0000000000092674
AUTHOR
Fabrizio Milazzo
Investigating Avatar Influence on Perceived Cognitive Load and Bimanual Interactions with Touchless Interfaces
In recent years, touchless-enabling technologies have been more and more adopted for providing public displays with gestural interactivity. This has led to the need for novel visual interfaces aimed at solving issues such as communicating interactivity to users, as well as supporting immediate usability and "natural" interactions. In this paper, we focus our investigation on a visual interface based only on the use of in-air direct manipulations. Our study aims at evaluating whether and how the presence of an Avatar that replays user’s movements may decrease the perceived cognitive workload during interactions. Moreover, we conducted a brief evaluation of the relationship between the presen…
Real-time pricing for aggregates energy resources in the Italian energy market
Abstract Over the last decade, the architecture of the energy market has radically changed. In many countries end-users are now able to directly access the market, which has given rise to the question of how they can actively participate in that market. End-users can comprise a critical mass through aggregation that is carried out by a third party – to wit the “loads aggregator.” This paper proposes a new framework for generating feasible real-time price curves for those end-users in a demand-response management process. The underlying algorithm generates output curves as the solution to a constrained optimization problem whose objective function is the aggregator's economic benefit. A case…
KIND-DAMA: A modular middleware for Kinect-like device data management
In the last decades, we have witnessed a growing interest toward touchless gestural user interfaces. Among other reasons, this is due to the large availability of different low-cost gesture acquisition hardware (the so-called âKinect-like devicesâ). As a consequence, there is a growing need for solutions that allow to easily integrate such devices within actual systems. In this paper, we present KIND-DAMA, an open and modular middleware that helps in the development of interactive applications based on gestural input. We first review the existing middlewares for gestural data management. Then, we describe the proposed architecture and compare its features against the existing similar so…
Short-Term Sensory Data Prediction in Ambient Intelligence Scenarios
Predicting data is a crucial ability for resource-constrained devices like the nodes of a Wireless Sensor Network. In the context of Ambient Intelligence scenarios, in particular, short-term sensory data prediction becomes a key enabler for more difficult tasks such as prolonging network lifetime, reducing the amount of communication required and improving user-environment interaction. In this chapter we propose a software module designed for clustered wireless sensor networks, able to predict various environmental quantities, namely temperature, humidity and light. The software module is supported by an ontology that describes the topology of the AmI scenario and the effects of the actuato…
KIND-DAMA: A modular middleware for Kinect-like device data management
Summary In the last decades, we have witnessed a growing interest toward touchless gestural user interfaces. Among other reasons, this is due to the large availability of different low-cost gesture acquisition hardware (the so-called “Kinect-like devices”). As a consequence, there is a growing need for solutions that allow to easily integrate such devices within actual systems. In this paper, we present KIND-DAMA, an open and modular middleware that helps in the development of interactive applications based on gestural input. We first review the existing middlewares for gestural data management. Then, we describe the proposed architecture and compare its features against the existing simila…
Exploiting Correlation between Body Gestures and Spoken Sentences for Real-time Emotion Recognition
Humans communicate their affective states through different media, both verbal and non-verbal, often used at the same time. The knowledge of the emotional state plays a key role to provide personalized and context-related information and services. This is the main reason why several algorithms have been proposed in the last few years for the automatic emotion recognition. In this work we exploit the correlation between one's affective state and the simultaneous body expressions in terms of speech and gestures. Here we propose a system for real-time emotion recognition from gestures. In a first step, the system builds a trusted dataset of association pairs (motion data -> emotion pattern), a…
Plantxel: Towards a plant-based controllable display
The use of plants as a mean for both visualization and interaction has been already explored in smart environments. In this work, we explore the possibility of constructing a controllable dynamic plant-based display using thigmonastic plants, i.e. plants that change the shape and position of their leaves as a response to external stimuli. As an initial step towards this vision, we first introduce our approach of building a plant-based pixel (plant-pixel, or plantxel), and the principles of composing a plantxel-based public display. We then present the results of a feasibility study conducted with Mimosa spegazzinii plants, showing that our approach can achieve an acceptable contrast ratio, …
Body Gestures and Spoken Sentences: A Novel Approach for Revealing User’s Emotions
In the last decade, there has been a growing interest in emotion analysis research, which has been applied in several areas of computer science. Many authors have con- tributed to the development of emotion recognition algorithms, considering textual or non verbal data as input, such as facial expressions, gestures or, in the case of multi-modal emotion recognition, a combination of them. In this paper, we describe a method to detect emotions from gestures using the skeletal data obtained from Kinect-like devices as input, as well as a textual description of their meaning. The experimental results show that the correlation existing between body movements and spoken user sentence(s) can be u…
A touchless gestural system for extended information access within a campus
In the last two decades, we have witnessed a growing spread of touchless interfaces, facilitated by higher performances of computational systems, as well as the increased availability of cheaper sensors and devices. Putting the focus on gestural input, several researchers and designers used Kinect-like devices to implement touchless gestural interfaces. The latter extends the possible deployments and usage of public interactive displays. For example, wall-sized displays may become interactive even if they are unreachable by touch. Moreover, billboard-sized displays may be placed in safe cases to avoid vandalism, while still maintaining their interactivity. Finally, people with temporary or …
Real-Time Body Gestures Recognition Using Training Set Constrained Reduction
Gesture recognition is an emerging cross-discipline research field, which aims at interpreting human gestures and associating them to a well-defined meaning. It has been used as a mean for supporting human to machine interaction in several applications of robotics, artificial intelligence, and machine learning. In this paper, we propose a system able to recognize human body gestures which implements a constrained training set reduction technique. This allows the system for a real-time execution. The system has been tested on a publicly available dataset of 7,000 gestures, and experimental results have highlighted that at the cost of a little decrease in the maximum achievable recognition ac…
Adaptive distributed outlier detection for WSNs.
