Applications of Internet of Things

This book introduces the Special Issue entitled “Applications of Internet of Things”, of ISPRS International Journal of Geo-Information. Topics covered in this issue include three main parts: (I) intelligent transportation systems (ITSs), (II) location-based services (LBSs), and (III) sensing techniques and applications. Three papers on ITSs are as follows: (1) “Vehicle positioning and speed estimation based on cellular network signals for urban roads,” by Lai and Kuo; (2) “A method for traffic congestion clustering judgment based on grey relational analysis,” by Zhang et al.; and (3) “Smartphone-based pedestrian’s avoidance behavior recognition towards opportunistic road anomaly detection,” by Ishikawa and Fujinami. Three papers on LBSs are as follows: (1) “A high-efficiency method of mobile positioning based on commercial vehicle operation data,” by Chen et al.; (2) “Efficient location privacy-preserving k-anonymity method based on the credible chain,” by Wang et al.; and (3) “Proximity-based asynchronous messaging platform for location-based Internet of things service,” by Gon Jo et al. Two papers on sensing techniques and applications are as follows: (1) “Detection of electronic anklet wearers’ groupings throughout telematics monitoring,” by Machado et al.; and (2) “Camera coverage estimation based on multistage grid subdivision,” by Wang et al

Migration from Teleoperation to Autonomy via Modular Sensor and Mobility Bricks

In this thesis, the teleoperated communications of a Remotec ANDROS robot have been reverse engineered. This research has used the information acquired through the reverse engineering process to enhance the teleoperation and add intelligence to the initially automated robot. The main contribution of this thesis is the implementation of the mobility brick paradigm, which enables autonomous operations, using the commercial teleoperated ANDROS platform. The brick paradigm is a generalized architecture for a modular approach to robotics. This architecture and the contribution of this thesis are a paradigm shift from the proprietary commercial models that exist today. The modular system of sensor bricks integrates the transformed mobility platform and defines it as a mobility brick. In the wall following application implemented in this work, the mobile robotic system acquires intelligence using the range sensor brick. This application illustrates a way to alleviate the burden on the human operator and delegate certain tasks to the robot. Wall following is one among several examples of giving a degree of autonomy to an essentially teleoperated robot through the Sensor Brick System. Indeed once the proprietary robot has been altered into a mobility brick; the possibilities for autonomy are numerous and vary with different sensor bricks. The autonomous system implemented is not a fixed-application robot but rather a non-specific autonomy capable platform. Meanwhile the native controller and the computer-interfaced teleoperation are still available when necessary. Rather than trading off by switching from teleoperation to autonomy, this system provides the flexibility to switch between the two at the operator’s command. The contributions of this thesis reside in the reverse engineering of the original robot, its upgrade to a computer-interfaced teleoperated system, the mobility brick paradigm and the addition of autonomy capabilities. The application of a robot autonomously following a wall is subsequently implemented, tested and analyzed in this work. The analysis provides the programmer with information on controlling the robot and launching the autonomous function. The results are conclusive and open up the possibilities for a variety of autonomous applications for mobility platforms using modular sensor bricks

Using wireless sensor networks in improvised explosive device detection

This research focused on wide-area surveillance of public environments for potential IEDs (improvised explosive devices) using wireless sensor networks. We explored magnetic and infrared sensors from Crossbow Technologies to detect simulated emplaced IEDs (emplacement is the step most susceptible to detection) in a public mall and along a typical street environment. The threat scenario was IED emplacement in a trash receptacle. A network of these sensors was built and positioned in these environments with human subjects entering (some carrying ferromagnetic materials and some not) and proceeding toward a receptacle. Results indicated that magnetic sensors could detect suspicious ferromagnetic materials, though not all simulated IEDs contained enough to trigger detection. Infrared sensors were not effective for such tasks as there is much background infrared radiation. Our network design was such that data could easily be aggregated over many sensors in larger networks. This suggests that the technology can be effective for protecting communal areas such as airports and urban areas. Other supplementary technologies such as imagery could be linked to build a more robust detection network.http://archive.org/details/usingwirelesssen109453129Singapore Army author.Approved for public release; distribution is unlimited

