Papers by Salvatore Gaglio
IEEE Access
Wireless Sensor Networks (WSNs) represent a key component in emerging distributed computing parad... more Wireless Sensor Networks (WSNs) represent a key component in emerging distributed computing paradigms such as IoT, Ambient Intelligence, and Smart Cities. In these contexts, the difficulty of testing, verifying, and monitoring applications in their intended scenarios ranges from challenging to impractical. Current simulators can only be used to investigate correctness at source code level and with limited accuracy. This paper proposes a system and a methodology to model and verify symbolic distributed applications running on WSNs. The approach allows to complement the distributed application code at a high level of abstraction in order to test and reprogram it, directly, on deployed network devices. The proposed intelligent architecture enables the execution of distributed applications and the verification of the supplied correctness conditions. This paper shows the feasibility of the proposed approach and its effectiveness even when networks include resource-constrained nodes with some sample applications and quantitative experiments measuring the overhead introduced by the monitoring operations.
Mathematics
The possibility of integrating quantum computation in a traditional system appears to be a viable... more The possibility of integrating quantum computation in a traditional system appears to be a viable route to drastically improve the performance of systems endowed with artificial intelligence. An example of such processing consists of implementing a teleo-reactive system employing quantum computing. In this work, we considered the navigation of a robot in an environment where its decisions are drawn from a quantum algorithm. In particular, the behavior of a robot is formalized through a production system. It is used to describe the world, the actions it can perform, and the conditions of the robot’s behavior. According to the production rules, the planning of the robot activities is processed in a recognize–act cycle with a quantum rule processing algorithm. Such a system aims to achieve a significant computational speed-up.
Sensors
We propose a methodology to verify applications developed following programming patterns inspired... more We propose a methodology to verify applications developed following programming patterns inspired by natural language that interact with physical environments and run on resource-constrained interconnected devices. Natural language patterns allow for the reduction of intermediate abstraction layers to map physical domain concepts into executable code avoiding the recourse to ontologies, which would need to be shared, kept up to date, and synchronized across a set of devices. Moreover, the computational paradigm we use for effective distributed execution of symbolic code on resource-constrained devices encourages the adoption of such patterns. The methodology is supported by a rule-based system that permits runtime verification of Software Under Test (SUT) on board the target devices through automated oracle and test case generation. Moreover, verification extends from syntactic and semantic checks to the evaluation of the effects of SUT execution on target hardware. Additionally, by...
The object-oriented paradigm enriched with the definition of design patterns proved successful in... more The object-oriented paradigm enriched with the definition of design patterns proved successful in lowering the development time and number of errors in produced software; now a similar phenomenon is occurring for multi-agent systems, where this is related to the great effort that has been currently spent in methodology definitions by several researchers. In this work we describe our experiences in the identification, description, production and application of agent patterns. Upon our pattern definition, we base a reuse process that can be considered as a crosscutting phase of the entire PASSI design methodology, from analysis to development. A classification criteria and a documentation template was defined in order to help user in selecting a pattern from the repository. The pattern solution is described using an MDA multi-level approach allowing us to automatically produce both source code (for multiple agent platforms) and UML diagrams (usually almost a structural and a dynamic d...
WIT Transactions on Information and Communication Technologies, 1970
A cognitive architecture for an artificial vision system, aimed for an autonomous intelligent sys... more A cognitive architecture for an artificial vision system, aimed for an autonomous intelligent system, is presented with particular attention to performance aspects. The architecture, based on the active vision paradigm, is cognitive in the sense that several cognitive hypotheses have been postulated as guidelines for its design in order to achieve good performance.
2021 IEEE International Conference on Smart Computing (SMARTCOMP), 2021
Simulations are indispensable to reduce costs and risks when developing and testing algorithms fo... more Simulations are indispensable to reduce costs and risks when developing and testing algorithms for unmanned aerial vehicles (UAV) especially for applications in high risk scenarios like search and rescue (SAR) operations and post-disaster damage assessment. Many UAV applications require real-time tasks for which the timeliness of computations is fundamental. However, standard simulation tools are not guaranteed to run in sync with real-time events, leading to unreliable assessments of the ability of the target hardware to perform specific tasks. In this work we present a simulation and test system able to run UAV tasks on resource-constrained target hardware possibly adopted in these applications. The system allows for hardware-in-the-loop simulations in which a virtual UAV provided with virtual sensors is controlled by the software under test (SUT) running on the target hardware, while simulated and real time are kept in sync. We provide experimental results from the execution of several increasingly difficult tasks in the system.
