Developing Cyber-Physical Systems requires methods and tools to support simulation and verification of hybrid (both continuous and discrete) models. The Acumen modeling and simulation language is an open source testbed for exploring the design space of what rigorous-but-practical next-generation tools can deliver to developers of Cyber-Physical Systems. Like verification tools, a design goal for Acumen is to provide rigorous results. Like simulation tools, it aims to be intuitive, practical, and scalable. However, it is far from evident whether these two goals can be achieved simultaneously. This paper explains the primary design goals for Acumen, the core challenges that must be addressed in order to achieve these goals, the “agile research method” taken by the project, the steps taken to realize these goals, the key lessons learned, and the emerging language design.
In this paper I present the paradigm shift occurred in recent years in the approach to technology development within the European Commission funded Research and Innovation frameworks. This new approach is attentive to social good, societal challenges and bottom-up users and stakeholders, but presents at the same time some limitations. By leveraging Sigma Orionis long-standing experience in European funded projects and highlighting the current trends, challenges and best practices, I identify some avenues for making this approach even more impactful in the coming years.
In order to deter bike thieves, we have designed and implemented a theft prevention system for bicycles based on RFID technology. Bikes can be stored in areas monitored by custom designed base stations without the need for visual or contact identification. The system is implemented with Web of Things technology, using a RESTful and a streaming server API, to facilitate communication between the embedded electronics and the back end service. The system is tested by deploying RFID technology in several environments to determine the viability of the platform.
In order to support navigation, gesture detection, and augmented reality, modern smartphones contain inertial measurement units (IMU) consisting of accelerometers and gyroscopes. Although the accuracy of these sensors directly affects the soundness of mobile applications, no standardized tests exist to verify the correctness of the retrieved sensor data. For this purpose, we present a novel benchmark, which utilizes the camera of the phone as a reference to estimate the quality of its sensor data fusion. Our experiments do not require special equipment and reveal significant discrepancies between different phone models.
This paper attempts to project a novel concept where medical sensors, cloud computing and robotic platform are unified to offer state-of-the-art healthcare solutions to a wide variety of scenarios. The proposed solution is most effective if there is scarcity of healthcare providers or if putting them in the field expose them into a high risk environment such as fighting epidemics. In addition, the proposed system will also benefit routine checks in quarantine wards of hospitals where human reluctance of performing routine task by the healthcare providers can be avoided. Finally, it can also assist a doctor as a decision support system by using machine's capability of number crunching while it examines through patient's complete history, goes through every medical test reports and then applies data mining for catching possible ailments from his/her symptoms.
This work presents a paradigm shift and introduces a data-centric security architecture for the COMPOSE framework; a platform as a service and marketplace for the IoT. We distinguish our approach from classical device-centric approaches and outline architectural as well as infrastructural specifics of our platform. In particular, we describe how fine-granular and data-centric security requirements can be combined with static and dynamic enforcement to regain governance on devices and data without sacrificing the intrinsic openness of IoT platforms. We also highlight the power of our architecture, converting concepts such as data provenance and reputation into efficient, highly useful, and practically applicable complements.
The satisfaction of security and data quality requirements plays a fundamental role in the Internet of Things (IoT) scenario. Such a dynamic environment requires the adoption of heterogeneous technologies to provide customized services in various application domains and both security threats and data quality issues need to be addresses in order to guarantee an effective and efficient data management. In this paper, a lightweight and cross-domain prototype of distributed architecture for IoT is presented and evaluated by means of open data provided by different sources. We show how users can access different types of data by changing security and quality requirements.
In this paper, the feasibility of a single integrated autonomous device equipped with WiFI capability is analyzed, discussing its potentiality in the framework of the Internet of Things and Cyber Physical Systems. By equipping photovoltaic panels with sensors and antennas, it is possible to obtain a single stand-alone wireless network node. Specifically, integration of a number of antennas in a large solar panel is suitable to obtain an integrated antenna array. Thus, beamforming techniques can be implemented to electronically orient the array maximum gain radiation, so improving the point-to-point network link.
Today, Wireless Sensor Networks (WSNs) with open source operating systems still need many efforts to guarantee that the protocol stack succeeds in delivering its expected performance. This is due to subtle implementation problems and unexpected interactions between protocol layers. The subtleties are often related to the judicious choice of parameters, in particular those related to timing issues. As these issues are often not visible in simulation studies, this paper proposes a low-cost versatile measurement testbed and demonstrates its usefulness in measuring the performance of RDC protocols. We demonstrate how the testbed helped to identify bugs in the implementation of an RDC protocol.
In this paper, we propose a zone-based living activity recognition method. The proposed method introduces a new concept called activity zone which represents the location and the area of an activity that can be done by a user. By using this activity zone concept, the proposed scheme uses Markov Logic Network (MLN) which integrates a common sense knowledge (i.e. area of each activity) with a probabilistic model. The proposed scheme can utilize only a positioning sensor attached to a resident with/without power meters attached to appliances of a smart environment. We target 10 different living activities which cover most of our daily lives at a smart environment and construct activity recognition models. Through experiments using sensor data collected by four participants in our smart home, the proposed scheme achieved average F-measure of recognizing 10 target activities starting from 84.14
Decision Support Systems can enhance e-Health monitoring and IoT scenarios on the early detection of neurodevelopmental disorders in children. Thus, Ambient Intelligence could support innovative application domains like motor or cognitive impairments' detection at the home environment. The paper describes the design of an innovative cooperative system (Galatea) that supports the refinement process of a Knowledge Base expressed as an OWL ontology. The ontology supports decision-making process and is the core of: (1) a Web-Based Smart System aimed to enhance the screening of language disorders at medical centers and schools by fostering the identification of a developmental disorders before 4 years old of age; (2) a set of child smart care services that use Ambient Intelligent paradigm for early attention of motor impairments in children who are often not diagnosed or treated by health care entities.
