Andrea Vinci

On the Design of Smart Homes: A Framework for Activity Recognition in Home Environment

A smart home is a home environment enriched with sensing, actuation, communication and computation capabilities which permits to adapt it to inhabitants preferences and requirements. Establishing a proper strategy of actuation on the home environment can require complex computational tasks on the sensed data. This is the case of activity recognition, which consists in retrieving high-level knowledge about what occurs in the home environment and about the behaviour of the inhabitants. The inherent complexity of this application domain asks for tools able to properly support the design and implementation phases. This paper proposes a framework for the design and implementation of smart home applications focused on activity recognition in home environments. The framework mainly relies on the Cloud-assisted Agent-based Smart home Environment (CASE) architecture offering basic abstraction entities which easily allow to design and implement Smart Home applications. CASE is a three layered architecture which exploits the distributed multi-agent paradigm and the cloud technology for offering analytics services. Details about how to implement activity recognition onto the CASE architecture are supplied focusing on the low-level technological issues as well as the algorithms and the methodologies useful for the activity recognition. The effectiveness of the framework is shown through a case study consisting of a daily activity recognition of a person in a home environment.

An edge-based platform for dynamic Smart City applications

Abstract A Smart City is a cyber–physical system improving urban behavior and capabilities by providing ICT-based functionalities. An infrastructure for Smart City has to be geographically and functionally extensible, as it requires both to grow up with the physical environment and to meet the increasing in needs and demands of city users/inhabitants. In this paper, we propose iSapiens, an IoT-based platform for the development of general cyber–physical systems suitable for the design and implementation of smart city services and applications. As distinguishing features, the iSapiens platform implements the edge computing paradigm through both the exploitation of the agent metaphor and a distributed network of computing nodes directly scattered in the urban environment. The platform promotes the dynamic deployment of new computing nodes as well as software agents for addressing geographical and functional extensibility. iSapiens provides a set of abstractions suitable to hide the heterogeneity of the physical sensing/actuator devices embedded in the system, and to support the development of complex applications. The paper also furnishes a set of methodological guidelines exploitable for the design and implementation of smart city applications by properly using iSapiens. As a significant case study, the design and implementation of a real Smart Street in the city of Cosenza (Italy) are shown, which provides decentralized urban intelligence services to citizens.

A distributed real-time approach for mitigating CSO and flooding in urban drainage systems

In an urban environment, sewer flooding and combined sewer overflows (CSOs) are a potential risk to human life, economic assets and the environment. To mitigate such phenomena, real time control systems represent a valid and cost-effective solution. This paper proposes an urban drainage network equipped by sensors and a series of electronically movable gates controlled by a decentralized real-time system based on a gossip-based algorithm which exhibits good performance and fault tolerance properties. The proposal aims to exploit effectively the storage capacity of the urban drainage network so as to reduce flooding and CSO. The approach is validated by considering the urban drainage system of the city of Cosenza (Italy) and a set of extreme rainfall events as a testbed. Experiments are conducted by using a customized version of the SWMM simulation software and show that the CSO and local flooding volumes are significantly reduced. HighlightsWe propose a distributed real-time control of urban drainage system.A gossip-based algorithm is exploited together with local PID controllers.The case study confirms the approach reduces effectively local flooding and overflow.

Smart Agents and Fog Computing for Smart City Applications

New Internet of Things IoT applications that leverage ubiquitous connectivity, big data and analytics are enabling Smart City initiatives all over the world. These new applications introduce tremendous new capabilities such as the ability to monitor, manage and control devices remotely, and to create new insights and actionable information from massive streams of real-time data. Supporting this new approach requires the adoption of new paradigms. In this paper, agent tecnology is combined with the emergent concept of Fog computing to design control systems based on the decentralization of control functions over distributed autonomous and cooperative entities that are running at the edge of the network. We describe the Rainbow platform that is designed to bring computation as close as possible to the physical part. Multi-agent systems running on top of Rainbow create smart services using adaptive and decentralized algorithms which exploit the principles of collective intelligence.

