On the Dynamics of Human Proximity for Data Diffusion in Ad-Hoc Networks

We report on a data-driven investigation aimed at understanding the dynamics of message spreading in a real-world dynamical network of human proximity. We use data collected by means of a proximity-sensing network of wearable sensors that we deployed at three different social gatherings, simultaneously involving several hundred individuals. We simulate a message spreading process over the recorded proximity network, focusing on both the topological and the temporal properties. We show that by using an appropriate technique to deal with the temporal heterogeneity of proximity events, a universal statistical pattern emerges for the delivery times of messages, robust across all the data sets. Our results are useful to set constraints for generic processes of data dissemination, as well as to validate established models of human mobility and proximity that are frequently used to simulate realistic behaviors.Comment: A. Panisson et al., On the dynamics of human proximity for data diffusion in ad-hoc networks, Ad Hoc Netw. (2011

Feasibility Analysis of Non-electromagnetical Signals Collected via Thingsee Sensors for Indoor Positioning

Internet of Things (IoT) has significant impacts on wireless networking and communication technologies of modern times. Recently it has gained also attention in the field of indoor positioning and localization, both in research and industrial markets. IoT technologies enables access to the real time information about indoor environment which are collected through sensors. The sensor data is processed and analysed to understand the complexity of the indoor environment so that it can be used for making applications based on positioning. This thesis deals with some modern applications, challenges, key technologies and architectural overviews of Internet of Things including some recent works which were carried out based on electromagnetical and non-electromagnetical approaches. Then. a feasibility analysis is made for indoor positioning using non-electromagnetical sensor data which includes temperature, humidity, pressure and luminance. These sensors are also known as environmental sensors. An IoT development device named ‘Thingsee One’ was used where the environmental sensors were embedded in. The device was used for capturing environmental data from different locations inside a university building in Tampere, Finland. At first, Thingsee One device was configured for capturing temperature, humidity, pressure and luminance data from an indoor environment. Measurements were taken from different locations of the building, from first and second floor. Different times and weather condition were also taken into account during data capturing. Then the captured data has been analysed for identifying those positions through histograms and power maps. The results show that, the data captured by the sensors are highly dependent on time and weather which makes them rather inconsistent over the same position in different situations and time and therefore not likely candidates for positioning estimation

Building efficient wireless infrastructures for pervasive computing environments

Pervasive computing is an emerging concept that thoroughly brings computing devices and the consequent technology into people\u27s daily life and activities. Most of these computing devices are very small, sometimes even invisible , and often embedded into the objects surrounding people. In addition, these devices usually are not isolated, but networked with each other through wireless channels so that people can easily control and access them. In the architecture of pervasive computing systems, these small and networked computing devices form a wireless infrastructure layer to support various functionalities in the upper application layer.;In practical applications, the wireless infrastructure often plays a role of data provider in a query/reply model, i.e., applications issue a query requesting certain data and the underlying wireless infrastructure is responsible for replying to the query. This dissertation has focused on the most critical issue of efficiency in designing such a wireless infrastructure. In particular, our problem resides in two domains depending on different definitions of efficiency. The first definition is time efficiency, i.e., how quickly a query can be replied. Many applications, especially real-time applications, require prompt response to a query as the consequent operations may be affected by the prior delay. The second definition is energy efficiency which is extremely important for the pervasive computing devices powered by batteries. Above all, our design goal is to reply to a query from applications quickly and with low energy cost.;This dissertation has investigated two representative wireless infrastructures, sensor networks and RFID systems, both of which can serve applications with useful information about the environments. We have comprehensively explored various important and representative problems from both algorithmic and experimental perspectives including efficient network architecture design and efficient protocols for basic queries and complicated data mining queries. The major design challenges of achieving efficiency are the massive amount of data involved in a query and the extremely limited resources and capability each small device possesses. We have proposed novel and efficient solutions with intensive evaluation. Compared to the prior work, this dissertation has identified a few important new problems and the proposed solutions significantly improve the performance in terms of time efficiency and energy efficiency. Our work also provides referrable insights and appropriate methodology to other similar problems in the research community

IoT Data Processing for Smart City and Semantic Web Applications

The world has been experiencing rapid urbanization over the last few decades, putting a strain on existing city infrastructure such as waste management, water supply management, public transport and electricity consumption. We are also seeing increasing pollution levels in cities threatening the environment, natural resources and health conditions. However, we must realize that the real growth lies in urbanization as it provides many opportunities to individuals for better employment, healthcare and better education. However, it is imperative to limit the ill effects of rapid urbanization through integrated action plans to enable the development of growing cities. This gave rise to the concept of a smart city in which all available information associated with a city will be utilized systematically for better city management. The proposed system architecture is divided in subsystems and is discussed in individual chapters. The first chapter introduces and gives overview to the reader of the complete system architecture. The second chapter discusses the data monitoring system and data lake system based on the oneM2M standards. DMS employs oneM2M as a middleware layer to achieve interoperability, and DLS uses a multi-tenant architecture with multiple logical databases, enabling efficient and reliable data management. The third chapter discusses energy monitoring and electric vehicle charging systems developed to illustrate the applicability of the oneM2M standards. The fourth chapter discusses the Data Exchange System based on the Indian Urban Data Exchange framework. DES uses IUDX standard data schema and open APIs to avoid data silos and enable secure data sharing. The fifth chapter discusses the 5D-IoT framework that provides uniform data quality assessment of sensor data with meaningful data descriptions