Physiological parameters such as Heart Rate (HR), Beat-to-Beat Interval (IBI) and Respiration Rate (RR) are vital indicators of people's physiological state and important to monitor. However, most of the measurements methods are connection based, i.e. sensors are connected to the body which is often complicated and requires personal assistance. This paper proposed a simple, low-cost and non-contact approach for measuring multiple physiological parameters using a web camera in real time. Here, the heart rate and respiration rate are obtained through facial skin colour variation caused by body blood circulation. Three different signal processing methods such as Fast Fourier Transform (FFT), independent component analysis (ICA) and Principal component analysis (PCA) have been applied on the colour channels in video recordings and the blood volume pulse (BVP) is extracted from the facial regions. HR, IBI and RR are subsequently quantified and compared to corresponding reference measurements. High degrees of agreement are achieved between the measurements across all physiological parameters. This technology has significant potential for advancing personal health care and telemedicine.
Interoperability within the Internet of Things is mired in entrenched incompatible specifications, backed by industry giants and consortiums seemingly hoping to “win the stack”. There is little hope that a common set of standards will be universally adopted that will allow all our Things to work together. However, by applying some of the core lessons of the Internet - use URIs for IDs, manipulate documents using the REST Model, and that documents should be “JSON-like” dictionary - we can create near seamless interoperability between Things independent of their standards stack.
This paper presents an IoT architecture for the semantic interoperability of diverse IoT systems and applications in smart cities. The architecture virtualizes diverse IoT systems and ensures their modelling and representation according to common standards-based IoT ontologies. Furthermore, based on this architecture, the paper introduces a first-of-a-kind visual development environment which eases the development of semantically interoperable applications in smart citites. The development environment comes with a range of visual tools, which enable the assembly of non-trivial data-driven applications in smart cities, including applications that leverage data streams from diverse IoT systems. Moreover, these tools allow developers to leverage the functionalities and building blocks of the presented architecture. Overall, the introduced visual environment advances the state of the art in IoT developments for smart cities towards the direction of semantic interoperability for data driven applications.
Popular test automation frameworks target the enterprise application testing but there is scarcity of test automation framework for device applications, especially for IoT domain. IoT testing paradigm throws a new set of challenges involving device integration, protocol adapters, task actuation, data integrity, security and non functional requirements. In this paper, we propose a scalable, lightweight device task actuation framework for IoT testing based on TCS Connected Universe Platform Device Management enabler. This framework can execute test suite on multiple remote devices spread across geographies and then show the results on the IoT tester's screen. Moreover it has the ability to gather runtime device statistics during test execution, thus can do dynamic health check for IoT devices deployed on field.
Understanding the sentiment of people is a process that may be useful when transforming a city into a smart city. A recent trend is to exploit social media data to infer people sentiments. While many studies focused on textual data, few considered the visual contents. In this paper we investigate whether the images available in the Instagram platform can be useful to understand people sentiments. Through an experimental assessment and two different validation methods, we observed that although the use of images in sentiment analysis can be useful to have insights about people sentiments, the use of Instagram images may be slightly misleading.
Travel information brokers are complex systems, dealing with a large amount of heterogeneous data from various sources. The exchange and integration of such data is therefore demanding, particularly for small mobility service providers with few IT resources. To face this problem, this work illustrates a key tool to support information and service integration. On a conceptual level, we present a travel information broker system architecture and respective information flows. Additionally, we describe data exchange related to system components, e.g., intermodal routing, pricing and accounting. On this basis, we developed and tested a communication adapter that enables and eases communication between the core system and second party service providers. Furthermore we outline the method of extending public transportation routing with information about sharing services. This enables travelers to query combined information about public transport, bikesharing as well as carsharing services using a single application.
This paper suggests an internet-based tool for cardiac diagnosis in children. The main focus of the paper is the intelligent algorithms for processing heart sounds that are implementable on an internet platform. The algorithms are based on the statistical classification methods, tailored for the heart sound signal processing. The algorithms, applied to 55 healthy and 45 children with congenital heart diseases. The accuracy of the algorithm is estimated to be 86.0
The advent of both Cloud computing and Internet of Things (IoT) is changing the way of conceiving information and communication systems. Generally, we talk about IoT Cloud to indicate a new type of distributed system consisting of a set of smart devices interconnected with a remote Cloud infrastructure, platform, or software through the Internet and able to provide IoT as a Service (IoTaaS). In this paper, we address such a challenging paradigm focusing on security in IoT Cloud Federation. In particular, we discuss several authentication schemes fitting different types of scenarios.
This article describes the design and development of an open data platform that was implemented as part of the Smart Health framework and aimed at supporting the development of Recreational Bike Path applications. Recreational Bike Path programs follow the guidelines of the World Health Organization and seek to reduce the appearance of Chronic Noncommunicable Diseases; these programs, although having great potential, do not have a source of data to investigate their impact or motivate public investment. This paper presents the design of a platform for integrating data through a service REST API by considering Smart Cities architectures as a reference. The final product features an extensible platform that supports basic functionalities, has the capability to integrate other APIs and has the ability to generate open data datasets while following the "Guidelines for the implementation of open data in Colombia".
