Smart objects as building blocks for the internet of things

The combination of the Internet and emerging technologies such as nearfield communications, real-time localization, and embedded sensors lets us transform everyday objects into smart objects that can understand and react to their environment. Such objects are building blocks for the Internet of Things and enable novel computing applications. As a step toward design and architectural principles for smart objects, the authors introduce a hierarchy of architectures with increasing levels of real-world awareness and interactivity. In particular, they describe activity-, policy-, and process-aware smart objects and demonstrate how the respective architectural abstractions support increasingly complex application

A Platform for the Analysis of Qualitative and Quantitative Data about the Built Environment and its Users

There are many scenarios in which it is necessary to collect data from multiple sources in order to evaluate a system, including the collection of both quantitative data - from sensors and smart devices - and qualitative data - such as observations and interview results. However, there are currently very few systems that enable both of these data types to be combined in such a way that they can be analysed side-by-side. This paper describes an end-to-end system for the collection, analysis, storage and visualisation of qualitative and quantitative data, developed using the e-Science Central cloud analytics platform. We describe the experience of developing the system, based on a case study that involved collecting data about the built environment and its users. In this case study, data is collected from older adults living in residential care. Sensors were placed throughout the care home and smart devices were issued to the residents. This sensor data is uploaded to the analytics platform and the processed results are stored in a data warehouse, where it is integrated with qualitative data collected by healthcare and architecture researchers. Visualisations are also presented which were intended to allow the data to be explored and for potential correlations between the quantitative and qualitative data to be investigated

Daily Stress Recognition from Mobile Phone Data, Weather Conditions and Individual Traits

Research has proven that stress reduces quality of life and causes many diseases. For this reason, several researchers devised stress detection systems based on physiological parameters. However, these systems require that obtrusive sensors are continuously carried by the user. In our paper, we propose an alternative approach providing evidence that daily stress can be reliably recognized based on behavioral metrics, derived from the user's mobile phone activity and from additional indicators, such as the weather conditions (data pertaining to transitory properties of the environment) and the personality traits (data concerning permanent dispositions of individuals). Our multifactorial statistical model, which is person-independent, obtains the accuracy score of 72.28% for a 2-class daily stress recognition problem. The model is efficient to implement for most of multimedia applications due to highly reduced low-dimensional feature space (32d). Moreover, we identify and discuss the indicators which have strong predictive power.Comment: ACM Multimedia 2014, November 3-7, 2014, Orlando, Florida, US

Distributed Hybrid Simulation of the Internet of Things and Smart Territories

This paper deals with the use of hybrid simulation to build and compose heterogeneous simulation scenarios that can be proficiently exploited to model and represent the Internet of Things (IoT). Hybrid simulation is a methodology that combines multiple modalities of modeling/simulation. Complex scenarios are decomposed into simpler ones, each one being simulated through a specific simulation strategy. All these simulation building blocks are then synchronized and coordinated. This simulation methodology is an ideal one to represent IoT setups, which are usually very demanding, due to the heterogeneity of possible scenarios arising from the massive deployment of an enormous amount of sensors and devices. We present a use case concerned with the distributed simulation of smart territories, a novel view of decentralized geographical spaces that, thanks to the use of IoT, builds ICT services to manage resources in a way that is sustainable and not harmful to the environment. Three different simulation models are combined together, namely, an adaptive agent-based parallel and distributed simulator, an OMNeT++ based discrete event simulator and a script-language simulator based on MATLAB. Results from a performance analysis confirm the viability of using hybrid simulation to model complex IoT scenarios.Comment: arXiv admin note: substantial text overlap with arXiv:1605.0487

GeoCoin:supporting ideation and collaborative design with location-based smart contracts

Design and HCI researchers are increasingly working with complex digital infrastructures, such as cryptocurrencies, distributed ledgers and smart contracts. These technologies will have a profound impact on digital systems and their audiences. However, given their emergent nature and technical complexity, involving non-specialists in the design of applications that employ these technologies is challenging. In this paper, we discuss these challenges and present GeoCoin, a location-based platform for embodied learning and speculative ideating with smart contracts. In collaborative workshops with GeoCoin, participants engaged with location-based smart contracts, using the platform to explore digital `debit' and `credit' zones in the city. These exercises led to the design of diverse distributed-ledger applications, for time-limited financial unions, participatory budgeting, and humanitarian aid. These results contribute to the HCI community by demonstrating how an experiential prototype can support understanding of the complexities behind new digital infrastructures and facilitate participant engagement in ideation and design processes