Tecnologias IoT para pastoreio e controlo de postura animal

The unwanted and adverse weeds that are constantly growing in vineyards, force wine producers to repeatedly remove them through the use of mechanical and chemical methods. These methods include machinery such as plows and brushcutters, and chemicals as herbicides to remove and prevent the growth of weeds both in the inter-row and under-vine areas. Nonetheless, such methods are considered very aggressive for vines, and, in the second case, harmful for the public health, since chemicals may remain in the environment and hence contaminate water lines. Moreover, such processes have to be repeated over the year, making it extremely expensive and toilsome. Using animals, usually ovines, is an ancient practice used around the world. Animals, grazing in vineyards, feed from the unwanted weeds and fertilize the soil, in an inexpensive, ecological and sustainable way. However, sheep may be dangerous to vines since they tend to feed on grapes and on the lower branches of the vines, which causes enormous production losses. To overcome that issue, sheep were traditionally used to weed vineyards only before the beginning of the growth cycle of grapevines, thus still requiring the use of mechanical and/or chemical methods during the remainder of the production cycle. To mitigate the problems above, a new technological solution was investigated under the scope of the SheepIT project and developed in the scope of this thesis. The system monitors sheep during grazing periods on vineyards and implements a posture control mechanism to instruct them to feed only from the undesired weeds. This mechanism is based on an IoT architecture, being designed to be compact and energy efficient, allowing it to be carried by sheep while attaining an autonomy of weeks. In this context, the thesis herein sustained states that it is possible to design an IoT-based system capable of monitoring and conditioning sheep’s posture, enabling a safe weeding process in vineyards. Moreover, we support such thesis in three main pillars that match the main contributions of this work and that are duly explored and validated, namely: the IoT architecture design and required communications, a posture control mechanism and the support for a low-cost and low-power localization mechanism. The system architecture is validated mainly in simulation context while the posture control mechanism is validated both in simulations and field experiments. Furthermore, we demonstrate the feasibility of the system and the contribution of this work towards the first commercial version of the system.O constante crescimento de ervas infestantes obriga os produtores a manter um processo contínuo de remoção das mesmas com recurso a mecanismos mecânicos e/ou químicos. Entre os mais populares, destacam-se o uso de arados e roçadores no primeiro grupo, e o uso de herbicidas no segundo grupo. No entanto, estes mecanismos são considerados agressivos para as videiras, assim como no segundo caso perigosos para a saúde pública, visto que os químicos podem permanecer no ambiente, contaminando frutos e linhas de água. Adicionalmente, estes processos são caros e exigem mão de obra que escasseia nos dias de hoje, agravado pela necessidade destes processos necessitarem de serem repetidos mais do que uma vez ao longo do ano. O uso de animais, particularmente ovelhas, para controlar o crescimento de infestantes é uma prática ancestral usada em todo o mundo. As ovelhas, enquanto pastam, controlam o crescimento das ervas infestantes, ao mesmo tempo que fertilizam o solo de forma gratuita, ecológica e sustentável. Não obstante, este método foi sendo abandonado visto que os animais também se alimentam da rama, rebentos e frutos da videira, provocando naturais estragos e prejuízos produtivos. Para mitigar este problema, uma nova solução baseada em tecnologias de Internet das Coisas é proposta no âmbito do projeto SheepIT, cuja espinha dorsal foi construída no âmbito desta tese. O sistema monitoriza as ovelhas enquanto estas pastoreiam nas vinhas, e implementam um mecanismo de controlo de postura que condiciona o seu comportamento de forma a que se alimentem apenas das ervas infestantes. O sistema foi incorporado numa infraestrutura de Internet das Coisas com comunicações sem fios de baixo consumo para recolha de dados e que permite semanas de autonomia, mantendo os dispositivos com um tamanho adequado aos animais. Neste contexto, a tese suportada neste trabalho defende que é possível projetar uma sistema baseado em tecnologias de Internet das Coisas, capaz de monitorizar e condicionar a postura de ovelhas, permitindo que estas pastem em vinhas sem comprometer as videiras e as uvas. A tese é suportada em três pilares fundamentais que se refletem nos principais contributos do trabalho, particularmente: a arquitetura do sistema e respetivo sistema de comunicações; o mecanismo de controlo de postura; e o suporte para implementação de um sistema de localização de baixo custo e baixo consumo energético. A arquitetura é validada em contexto de simulação, e o mecanismo de controlo de postura em contexto de simulação e de experiências em campo. É também demonstrado o funcionamento do sistema e o contributo deste trabalho para a conceção da primeira versão comercial do sistema.Programa Doutoral em Informátic

A Novel Approach to Railway Track Faults Detection Using Acoustic Analysis.