Metamodeling of Smart Environments: from design to implementation

Abstract A smart environment is a physical environment enriched with sensing, actuation, communication and computation capabilities aiming at acquiring and exploiting knowledge about the environment so as to adapt itself to its inhabitants’ preferences and requirements. In this domain, there is the need of tools supporting the design and analysis of applications. In this paper, the Smart Environment Metamodel (SEM) framework is proposed. The framework allows to model applications by exploiting concepts specific to the smart environment domain. SEM approaches the modeling from two different points of view, namely the functional and data perspectives. The application of the framework is supported by a set of general guidelines to drive the analysis, the design and the implementation of smart environments. The effectiveness of the framework is shown by applying it to the modeling of a real smart office scenario that has been developed, deployed and analyzed.

A Cyber-Physical System for Distributed Real-Time Control of Urban Drainage Networks in Smart Cities

This paper focuses on a distributed real time control approach applied to drainage networks. The increasing of urbanization and climate change heightens the challenge for new technologies to be developed for drainage networks. Higher runoff volume, produced by the increase in impervious surfaces and intense rain events, overwhelms the existing urban drainage systems. Recent technical improvements have enabled the exploitation of real-time control on drainage networks. The novelty in this paper regards the use of a totally decentralized approach based on a proper combination of a Gossip-based algorithm, which ensures a global correct behaviour even if local faults occur, and a classic controlling technique (PID) used for local actuations.

A Data Analytics Schema for Activity Recognition in Smart Home Environments

Recent advancements in the fields of embedded systems, communication technologies and computer science open up to new application scenarios in the home environment. Anyway, many issues raised from the inherent complexity of this new application domain need to be properly tackled. This paper proposes the Cloud-assisted Agent-based Smart home Environment (CASE) architecture for activity recognition with sensors capturing the data related to activities being performed by humans and objects in the environment. Moreover, the potential of analytics methods for discovering activity recognition in such environment has been investigated. CASE easily allows to implement Smart Home applications exploiting a distributed multi-agent system and the cloud technology. The work is mainly focused on activity recognition albeit CASE architecture permits an easy integration of other kinds of smart home applications such as home automation and energy optimization. The CASE effectiveness is shown through the design of a case study consisting of a daily activity recognition of an elder person in its home environment.

Pattern Detection in Cyber-Physical Systems.

Abstract A Cyber-Physical System (CPS) integrates physical devices (i.e., sensors) with cyber (i.e., informational) components to form a context sensitive system that responds intelligently to dynamic changes in real-world situations. A core element of CPS is the collection and assessment of information from noisy, dynamic, and uncertain physical environments that must be transformed into usable knowledge in real-time. Machine learning algorithms such as cluster analysis can be used to extract useful information and patterns from data generated from physical devices based on which novel applications of CPS can make informed decisions. In this paper we propose to use a density-based data stream clustering algorithm, built on the Multiple Species Flocking model, for the monitoring of big data, generated from numerous applications such as machine monitoring, health monitoring, sensor networks. In the proposed approach, approximate results are available on demand at anytime, so it is particularly apt for real life monitoring applications.

iSapiens: A platform for social and pervasive smart environments

The advent of Internet of Things (IoT) has fueled the implementation of Smart Environments (SEs) where the information made available by the “Things” is processed and utilized to increase the livability, the safety and the security of the environment, and to make easier the life of its inhabitants. In literature there are many attempts to create specific SEs or platform for the SEs realization. Although effective, these solutions lack of interoperability with other third-part “Things”. In this paper we propose iSapiens, a Java-based platform for the design and the implementation of SEs. iSapiens deals with the above mentioned limitation by leveraging the Social Internet of Things (SIoT) paradigm to dynamically include in a SE newly available “Things” without requiring any human intervention. iSapiens allows the creation of pervasive smart environments by exploiting the edge computing paradigm, that makes locally available distributed storage and computational resources without introducing latency and causing bandwidth shortage.

An edge-based approach to develop large-scale smart environments by leveraging SIoT

Large-scale Smart Environments (LSEs) are open and dynamic systems where issues related to scalability and interoperability require to be carefully addressed. Moreover, as such systems typically extend on a wide area and include a huge number of interacting devices, aspects concerning services and objects discovery and reputation assessment require being managed. Despite the increasing interest in this topic, there is a lack of approaches for developing LSEs. This paper proposes an agent-based approach for the development of LSEs which leverages Edge Computing and Social Internet of Things paradigms in order to address the above mentioned issues. The effectiveness of such an approach is assessed through a case study involving a Smart School District environment.