2017 AEIT International Annual Conference, 2017
Nowadays, the population's average age is constantly increasing, and thus the need for specialize... more Nowadays, the population's average age is constantly increasing, and thus the need for specialized home assistance is on the rise. Smart homes especially tailored to meet elderly and disabled people's needs can help them maintaining their autonomy, whilst ensuring their safety and well-being. This paper proposes a complete context-aware system for Ambient Assisted Living (AAL), which infers user's actions and context, analyzing its past and current behavior to detect anomalies and prevent possible emergencies. The proposed system exploits Dynamic Bayesian Networks to merge raw data coming from heterogeneous sensors and infer user's behavior and health conditions. A rule-based reasoner is able to detect and predict anomalies in such data, sending appropriate alerts to caregivers and family members. The effectiveness of the proposed AAL system is demonstrated by extensive experimental results carried out in a simulated smart home.
2019 IEEE International Conference on Smart Computing (SMARTCOMP), 2019
Being part of one of the fastest growing area in Artificial Intelligence (AI), virtual assistants... more Being part of one of the fastest growing area in Artificial Intelligence (AI), virtual assistants are nowadays part of everyone's life being integrated in almost every smart device. Alexa, Siri, Google Assistant, and Cortana are just few examples of the most famous ones. Beyond these off-the-shelf solutions, different technologies which allow to create custom assistants are available. IBM Watson, for instance, is one of the most widely-adopted question-answering framework both because of its simplicity and accessibility through public APIs. In this work, we present a virtual assistant that exploits the Watson technology to support students and staff of a smart campus at the University of Palermo. Some in progress results show the effectiveness of the approach we propose.
AI*IA 2017 Advances in Artificial Intelligence, 2017
In recent years, the percentage of the population owning a smartphone has increased significantly... more In recent years, the percentage of the population owning a smartphone has increased significantly. These devices provide the user with more and more functions, so that anyone is encouraged to carry one during the day, implicitly producing that can be analysed to infer knowledge of the user's context. In this work we present a novel framework for Human Activity Recognition (HAR) using smartphone data captured by means of embedded triaxial accelerometer and gyroscope sensors. Some statistics over the captured sensor data are computed to model each activity, then real-time classification is performed by means of an efficient supervised learning technique. The system we propose also adopts a participatory sensing paradigm where user's feedbacks on recognised activities are exploited to update the inner models of the system. Experimental results show the effectiveness of our solution as compared to other state-of-the-art techniques.
2015 IEEE 20th Conference on Emerging Technologies & Factory Automation (ETFA), 2015
Many issues in creating complex applications for pervasive environments are primarily due to the ... more Many issues in creating complex applications for pervasive environments are primarily due to the effort required to integrate perception, reasoning and actuating tasks in an efficient and homogeneous way, especially when the underlying infrastructure consists of wirelessly networked embedded devices. To mitigate the complexity of the actual implementation, satisfactory programming paradigms supporting the integration and coordination among heterogeneous devices are required. In this paper we show how a distributed symbolic processing approach that is particularly suited for resource constrained devices, such as the nodes of a Wireless Sensor and Actuator Network (WSAN), may be apt to the purpose. We also discuss a case study in which sensors and actuators, without any centralized control, act on the environment according to the thermal preferences that are continuously learned and monitored.
Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, 2015
While the vision of Internet of Things (IoT) is rather inspiring, its practical implementation re... more While the vision of Internet of Things (IoT) is rather inspiring, its practical implementation remains challenging. Conventional programming approaches prove unsuitable to provide IoT resource constrained devices with the distributed processing capabilities required to implement intelligent, autonomic, and self-organizing behaviors. In our previous work, we had already proposed an alternative programming methodology for such systems that is characterized by high-level programming and symbolic expressions evaluation, and developed a lightweight middleware to support it. Our approach allows for interactive programming of deployed nodes, and it is based on the simple but effective paradigm of executable code exchange among nodes. In this paper, we show how our methodology can be used to provide IoT resource constrained devices with reasoning abilities by implementing a Fuzzy Logic symbolic extension on deployed nodes at runtime.