Regular inspection of railway track health is crucial for maintaining safe and reliable train operations. Factors, such as cracks, ballast issues, rail discontinuity, loose nuts and bolts, burnt wheels, superelevation, and misalignment developed on the rails due to non-maintenance, pre-emptive investigations and delayed detection, pose a grave danger and threats to the safe operation of rail transport. The traditional procedure of manually inspecting the rail track using a railway cart is both inefficient and prone to human error and biases. In a country like Pakistan where train accidents have taken many lives, it is not unusual to automate such approaches to avoid such accidents and save countless lives. This study aims at enhancing the traditional railway cart system to address these issues by introducing an automatic railway track fault detection system using acoustic analysis. In this regard, this study makes two important contributions: data collection on Pakistan railway tracks using acoustic signals and the application of various classification techniques to the collected data. Initially, three types of tracks are considered, including normal track, wheel burnt and superelevation, due to their common occurrence. Several well-known machine learning algorithms are applied such as support vector machines, logistic regression, random forest and decision tree classifier, in addition to deep learning models like multilayer perceptron and convolutional neural networks. Results suggest that acoustic data can help determine the track faults successfully. Results indicate that the best results are obtained by RF and DT with an accuracy of 97%

AI and IoT Meet Mobile Machines: Towards a Smart Working Site

Infrastructure construction is society's cornerstone and economics' catalyst. Therefore, improving mobile machinery's efficiency and reducing their cost of use have enormous economic benefits in the vast and growing construction market. In this thesis, I envision a novel concept smart working site to increase productivity through fleet management from multiple aspects and with Artificial Intelligence (AI) and Internet of Things (IoT)

Design of a walking robot

Carnegie Mellon University's Autonomous Planetary Exploration Program (APEX) is currently building the Daedalus robot; a system capable of performing extended autonomous planetary exploration missions. Extended autonomy is an important capability because the continued exploration of the Moon, Mars and other solid bodies within the solar system will probably be carried out by autonomous robotic systems. There are a number of reasons for this - the most important of which are the high cost of placing a man in space, the high risk associated with human exploration and communication delays that make teleoperation infeasible. The Daedalus robot represents an evolutionary approach to robot mechanism design and software system architecture. Daedalus incorporates key features from a number of predecessor systems. Using previously proven technologies, the Apex project endeavors to encompass all of the capabilities necessary for robust planetary exploration. The Ambler, a six-legged walking machine was developed by CMU for demonstration of technologies required for planetary exploration. In its five years of life, the Ambler project brought major breakthroughs in various areas of robotic technology. Significant progress was made in: mechanism and control, by introducing a novel gait pattern (circulating gait) and use of orthogonal legs; perception, by developing sophisticated algorithms for map building; and planning, by developing and implementing the Task Control Architecture to coordinate tasks and control complex system functions. The APEX project is the successor of the Ambler project

Improving perception and locomotion capabilities of mobile robots in urban search and rescue missions

