Mechanisms for improving information quality in smartphone crowdsensing systems

Given its potential for a large variety of real-life applications, smartphone crowdsensing has recently gained tremendous attention from the research community. Smartphone crowdsensing is a paradigm that allows ordinary citizens to participate in large-scale sensing surveys by using user-friendly applications installed in their smartphones. In this way, fine-grained sensing information is obtained from smartphone users without employing fixed and expensive infrastructure, and with negligible maintenance costs. Existing smartphone sensing systems depend completely on the participants\u27 willingness to submit up-to-date and accurate information regarding the events being monitored. Therefore, it becomes paramount to scalably and effectively determine, enforce, and optimize the information quality of the sensing reports submitted by the participants. To this end, mechanisms to improve information quality in smartphone crowdsensing systems were designed in this work. Firstly, the FIRST framework is presented, which is a reputation-based mechanism that leverages the concept of mobile trusted participants to determine and improve the information quality of collected data. Secondly, it is mathematically modeled and studied the problem of maximizing the likelihood of successful execution of sensing tasks when participants having uncertain mobility execute sensing tasks. Two incentive mechanisms based on game and auction theory are then proposed to efficiently and scalably solve such problem. Experimental results demonstrate that the mechanisms developed in this thesis outperform existing state of the art in improving information quality in smartphone crowdsensing systems --Abstract, page iii

Studying user behavior through a participatory sensing framework in an urban context

A thesis submitted in partial fulfillment of the requirements for the degree of Doctor in Information Management, specialization in Geographic Information SystemsThe widespread use of mobile devices has given birth to participatory sensing, a data collection approach leveraging the sheer number of device users, their mobility, intelligence and device’s increasingly powerful computing and sensing capabilities. As a result, participatory sensing is able to collect various types of information at a high spatial and temporal resolution and it has many applications ranging from measuring cellular signal strength or road condition monitoring to observing the distribution of birds. However, in order to achieve better results from participatory sensing, some issues needed to be dealt with. On a high level, this thesis addressed two issues: (1) the design and development of a participatory sensing framework that allows users to flexibly create campaigns and at the same time collect different types of data and (2) the study of different aspects of the user behaviors in the context of participatory sensing. In particular, the first contribution of the thesis is the design and development of Citizense, a participatory sensing framework that facilitates flexible deployments of participatory sensing campaigns while at the same time providing intuitive interfaces for users to create sensing campaigns and collect a variety of data types. During the real-world deployments of Citizense, it has shown its effectiveness in collecting different types of urban information and subsequently received appreciation from different stakeholders. The second contribution of the thesis is the in-depth study of user behavior under the presence of different monetary incentive mechanisms and the analysis of the spatial and temporal user behavior when participants are simultaneously exposed to a large number of participatory sensing campaigns. Concerning the monetary incentive, it is observed that participants prefer fixed micro-payment to other mechanisms (i.e., lottery, variable micro-payment); their participation was increased significantly when they were given this incentive. When taking part in the participatory sensing process, participants exhibit certain spatial and temporal behaviors. They tend to primarily contribute in their free time during the working week, although the decision to respond and complete a particular participatory sensing campaign seems to be correlated to the campaign’s geographical context and/or the recency of the participants’ activities. Participants can be divided into two groups according to their behaviors: a smaller group of active participants who frequently perform participatory sensing activities and a larger group of regular participants who exhibit more intermittent behaviors

Redes autónomas e inteligentes para la monitorización de variables ambientales

El entendimiento de nuestro entorno, ya sea urbano o natural, es un tema de constante interés en la sociedad, tanto por razones de mejora de calidad de vida como preservación ecológica. En las últimas décadas, la tecnología ha sido la principal aliada para lograr este objetivo, siendo uno de los principales contribuyentes las redes de sensores inalámbricos, o WSN por sus siglas en inglés. No obstante, sigue existiendo una fuerte necesidad de monitorización en distintas temáticas, además que los avances tecnológicos recientes permiten profundizar en el conocimiento en algunas áreas de estudio. En este sentido, este trabajo pretende evaluar la tecnología de WSN reciente con el fin de diseñar y desarrollar sistemas que aporten soluciones a problemáticas reales. Por consiguiente, con el conocimiento obtenido a partir de lo anterior, se busca también contribuir a las WSN en un sentido científico literario. Dicho lo anterior, la presente tesis realiza aportaciones en dos campos: el tecnológico y el metodológico. Desde una perspectiva técnica, se presenta la implementación de un sistema autónomo para monitorización en viviendas y un sistema de monitorización no supervisado para zonas ecológicas marinas protegidas. El primero busca cubrir una necesidad de estimación del consumo energético-térmico de los sistemas de calefacción, con el cual poder gestionar de mejor manera este recurso. Para ello se desarrolló el prototipo de un nodo sensor WiFi de bajo consumo energético, capaz de sustentar su demanda de potencia con una etapa de energy harvesting termoeléctrico. Se utilizó este enfoque para poder ofrecer una solución intuitiva con poca interacción por parte de los usuarios. Con respecto al segundo, se pretende proveer una alternativa a los sistemas de monitorización de líneas costeras, donde se busca realizar análisis de corrientes marinas superficiales y variables físicas del entorno. Para este desarrollo fue necesario que el sistema pudiese ser desplegado de la manera más sencilla posible, minimizando el impacto en el entorno dada su clasificación como parque nacional protegido. Por estos motivos se diseñó, desarrolló e implementó una red de boyas de deriva asistida por dron, donde las primeras actuaban como nodos sensores y el dron ejercía como recolector de datos remoto, utilizando un protocolo de comunicaciones inalámbrico basado en la modulación LoRa.En tema de aportaciones metodológicas, se realizó una recopilación literaria de métricas para el análisis, selección y diseño de una WSN, con el afán de definir el impacto que estas presentan en dicha labor. Esto a su vez propició el desarrollo de una propuesta de metodología aplicable a nuevas implementaciones o sistemas activos con posibles mejoras. La metodología se realizó con el objetivo de proveer una serie de directrices claras al momento de diseñar una WSN, buscando también cubrir los aspectos más relevantes de estas mismas, es decir, la parte de hardware, red y requerimientos de una aplicación. Aunado a lo anterior, se ejemplifica el uso de dicha metodología, aplicada a tres escenarios tecnológicos distintos, para demostrar la relevancia de un diseño apropiado de una WSN.<br /