The paradigm of pervasive computing is gaining more and more attention nowadays, thanks to the possibility of obtaining precise and continuous monitoring. Ease of deployment and adaptivity are typically implemented by adopting autonomous and cooperative sensory devices; however, for such systems to be of any practical use, reliability and fault tolerance must be guaranteed, for instance by detecting corrupted readings amidst the huge amount of gathered sensory data. This paper proposes an adaptive distributed Bayesian approach for detecting outliers in data collected by a wireless sensor network; our algorithm aims at optimizing classification accuracy, time complexity and communication com…
Secure random number generation in wireless sensor networks
The increasing adoption of wireless sensor networks as a flexible and inexpensive tool for the most diverse applications, ranging from environmental monitoring to home automation, has raised more and more attention to the issues related to the design of specifically customized security mechanisms. The scarcity of computational, storage, and bandwidth resources cannot definitely be disregarded in such context, and this makes the implementation of security algorithms particularly challenging. This paper proposes a security framework for the generation of true random numbers, which are paramount as the core building block for many security algorithms; the intrinsic nature of wireless sensor no…
FAULT DETECTION AND DATA PREDICTION FOR WIRELESS SENSOR NETWORKS
In the last few years, Wireless Sensor Networks (WSNs) have been extensively used as a pervasive sensing module of Ambient Intelligence (AmI) systems in several application fields, thanks to their versatility and ability to monitor diverse environmental quantities. Although wireless sensor nodes are able to perform onboard computations and to share the sensed data, they are limited by the scarcity of energy resources which heavily influences the network lifetime; moreover, the design phase of a WSN requires testing the application scalability prior to actual deployment. In this regard, this dissertation focuses on data prediction to address such crucial tasks as prolonging the network lifet…
Investigating how user avatar in touchless interfaces affects perceived cognitive load and two-handed interactions
In recent years, touchless-enabling technologies have been more and more adopted for providing public displays with gestural interactivity. This has led to the need for novel visual interfaces aimed at solving issues such as communicating interactivity to users, as well as supporting immediate usability and "natural" interactions. In this paper, we focus our investigation on a visual interface based only on the use of in-air direct manipulations. Our study aims at evaluating whether and how the presence of an Avatar that replays user's movements may decrease the perceived cognitive workload during interactions. Moreover, we conducted a brief evaluation of the relationship between the presen…
A distributed Bayesian approach to fault detection in sensor networks
Sensor networks are widely used in industrial and academic applications as the pervasive sensing module of an intelligent system. Sensor nodes may occasionally produce incorrect measurements due to battery depletion, dust on the sensor, manumissions and other causes. The aim of this paper is to develop a distributed Bayesian fault detection algorithm that classifies measurements coming from the network as corrupted or not. The computational complexity is polynomial so the algorithm scales well with the size of the network. We tested the approach on a synthetic dataset and obtained significant results in terms of correctly labeled measurements.
Adaptable data models for scalable Ambient Intelligence scenarios
In most real-life scenarios for Ambient Intelligence, the need arises for scalable simulations that provide reliable sensory data to be used in the preliminary design and test phases. This works present an approach to modeling data generated by a hybrid simulator for wireless sensor networks, where virtual nodes coexist with real ones. We apply our method to real data available from a public repository and show that we can compute reliable models for the quantities measured at a given reference site, and that such models are portable to different environments, so as to obtain a complete, scalable and reliable testing environment.