Nasazení mobilních robotů během zásahů záchranných složek je způsob, jak učinit práci záchranářů bezpečnější a efektivnější. Na roboty jsou ale při takovém použití kladeny vyšší nároky kvůli podmínkám, které při těchto událostech panují. Roboty se musejí pohybovat po nestabilních površích, ve stísněných prostorech nebo v kouři a prachu, což ztěžuje použití některých senzorů. Lokalizace, v robotice běžná úloha spočívající v určení polohy robotu vůči danému souřadnému systému, musí spolehlivě fungovat i za těchto ztížených podmínek. V této dizertační práci popisujeme vývoj lokalizačního systému pásového mobilního robotu, který je určen pro nasazení v případě zemětřesení nebo průmyslové havárie. Nejprve je předveden lokalizační systém, který vychází pouze z měření proprioceptivních senzorů a který vyvstal jako nejlepší varianta při porovnání několika možných uspořádání takového systému. Lokalizace je poté zpřesněna přidáním měření exteroceptivních senzorů, které zpomalují kumulaci nejistoty určení polohy robotu. Zvláštní pozornost je věnována možným výpadkům jednotlivých senzorických modalit, prokluzům pásů, které u tohoto typu robotů nevyhnutelně nastávají, výpočetním nárokům lokalizačního systému a rozdílným vzorkovacím frekvencím jednotlivých senzorů. Dále se věnujeme problému kinematických modelů pro přejíždění vertikálních překážek, což je další zdroj nepřesnosti při lokalizaci pásového robotu. Díky účasti na výzkumných projektech, jejichž členy byly hasičské sbory Itálie, Německa a Nizozemska, jsme měli přístup na cvičiště určená pro přípravu na zásahy během zemětřesení, průmyslových a dopravních nehod. Přesnost našeho lokalizačního systému jsme tedy testovali v podmínkách, které věrně napodobují ty skutečné. Soubory senzorických měření a referenčních poloh, které jsme vytvořili pro testování přesnosti lokalizace, jsou veřejně dostupné a považujeme je za jeden z přínosů naší práce. Tato dizertační práce má podobu souboru tří časopiseckých publikací a jednoho článku, který je v době jejího podání v recenzním řízení.eployment of mobile robots in search and rescue missions is a way to make job of human rescuers safer and more efficient. Such missions, however, require robots to be resilient to harsh conditions of natural disasters or human-inflicted accidents. They have to operate on unstable rough terrain, in confined spaces or in sensory-deprived environments filled with smoke or dust. Localization, a common task in mobile robotics which involves determining position and orientation with respect to a given coordinate frame, faces these conditions as well. In this thesis, we describe development of a localization system for tracked mobile robot intended for search and rescue missions. We present a proprioceptive 6-degrees-of-freedom localization system, which arose from the experimental comparison of several possible sensor fusion architectures. The system was modified to incorporate exteroceptive velocity measurements, which significantly improve accuracy by reducing a localization drift. A special attention was given to potential sensor outages and failures, to track slippage that inevitably occurs with this type of robots, to computational demands of the system and to different sampling rates sensory data arrive with. Additionally, we addressed the problem of kinematic models for tracked odometry on rough terrains containing vertical obstacles. Thanks to research projects the robot was designed for, we had access to training facilities used by fire brigades of Italy, Germany and Netherlands. Accuracy and robustness of proposed localization systems was tested in conditions closely resembling those seen in earthquake aftermath and industrial accidents. Datasets used to test our algorithms are publicly available and they are one of the contributions of this thesis. We form this thesis as a compilation of three published papers and one paper in review process

A wireless sensor network system for border security and crossing detection

The protection of long stretches of countries’ borders has posed a number of challenges. Effective and continuous monitoring of a border requires the implementation of multi-surveillance technologies, such as Wireless Sensor Networks (WSN), that work as an integrated unit to meet the desired goals. The research presented in this thesis investigates the application of topologically Linear WSN (LWSNs) to international border monitoring and surveillance. The main research questions studied here are: What is the best form of node deployment and hierarchy? What is the minimum number of sensor nodes to achieve k− barrier coverage in a given belt region? iven an appropriate network density, how do we determine if a region is indeed k−barrier covered? What are the factors that affect barrier coverage? How to organise nodes into logical segments to perform in-network processing of data? How to transfer information from the networks to the end users while maintaining critical QoS measures such as timeliness and accuracy. To address these questions, we propose an architecture that specifies a mechanism to assign nodes to various network levels depending on their location. These levels are used by a cross-layer communication protocol to achieve data delivery at the lowest possible cost and minimal delivery delay. Building on this levelled architecture, we study the formation of weak and strong barriers and how they determine border crossing detection probability. We propose new method to calculate the required node density to provide higher intruder detection rate. Then, we study the effect of people movement models on the border crossing detection probability. At the data link layer, new energy balancing along with shifted MAC protocol are introduced to further increase the network lifetime and delivery speed. In addition, at network layer, a routing protocol called Level Division raph (LD ) is developed. LD utilises a complex link cost measurement to insure best QoS data delivery to the sink node at the lowest possible cost. The proposed system has the ability to work independently or cooperatively with other monitoring technologies, such as drowns and mobile monitoring stations. The performance of the proposed work is extensively evaluated analytically and in simulation using real-life conditions and parameters. The simulation results show significant performance gains when comparing LD to its best rivals in the literature Dynamic Source Routing. Compared to DSR, LD achieves higher performance in terms of average end-to-end delays by up to 95%, packet delivery ratio by up to 20%, and throughput by up to 60%, while maintaining similar performance in terms of normalised routing load and energy consumption

AI and IoT Meet Mobile Machines

Infrastructure construction is society's cornerstone and economics' catalyst. Therefore, improving mobile machinery's efficiency and reducing their cost of use have enormous economic benefits in the vast and growing construction market. In this thesis, I envision a novel concept smart working site to increase productivity through fleet management from multiple aspects and with Artificial Intelligence (AI) and Internet of Things (IoT)