Mapping and the Citizen Sensor

Maps are a fundamental resource in a diverse array of applications ranging from everyday activities, such as route planning through the legal demarcation of space to scientific studies, such as those seeking to understand biodiversity and inform the design of nature reserves for species conservation. For a map to have value, it should provide an accurate and timely representation of the phenomenon depicted and this can be a challenge in a dynamic world. Fortunately, mapping activities have benefitted greatly from recent advances in geoinformation technologies. Satellite remote sensing, for example, now offers unparalleled data acquisition and authoritative mapping agencies have developed systems for the routine production of maps in accordance with strict standards. Until recently, much mapping activity was in the exclusive realm of authoritative agencies but technological development has also allowed the rise of the amateur mapping community. The proliferation of inexpensive and highly mobile and location aware devices together with Web 2.0 technology have fostered the emergence of the citizen as a source of data. Mapping presently benefits from vast amounts of spatial data as well as people able to provide observations of geographic phenomena, which can inform map production, revision and evaluation. The great potential of these developments is, however, often limited by concerns. The latter span issues from the nature of the citizens through the way data are collected and shared to the quality and trustworthiness of the data. This book reports on some of the key issues connected with the use of citizen sensors in mapping. It arises from a European Co-operation in Science and Technology (COST) Action, which explored issues linked to topics ranging from citizen motivation, data acquisition, data quality and the use of citizen derived data in the production of maps that rival, and sometimes surpass, maps arising from authoritative agencies

Mapping and the citizen sensor

Maps are a fundamental resource in a diverse array of applications ranging from everyday activities, such as route planning through the legal demarcation of space to scientific studies, such as those seeking to understand biodiversity and inform the design of nature reserves for species conservation. For a map to have value, it should provide an accurate and timely representation of the phenomenon depicted and this can be a challenge in a dynamic world. Fortunately, mapping activities have benefitted greatly from recent advances in geoinformation technologies. Satellite remote sensing, for example, now offers unparalleled data acquisition and authoritative mapping agencies have developed systems for the routine production of maps in accordance with strict standards. Until recently, much mapping activity was in the exclusive realm of authoritative agencies but technological development has also allowed the rise of the amateur mapping community. The proliferation of inexpensive and highly mobile and location aware devices together with Web 2.0 technology have fostered the emergence of the citizen as a source of data. Mapping presently benefits from vast amounts of spatial data as well as people able to provide observations of geographic phenomena, which can inform map production, revision and evaluation. The great potential of these developments is, however, often limited by concerns. The latter span issues from the nature of the citizens through the way data are collected and shared to the quality and trustworthiness of the data. This book reports on some of the key issues connected with the use of citizen sensors in mapping. It arises from a European Co-operation in Science and Technology (COST) Action, which explored issues linked to topics ranging from citizen motivation, data acquisition, data quality and the use of citizen derived data in the production of maps that rival, and sometimes surpass, maps arising from authoritative agencies

Crowd-sensing for smart city applications: towards solving crowd-sensing data challenges by introducing edge and cloud services

Crowd-sensing is the ability of a crowd to utilize sensors embedded in mobile devices to sense the surroundings and then send data to a centralized server or the cloud. With crowd-sensing, a wide range of applications have been empowered, such as smart city, healthcare and marketing, of which the smart city is the domain of interest in this research. However, sending a large amount of data to the cloud has introduced several challenges, such as data truthfulness, redundancy, transfer cost, bandwidth consumption and the way data are stored and managed in the cloud. This thesis presents a crowd-sensing architecture for smart city applications. This architecture contains several services that play a key role in solving a number of the challenges listed earlier. Services are distributed between the cloud and public local servers. The local servers are distributed around a city to improve citizens’ quality of life. Services located on public local servers are called edge services and are concerned with trust, the scheduler and compression. Services located in the cloud are known as cloud services and contain a partitioning method along with two reduction techniques: optimization and context extraction. The trust service calculates trust using different factors. Then, if the trust value is above a predefined threshold, data are trusted; otherwise, they are discarded. The scheduler removes redundant data and schedules sending data to the cloud depending on their priority. The compression service compresses single precision floating-point data using two lossless compression algorithms. The partitioning method in the cloud highlights the importance of data entries using time, access rate and singularity factors. Then, based on the output of this method, users can apply optimization and context extraction to optimize data entries and extract important information, respectively. The order in which these services are performed and how they work and communicate are presented. Evaluations and use cases are performed on the mobile, local server and the cloud using Android-based mobile devices and the Amazon EC2 cloud. The results show the effectiveness of the proposed work by meeting predefined requirements, such as reducing the amount of the data transferred