A Mobile Sensor Networks (MSNs) is normally made up of a number of mobile sensors which can be placed in a region of interest (ROI) by people. Sensors communicate with each other through wireless links to perform the distributed sensing ability for covering a region. Through a specific algorithm, the sensors move automatically, and finally the sensor network achieves a large sensing coverage. Sensing coverage can be established and promoted by different algorithms, and a good algorithm can lead sensors to form the largest possible sensing area without any sensing holes (areas that cannot be detected or monitored). The coverage of a sensor network is defined as the total area of interest covered, minus the area of the sensing holes. We introduce a novel algorithm called the Spanning Tree-based Greedy-Rotation-Back (STGRB). The traditional Greedy-Rotation-Greedy (GRG) algorithm uses a point as a specific start so it's not appropriate for practical circumstances. So in the STGRB, we first use a spanning tree algorithm to get the gravity center (the sensor that connects the most sensors or is physically close to most of the other sensors) of the network. In this way we eliminate the first condition of selecting a sensor as a start point and also we conserve the energy of the sensors via letting them move a shorter distance.

In this thesis we considered a simulation platform for mobile robots algorithms: Sycamore. We implemented several new features for Sycamore and we tested them while studying three different algorithms to achieve gathering by robots with limited visibility: a deterministic well known algorithm, a simple new probabilistic algorithm, and a combination of the two. The deterministic algorithm is known to achieve exact gathering when there are no faults; we tested it for the first time in presence of crashes and observed interesting and unexpected behaviors. We then performed extensive simulations with the probabilistic solution to identify the cause of an unexpected high rate of success, the simulations help us identify the relation between the rate of success and the initial configuration. Finally, we combined the two designing a hybrid solution. This work resulted in improvements of Sycamore, which can now be better employed to study mobile robots algorithms, as well as in empirical observations leading to new theoretical problems to be investigated.

This thesis is concerned with the analysis of large offshore gravity structures used for oil exploration and recovery in the Beaufort Sea. Because of the high ice loads and the water depths involved, these structures comprise a large steel box infilled with a sand core for stability. One such structure was subjected to severe ice loading in April 1986 causing portions of the sand core to liquefy and bring the structure to a near failure condition. This structure was heavily monitored and thus serves as a case study against which the proposed analysis procedure can be checked. The behaviour of these soil-structure systems is highly complex depending upon the characteristics of the soil, the structural elements and the soil-structure interface. In this thesis a three-dimensional Finite Element computer program with soil, interface and structural elements is developed. Emphasis is placed on the three-dimensional stress-strain constitutive law both in terms of its ability to model observed laboratory response as well as the determination of the constitutive law parameters from in situ testing. The results obtained in terms of displacement, acceleration and zones of liquefaction by the analysis were then compared with the field measurements obtained during the April 1986 ice load event. The good agreement obtained between predicted and observed response is a validation of the proposed procedure. / Applied Science, Faculty of / Civil Engineering, Department of / Graduate

M.B.A. / The first mobile cellular telephone was established In St. louis (Missouri. USA) in 1946. In a few years time Europe followed with a similar service. These systems were based on technology developed during the World War 2 (Vodacom Corporate Profile:1999/2000:1). Between 1950 and 1960, cellular radio evolved to become automatic and Its costs dropped due to the Introduction of transistor technology. During the 1970's large scale integration and development of micro-processors enabled more complex systems development (Vodacom Corporate Profile :1999/2000:1 ). In 1988 the European Telecommunications Standard Institute (ETSI) was created. This Institute enabled network operators and telecommunications equipment manufacturers to become Involved In the specification of Global System for Mobile Communications (GSM) (Vodacom Corporate Profile :199~/2000:1 ). The GSM standard of communication was launched In Europe in 1992. This standard Is widelyused In European and African countries...

0 / SPK / specialcollections@tulane.edu

The purpose of this thesis is to design and implement four-wheel mobile robot control which will be used in future in the field of mapping and localization. Concretely, it will be a design of drive control with microcontrollers Xmega, which will also process the signals of the sensors. Communication with the PC will ensure the BlueTooth module. In view of the future use of the robot, there will be designed and carried out modifications of the mechanical part. Correctness and functionality of all parts of the robot will be verified by carrying out basic movements.

Bei der Entwicklung von mobilen Informationssystemen stehen die Entwickler oft vor immer wiederkehrenden Entwurfsentscheidungen, die von einer Anzahl noch unstrukturierter Kriterien abhängen. Den kompletten Entscheidungsprozess für jedes einzelne Projekt von vorne bis hinten zu durchlaufen ist ineffizient und fehleranfällig, trotzdem gibt es noch keine umfassende Sammlung von „Best Practices“, die diesen Prozess verkürzen könnte. Wir präsentieren daher die Grundlagen eines Klassifikationsschemas für mobile Informationssysteme, das Entwicklern hilft, Anwendungen anhand von Anforderungen auf höherer Ebene zu klassifizieren und entsprechende Architekturentscheidungen zu treffen. Im Anschluss an die Diskussion der vorgestellten Kriterien schlagen wir Erweiterungen des Klassifikationsschemas und Folgerungen, die daraus gezogen werden können, vor.