Design of a web-based LBS framework addressing usability, cost, and implementation constraints

This research investigates barriers that prevent Location Based Services (LBS) from reaching its full potential. The different constraints, including poor usability, lack of positioning support, costs, and integration difficulties are highlighted. A framework was designed incorporating components based on existing and new technologies that could help address the constraints of LBS and increase end-user acceptance. This research proposes that usability constraints can be addressed by adapting a system to user characteristics which are inferred on the basis of captured user context and interaction data. A prototype LBS system was developed to prove the feasibility and benefit of the framework design, demonstrating that constraints of positioning, cost, and integration can be overcome. Volunteers were asked to use the system, and to answer questions in relation to their proficiency and experience. User-feedback showed that the proposed combination of functionality was well-received, and the prototype was appealing to many users. Ground-truths from the survey were related back to data captured with a user monitoring component in order to investigate whether users can be classified according to their context and how they interact. The results have shown that statistically significant relationships exist, and that by using the C4.5 decision-tree, computer proficiency can be estimated within one class-width in 76.7% of the cases. These results suggest that it may be possible to build a user-model to estimate computer proficiency on the basis of user-interaction data. The user model could then used to improve usability through adaptive user-specific customisations

IoT for Efficient Data Collection from Real World Resources

The Internet of Things is providing new ways of experiencing and reacting to the physical world through the ability of advanced electronic devices that collect data. At the same time, as new application scenarios are envisioned, with the assistance of information generated by sensors, new problems and obstacles will arise. This requires new development to meet business and technical requirements, such as interoperability between heterogeneous devices and confidence (such as validity, security and trust) over smart devices. With the increase of these complex requirements it becomes crucial to develop an infrastructure aimed at tackling such requirements mentioned. IoT middleware – a software layer that bridges the gap between devices and information systems. Thus, this work aims to study the mechanisms and methodology for data collection, devices interoperability and data filtering, closer to the data sources, in order to optimize the collection and pre-analysis of data that can then be used by various applications such as the ones in manufacturing industry

An efficient scheme for applying software updates in pervasive computing applications

The Internet of Things (IoT) offers a vast infrastructure of numerous interconnected devices capable of communicating and exchanging data. Pervasive computing applications can be formulated on top of the IoT involving nodes that can interact with their environment and perform various processing tasks. Any task is part of intelligent services executed in nodes or the back end infrastructure for supporting end users’ applications. In this setting, one can identify the need for applying updates in the software/firmware of the autonomous nodes. Updates are extensions or patches significant for the efficient functioning of nodes. Legacy methodologies deal with centralized approaches where complex protocols are adopted to support the distribution of the updates in the entire network. In this paper, we depart from the relevant literature and propose a distributed model where each node is responsible to, independently, initiate and conclude the update process. Nodes monitor a set of metrics related to their load and the performance of the network and through a time-optimized scheme identify the appropriate time to conclude the update process. We report on an infinite horizon optimal stopping model on top of the collected performance data. The aim is to make nodes capable of identifying when their performance and the performance of the network are of high quality to efficiently conclude the update process. We provide specific formulations and the analysis of the problem while extensive simulations and a comparison assessment reveal the advantages of the proposed solution

Recognizing Patterns in Transmitted Signals for Identification Purposes

The ability to identify and authenticate entities in cyberspace such as users, computers, cell phones, smart cards, and radio frequency identification (RFID) tags is usually accomplished by having the entity demonstrate knowledge of a secret key. When the entity is portable and physically accessible, like an RFID tag, it can be difficult to secure given the memory, processing, and economic constraints. This work proposes to use unique patterns in the transmitted signals caused by manufacturing differences to identify and authenticate a wireless device such as an RFID tag. Both manufacturer identification and tag identification are performed on a population of 300 tags from three different manufacturers. A methodology to select features for identifying signals with high accuracy is developed and applied to passive RFID tags. The classifier algorithms K-Nearest Neighbors, Parzen Windows, and Support Vector Machines are investigated. The tag\u27s manufacturer can be identified with 99.93\% true positive rate. An individual tag is identified with 99.8\% accuracy, which is better than previously published work. Using a Hidden Markov Model with framed timing and power data, the tag manufacturer can be identified with 97.37\% accuracy and has a compact representation. An authentication system based on unique features of the signals is proposed assuming that the readers that interrogate the tags may be compromised by a malicious adversary. For RFID tags, a set of timing-only features can provide an accuracy of 97.22\%, which is better than previously published work, is easier to measure, and appears to be more stable than power features

Deep Space Habitability Design Guidelines Based on the NASA NextSTEP Phase 2 Ground Test Program

This report summarizes habitation design guidelines for deep space habitats, which were derived from the NASA Next Space Technologies for Exploration Partnerships (NextSTEP) Phase 2 Habitat Ground Test Program. All data presented in this document have been contractor-deidentified and approved for public release. The report prioritizes capabilities and recommends allocating those capabilities to either the Habitation and Logistics Outpost (HALO) or the International Habitat (I-Hab). A review of the design guidelines is presented in the main body of the report, along with a list of the 170 specific design guidelines with references to the specific data sources from which they were derived