Enabling High-Level Application Development for the Internet of Things

Application development in the Internet of Things (IoT) is challenging because it involves dealing with a wide range of related issues such as lack of separation of concerns, and lack of high-level of abstractions to address both the large scale and heterogeneity. Moreover, stakeholders involved in the application development have to address issues that can be attributed to different life-cycles phases. when developing applications. First, the application logic has to be analyzed and then separated into a set of distributed tasks for an underlying network. Then, the tasks have to be implemented for the specific hardware. Apart from handling these issues, they have to deal with other aspects of life-cycle such as changes in application requirements and deployed devices. Several approaches have been proposed in the closely related fields of wireless sensor network, ubiquitous and pervasive computing, and software engineering in general to address the above challenges. However, existing approaches only cover limited subsets of the above mentioned challenges when applied to the IoT. This paper proposes an integrated approach for addressing the above mentioned challenges. The main contributions of this paper are: (1) a development methodology that separates IoT application development into different concerns and provides a conceptual framework to develop an application, (2) a development framework that implements the development methodology to support actions of stakeholders. The development framework provides a set of modeling languages to specify each development concern and abstracts the scale and heterogeneity related complexity. It integrates code generation, task-mapping, and linking techniques to provide automation. Code generation supports the application development phase by producing a programming framework that allows stakeholders to focus on the application logic, while our mapping and linking techniques together support the deployment phase by producing device-specific code to result in a distributed system collaboratively hosted by individual devices. Our evaluation based on two realistic scenarios shows that the use of our approach improves the productivity of stakeholders involved in the application development

Averting Robot Eyes

Home robots will cause privacy harms. At the same time, they can provide beneficial services—as long as consumers trust them. This Essay evaluates potential technological solutions that could help home robots keep their promises, avert their eyes, and otherwise mitigate privacy harms. Our goals are to inform regulators of robot-related privacy harms and the available technological tools for mitigating them, and to spur technologists to employ existing tools and develop new ones by articulating principles for avoiding privacy harms. We posit that home robots will raise privacy problems of three basic types: (1) data privacy problems; (2) boundary management problems; and (3) social/relational problems. Technological design can ward off, if not fully prevent, a number of these harms. We propose five principles for home robots and privacy design: data minimization, purpose specifications, use limitations, honest anthropomorphism, and dynamic feedback and participation. We review current research into privacy-sensitive robotics, evaluating what technological solutions are feasible and where the harder problems lie. We close by contemplating legal frameworks that might encourage the implementation of such design, while also recognizing the potential costs of regulation at these early stages of the technology

A Racial Impact Analysis of HB 869/SB 274

Virginia is growing. Between 1990 and 2000, Virginia’s population rose by over 14% - the largest population growth experienced by the state in a single decade (Pollard, 2007). And the state continues to grow. It has been estimated that by 2030, Virginia’s total population may exceed 9.8 million people (Pollard, 2007). Along with population growth, land development has increased which in turn affects transportation, housing and job placement across the Commonwealth. In fact, in many parts of the state, development has outpaced population growth. According to Pollard, “If current patterns continue, Virginia will develop more land in the next 40 years than in the previous 400 years (p.8).” In an effort to curb sprawling development and decrease transportation expenditure, the Virginia General Assembly passed House Bill 3202 in 2007. One major outcome of this multifaceted legislation was the introduction of mandatory Urban Development Areas (UDAs). The goal of UDAs was for localities to concentrate growth and development in order to reduce the cost of transportation and increase opportunities to build multi-use developments and expand affordable housing. In 2012, the General Assembly passed House Bill 869 and Senate Bill 274 which effectively make UDAs no longer mandatory but optional for all localities in the Commonwealth. In this paper, we analyze the racial impact and explore the political history of HB 869/SB 274 while addressing the larger issue of sprawl across the Commonwealth. Smart Growth policies are known to positively impact the environment but they also positively impact low-income and minority communities by increasing access to housing, transportation and ultimately jobs. The story behind Urban Development Areas in the Commonwealth is one of politics and regulation but issues as critical as housing, transportation and job access should be focused much more on the citizens of the Commonwealth. The friction created by the UDA policy between the localities and the state has the potential to spark a statewide conversation about land use and more importantly - the need for people-centered solutions to a growing problem