Secure random number generation in wireless sensor networks
The increasing adoption of wireless sensor networks as a flexible and inexpensive tool for the most diverseapplications, ranging from environmental monitoring to home automation, has raised more and more atten-tion to the issues related to the design of specifically customized security mechanisms. The scarcity ofcomputational, storage, and bandwidth resources cannot definitely be disregarded in such context, and thismakes the implementation of security algorithms particularly challenging. This paper proposes a securityframework for the generation of true random numbers, which are paramount as the core building blockfor many security algorithms; the intrinsic nature of wireless sensor nodes …
Predictive models for energy saving in Wireless Sensor Networks
ICT devices nowadays cannot disregard optimizations toward energy sustainability. Wireless Sensor Networks, in particular, are a representative class of a technology where special care must be given to energy saving, due to the typical scarcity and non-renewability of their energy sources, in order to enhance network lifetime. In our work we propose a novel approach that aims to adaptively control the sampling rate of wireless sensor nodes using prediction models, so that environmental phenomena can be consistently modeled while reducing the required amount of transmissions; the approach is tested on data available from a public dataset.
Modular Middleware for Gestural Data and Devices Management
In the last few years, the use of gestural data has become a key enabler for human-computer interaction (HCI) applications. The growing diffusion of low-cost acquisition devices has thus led to the development of a class of middleware aimed at ensuring a fast and easy integration of such devices within the actual HCI applications. The purpose of this paper is to present a modular middleware for gestural data and devices management. First, we describe a brief review of the state of the art of similar middleware. Then, we discuss the proposed architecture and the motivation behind its design choices. Finally, we present a use case aimed at demonstrating the potential uses as well as the limit…
A simple operation strategy of battery storage systems under dynamic electricity pricing: An Italian case study for a medium-scale public facility
In the electricity market, wholesale energy prices depend on the balance between energy production and load demand. In the last few years, electricity market has become more and more flexible as many utilities have started to replace the fixed retail prices schemes with prices changing during the day. Dynamic pricing, also known as Real-Time Pricing (RTP), reflects the trend of the wholesale market and allows to reduce the volatility of the wholesale prices, also contributing to a reduction of demand peaks. Electricity customers take advantage of dynamic pricing by shifting their consumption according to the real-time prices or by using Battery Energy Storage Systems (BESS) to shift electri…
Predicting mid-air gestural interaction with public displays based on audience behaviour
Abstract Knowledge about the expected interaction duration and expected distance from which users will interact with public displays can be useful in many ways. For example, knowing upfront that a certain setup will lead to shorter interactions can nudge space owners to alter the setup. If a system can predict that incoming users will interact at a long distance for a short amount of time, it can accordingly show shorter versions of content (e.g., videos/advertisements) and employ at-a-distance interaction modalities (e.g., mid-air gestures). In this work, we propose a method to build models for predicting users’ interaction duration and distance in public display environments, focusing on …
A HEURISTIC LOAD MANAGEMENT APPROACH FOR DOMESTIC APPLIANCES
In this paper, an innovative heuristic for domestic loads management is proposed. The method is straightforward and easy to be implemented on embedded systems. The idea is to start from the mathematical modeling of loads and to perform a profile based scheduling, namely loads will try to fit a given schedule. The solution of the scheduling is based on a rolling horizon of 24 hours and is recomputed when an ON signal is provided to the considered appliance. Experimental results show the pertinence of the approach and how it may be profitably used to lower the energy costs for the end user.
Reputation Management for Distributed Service-Oriented Architectures
Nowadays, several network applications require that consumer nodes acquire distributed services from unknown service providers on the Internet. The main goal of consumer nodes is the selection of the best services among the huge multitude provided by the network. As basic criteria for this choice, service cost and Quality-of-Service (QoS) can be considered, provided that the underlying Service-Oriented Architecture (SOA) be augmented in order to support the declaration of this information. The correct behavior of such new SOA platforms, however, will depend on the presence of some mechanisms that allow consumer nodes to evaluate trustworthiness of service providers. This work proposes a new…
QoS-Aware Fault Detection in Wireless Sensor Networks
Wireless sensor networks (WSNs) are a fundamental building block of many pervasive applications. Nevertheless the use of such technology raises new challenges regarding the development of reliable and fault-tolerant systems. One of the most critical issues is the detection of corrupted readings amidst the huge amount of gathered sensory data. Indeed, such readings could significantly affect the quality of service (QoS) of the WSN, and thus it is highly desirable to automatically discard them. This issue is usually addressed through “fault detection” algorithms that classify readings by exploiting temporal and spatial correlations. Generally, these algorithms do not take into account QoS re…