41,147 research outputs found

    Sensing Human Activity for Smart Cities’ Mobility Management

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    Knowledge about human mobility patterns is the key element towards efficient mobility management. Traditionally, these data are collected by paper/phone household surveys or travel diaries and serve as input for transportation planning models. In this chapter, we report on current state-of-the-art techniques for sensing human activity and report on their applicability for smart city mobility management purposes. We particularly focus on the use of location-enabled devices and their potential towards replacing traditional data collection approaches. Furthermore, to illustrate applicability of smartphones as ubiquitous sensing devices we report on the use of Routecoach application that was used for mobility data collection in the city of Leuven, Belgium. We provide insights into lessons learned, ways in which collected data were used by different stakeholders, and identify existing gaps and future research needs in this field

    Editorial: Smart Objects and Technologies

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    Smart objects are entering everyday life and are heavily modifying it. Healthcare, communication, art, entertainment, safety, environment, education, democracy, and human rights, are just a few examples of scenarios that are radically changing thanks to the use of smart objects and technologies. In this context, the popularity of portable computing devices, such as smartphones, tablets, or smart watches combined with the emergence of many other small smart objects with computational, sensing and communication capabilities coupled with the popularity of social networks and new human-technology interaction paradigms is creating unprecedented opportunities for each of us to do something useful, ranging from a single person to the whole world. Furthermore, Internet of Things, Smart-cities, distributed sensing and Fog computing are representative examples of modern ICT paradigms that aim to describe a dynamic and globally cooperative infrastructure built upon objects intelligence and self-configuring capabilities. These connected objects are finding their way into our pockets, vehicles, urban areas and infrastructure, thus becoming the very texture of our society and providing us the possibility, but also the responsibility, to shape it

    Investigating IoT Middleware Platforms for Smart Application Development

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    With the growing number of Internet of Things (IoT) devices, the data generated through these devices is also increasing. By 2030, it is been predicted that the number of IoT devices will exceed the number of human beings on earth. This gives rise to the requirement of middleware platform that can manage IoT devices, intelligently store and process gigantic data generated for building smart applications such as Smart Cities, Smart Healthcare, Smart Industry, and others. At present, market is overwhelming with the number of IoT middleware platforms with specific features. This raises one of the most serious and least discussed challenge for application developer to choose suitable platform for their application development. Across the literature, very little attempt is done in classifying or comparing IoT middleware platforms for the applications. This paper categorizes IoT platforms into four categories namely-publicly traded, open source, developer friendly and end-to-end connectivity. Some of the popular middleware platforms in each category are investigated based on general IoT architecture. Comparison of IoT middleware platforms in each category, based on basic, sensing, communication and application development features is presented. This study can be useful for IoT application developers to select the most appropriate platform according to their application requirement

    Surveillance Risks in IoT Applied to Smart Cities

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    With the advent of the IoT, proximity sensor devices are installed in many places in smart cities. Without any regulation or social policy, they could lead to a super-surveillance network managed by multi-agent systems in the future. Such networks may be able to reduce accidents, risks, damage and errors. However, they also pose high risk of surveillance and data breaches, including hacking attacks or malware intrusion. This research project is aimed at investigating the implications of IoT-driven surveillance in smart cities from privacy, data protection and ethical perspectives. The identification of the critical issues related to the extensive deployment of such sensing devices in the urban area will constitute a starting point for the development of a new regulatory framework for sensor-based surveillance in European Smart Cities. This new regulatory system shall be aimed at providing citizens with effective tools to exercise their rights to privacy and data protection when facing IoT-driven surveillance. Indeed, setting a clear set of rules governing big urban data processing shall be considered crucial to ensure a fair, democratic, human-centric development of smart cities in Europe

    SoK: Inference Attacks and Defenses in Human-Centered Wireless Sensing

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    Human-centered wireless sensing aims to understand the fine-grained environment and activities of a human using the diverse wireless signals around her. The wireless sensing community has demonstrated the superiority of such techniques in many applications such as smart homes, human-computer interactions, and smart cities. Like many other technologies, wireless sensing is also a double-edged sword. While the sensed information about a human can be used for many good purposes such as enhancing life quality, an adversary can also abuse it to steal private information about the human (e.g., location, living habits, and behavioral biometric characteristics). However, the literature lacks a systematic understanding of the privacy vulnerabilities of wireless sensing and the defenses against them. In this work, we aim to bridge this gap. First, we propose a framework to systematize wireless sensing-based inference attacks. Our framework consists of three key steps: deploying a sniffing device, sniffing wireless signals, and inferring private information. Our framework can be used to guide the design of new inference attacks since different attacks can instantiate these three steps differently. Second, we propose a defense-in-depth framework to systematize defenses against such inference attacks. The prevention component of our framework aims to prevent inference attacks via obfuscating the wireless signals around a human, while the detection component aims to detect and respond to attacks. Third, based on our attack and defense frameworks, we identify gaps in the existing literature and discuss future research directions

    Functional-Material-Based Touch Interfaces for Multidimensional Sensing for Interactive Displays: A Review

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    Multidimensional sensing is a highly desired attribute for allowing human-machine interfaces (HMIs) to perceive various types of information from both users and the environment, thus enabling the advancement of various smart electronics/applications, e.g., smartphones and smart cities. Conventional multidimensional sensing is achieved through the integration of multiple discrete sensors, which introduces issues such as high energy consumption and high circuit complexity. These disadvantages have motivated the widespread use of functional materials for detecting various stimuli at low cost with low power requirements. This work presents an overview of simply structured touch interfaces for multidimensional (x-y location, force and temperature) sensing enabled by piezoelectric, piezoresistive, triboelectric, pyroelectric and thermoelectric materials. For each technology, the mechanism of operation, state-of-the-art designs, merits, and drawbacks are investigated. At the end of the article, the author discusses the challenges limiting the successful applications of functional materials in commercial touch interfaces and corresponding development trends
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