ʼn aanvaarbare vlak met kontroles sowel as hulle te help om moontlike gebruike en hulle impak op bedrywighede vas te stel