Prototyping is generally acknowledged as an effective method for generating cost-effective, preliminary designs of various products including web and mobile user interfaces. Out of the existing types of prototyping, paper prototyping is known for being the most cost-effective of them all, as well as the most constrained for the realistic user experience elements it can render. High-Fidelity prototypes on the other hand offer a richer experience to the user, at the high cost of developing sophisticated software/hardware-based demonstrations. Although both of these types of prototypes continue to be widely and successfully used in product and interface design, there is no evidence of a cost-effective technique that would elicit user’s feedback which as rich as high-fidelity prototypes but without implementation effort. This study proposes an innovative prototyping technique called “Paper in Screen” (Bolchini, Pulido, Faiola, 2009) which enables designers to cheaply and rapidly prototype a mobile application in its key components (interface design and mobile device integration) without the need for implementing a high-fidelity prototype. A study was performed with 10 user experience professionals to evaluate their perception of the technique’s effectiveness, from which a number of benefits and drawbacks of the “Paper in Screen” were learned. The obtained results point to areas of future research in mobile prototyping.

Doctor of Science in Engineering - Engineering / The advent of mobile technology, Geospatial Information Systems (GIS) and convergence of voice and data over wireless networks have led to an explosion of a wide range of mobile applications. These applications include mobile internet browsers, handheld GPS navigation systems, Location Based Services (LBS), mobile workforce management systems, and so on. While much of the underlying technology is already available, there are challenges with respect to the usability of mobile applications. This project investigates the usability of a mobile application for field data collection in a utility industry. The purpose of the investigation is to gain a better understanding of the usability requirements for a mobile field data collection application but more importantly, how to meet these requirements using appropriate usability engineering techniques. A usage-centered design approach is used to design the user interface for the field data collection application. During this model-driven design process, the usability requirements are analyzed in terms of the user requirements, field data collection tasks and the operational context of fieldwork. An Underground Utility Closure (UUC) data sourcing work employed at a telecommunications utility is used as a case study for the field data collection work. The user interface is implemented as a functional prototype on a pocket computer and evaluated for usability in a field setting. It is envisaged that the usability requirements and design guidelines presented in this project will enable software engineers to meet the design challenges of usable mobile applications for field data collection and mobile computing in general.

Large-scale spatial data such as air quality of a city, biomass content in a lake, Wi-Fi Received Signal Strengths (RSS, also referred as fingerprints) in indoor spaces often play vital roles to applications like indoor localization. However, it is extremely labor-intensive and time-consuming to collect those data manually. In this thesis, the main goal is to develop efficient means for large-scale spatial data collection. Robotic technologies nowadays offer an opportunity on mobile sensing, where data are collected by a robot traveling in target areas. However, since robots usually have a limited travel budget depending on battery capacity, one important problem is to schedule a data collection path to best utilize the budget. Inspired by existing literature, we consider to collect data along informative paths. The process to search the most informative path given a limited budget is known as the informative path planning (IPP) problem, which is NP-hard. Thus, we propose two heuristic approaches, namely a greedy algorithm and a genetic algorithm. Experiments on Wi-Fi RSS based localization show that data collected along informative paths tend to achieve lower errors than that are opportunistically collected. In practice, the budget of a mobile robot can vary due to insufficient charging or battery degradation. Although it is possible to apply the same path planning algorithm repetitively whenever the budget changes, it is more efficient and desirable to avoid solving the problem from scratch. This can be possible since informative paths for the same area share common characteristics. Based on this intuition, we propose and design a reinforcement learning based IPP solution, which is able to predict informative paths given any budget. In addition, it is common to have multiple robots to conduct sensing tasks cooperatively. Therefore, we also investigate the multi-robot IPP problem and present two solutions based on multi-agent reinforcement learning. Mobile crowdsourcing (MCS) offers another opportunity to lowering the cost of data collection. In MCS, data are collected by individual contributors, which is able to accumulate a large amount of data when there are sufficient participants. As an example, we consider the collection of a specific type of spatial data, namely Wi-Fi RSS, for indoor localization purpose. The process to collect RSS is also known as site survey in the localization community. Though MCS based site survey has been suggested a decade ago~\cite{park2010growing}, so far, there has not been any published large-scale fingerprint MCS campaign. The main issue is that it depends on user's participation, and users may be reluctant to make a contribution. To investigate user behavior in a real-world site survey, we design an indoor fingerprint MCS system and organize a data collection campaign in the McMaster University campus for five months. Although we focus on Wi-Fi fingerprints, the design choices and campaign experience are beneficial to the MCS of other types of spatial data as well. The contribution of this thesis is two-fold. For applications where robots are available for large-scale spatial sensing, efficient path planning solutions are investigated so as to maximize data utility. Meanwhile, for MCS based data acquisition, our real-world campaign experience and user behavior study reveal essential design factors that need to be considered and aspects for further improvements. / Thesis / Doctor of Philosophy (PhD) / A variety of applications such as environmental monitoring require to collect large-scale spatial data like air quality, temperature and humidity. However, it usually incurs dramatic costs like time to obtain those data, which is impeding the deployment of those applications. To reduce the data collection efforts, we consider two mobile sensing schemes, i.e, mobile robotic sensing and mobile crowdsourcing. For the former scheme, we investigate how to plan paths for mobile robots given limited travel budgets. For the latter scheme, we design a crowdsourcing platform and study user behavior through a real word data collection campaign. The proposed solutions in this thesis can benefit large-scale spatial data collection tasks.