2006 IEEE/WIC/ACM International Conference on Intelligent Agent Technology, 2006
The representation of goals and the ability to reason about them play an important role in goal-o... more The representation of goals and the ability to reason about them play an important role in goal-oriented requirements analysis and modelling techniques, especially in agent-oriented software engineering, as goals are more stable than other abstractions (e.g. user stories). In PRACTIONIST, a framework for developing agent systems according to the Belief-Desire-Intention (BDI) model, goals play a central role. Thus, in this paper we describe the structure of the goal model in the PRACTIONIST framework and how agents use their goal model to reason about goals, desires, and intentions during their deliberation process and means-ends reasoning as well as while performing their activities.
The main aim of this paper is contributing to what in the last few years has been known as comput... more The main aim of this paper is contributing to what in the last few years has been known as computational creativity. This will be done by showing the relevance of a particular mathematical representation of Gärdenfors's conceptual spaces to the problem of modelling a phenomenon which plays a central role in producing novel and fruitful representations of perceptual patterns: analogy.
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 2009
Lecture Notes in Computer Science, 2008
The Self-Organizing Map (SOM) is a popular unsupervised neural network able to provide effective ... more The Self-Organizing Map (SOM) is a popular unsupervised neural network able to provide effective clustering and data visualization for data represented in multidimensional input spaces. In this paper we describe Fast Learning SOM (FLSOM) which adopts a learning algorithm that improves the performance of the standard SOM with respect to the convergence time in the training phase. We show that FLSOM also improves the quality of the map by providing better clustering quality and topology preservation of multidimensional input data. Several tests have been carried out on different multidimensional datasets, which demonstrate better performances of the algorithm in comparison with the original SOM.
2007 International Joint Conference on Neural Networks, 2007
Visual exploration of scientific data in life science area is a growing research field due to the... more Visual exploration of scientific data in life science area is a growing research field due to the large amount of available data. The Kohonen's Self Organizing Map (SOM) is a widely used tool for visualization of multidimensional data. In this paper we present a fast learning algorithm for SOMs that uses a simulated annealing method to adapt the learning parameters. The algorithm has been adopted in a data analysis framework for the generation of similarity maps. Such maps provide an effective tool for the visual exploration of large and multi-dimensional input spaces. The approach has been applied to data generated during the High Throughput Screening of molecular compounds; the generated maps allow a visual exploration of molecules with similar topological properties. The experimental analysis on real world data from the National Cancer Institute shows the speed up of the proposed SOM training process in comparison to a traditional approach. The resulting visual landscape groups molecules with similar chemical properties in densely connected regions.
Lecture Notes in Computer Science, 2013
2009 International Conference on New Trends in Information and Service Science, 2009
Recently the companies' interest on a correct knowledge management is grown, more than interest o... more Recently the companies' interest on a correct knowledge management is grown, more than interest on the mere knowledge itself. In the last few years, several projects have been carried out, with the aim of the development of innovative systems capable of collecting and sharing information. This paper proposes a Knowledge Management System, whose main feature is an ontological knowledge representation. The ontological representation of data allows of specializing the reasoning capabilities and of providing ad hoc behaviors. The system has been tested collecting and using data coming from projects and processes typical of ICT companies, and provides a Document Management System and an Expert System to share documents and to plan how to best use firms' knowledge.
Advances in Intelligent Systems and Computing, 2014
Research on Ambient Intelligence (AmI) focuses on the development of smart environments adaptable... more Research on Ambient Intelligence (AmI) focuses on the development of smart environments adaptable to the needs and preferences of their inhabitants. For this reason it is important to understand and model user preferences. In this chapter we describe a system to detect user behavior patterns in an intelligent workplace. The system is designed for a workplace equipped in the context of Sensor 9 k, a project carried out at the Department of Computer Science at the University of Palermo (Italy). Research in Ambient Intelligence (AmI) focuses on the development of smart environments, generally equipped with wireless sensor networks, allowing the gathering of data about the environment state ; such data needs to be processed and analyzed in order to deduce useful information. Ambient Intelligence brings intelligence to our everyday environments making those environments sensitive, and adaptive to us . The definition of appropriate user profiles can allow an AmI system to anticipate their needs, and adapt the environment settings to their preferences . User profiling can also be used to detect significant changes in resident behaviors , to customize building energy and comfort management systems [6], or to allow automatic setting of system parameters in order to optimize energy consumption . Most systems perform an explicit profiling or derive users presence and activity by analyzing the sensor data and the use of actuators. In many projects, data mining A.
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Papers by Salvatore Gaglio