Mechanism Design Approach for Energy Efficiency

In this work we deploy a mechanism design approach for allocating a divisible commodity (electricity in our example) among consumers. We consider each consumer with an associated personal valuation function of the energy resource during a certain time interval. We aim to select the optimal consumption profile for every user avoiding consumption peaks when the total required energy could exceed the energy production. The mechanism will be able to drive users in shifting energy consumptions in different hours of the day. We start by presenting a very basic Vickrey-Clarke-Groves mechanism, we discuss its weakness and propose several more complex variants.Comment: Techical repor

Human Activity Recognition using a Semantic Ontology-Based Framework

In the last years, the extensive use of smart objects embedded in the physical world, in order to monitor and record physical or environmental conditions, has increased rapidly. In this scenario, heterogeneous devices are connected together into a network. Data generated from such system are usually stored in a database, which often shows a lack of semantic information and relationship among devices. Moreover, this set can be incomplete, unreliable, incorrect and noisy. So, it turns out to be important both the integration of information and the interoperability of applications. For this reason, ontologies are becoming widely used to describe the domain and achieve efficient interoperability of information system. An example of the described situation could be represented by Ambient Assisted Living context, which intends to enable older or disabled people to remain living independently longer in their own house. In this contest, human activity recognition plays a main role because it could be considered as starting point to facilitate assistance and care for elderly. Due to the nature of human behavior, it is necessary to manage the time and spatial restrictions. So, we propose a framework that implements a novel methodology based on the integration of an ontology for representing contextual knowledge and a Complex Event Processing engine for supporting timed reasoning. Moreover, it is an infrastructure where knowledge, organized in conceptual spaces (based on its meaning) can be semantically queried, discovered, and shared across applications. In our framework, benefits deriving from the implementation of a domain ontology are exploited into different levels of abstrac- tion. Thereafter, reasoning techniques represent a preprocessing method to prepare data for the final temporal analysis. The results, presented in this paper, have been obtained applying the methodology into AALISABETH, an Ambient Assisted Living project aimed to monitor the lifestyle of old people, not suffering from major chronic diseases or severe disabilities

An ontology-based consultation system to support medical care on board seagoing vessels

Background: A realistic possibility to obtain medical care for patients located in remote sites such as seagoing vessels, in which health professionals are not available, is to contact a doctor via telecommunication systems. In general, the medical knowledge of who on board ships is in charge of medical care is quite limited and therefore, in a first level telemedical consultation, the flow of information should be correct and its efficiency should be maximised. This paper describes an application conceived to improve requests of medical assistance from sailing ships. The ultimate objective of this system is a) to standardise as much as possible the requests of medical advice at a distance, b) to overcome language barriers and jammed-related troubles that could make difficult or not understandable a telephone conversation. Materials and methods: The application is based on a software engine extracting data from an ontological knowledgebase built ad hoc using Protégé. Results: Compared to the conventional consultation systems based on telephone and e-mail, the proposed device is more accurate and complete in terms of information contained in the request of assistance. Moreover, data received by the medical centre can be more easily managed, as they can be standardised. Conclusions: The system described here allows people responsible of medical care on board ships to forward detailed requests of assistance containing symptom-guided information on patient clinical conditions. This may represent an innovative tool for medical consultations at distance allowing the remote centre to provide more precise and quicker medical advice.

An Artificial Neural Network-based Prediction Model for Underdog Teams in NBA Matches

In this work, we present an artificial neural network-based prediction model for underdog teams in NBA matches (ANNUT). We describe the steps of our supervised algorithm, starting from data acquisition to prediction selection. We talk about prediction selection because the final stage of our model is represented by a filtration phase. In this phase, the outputs returned from the neural network are evaluated according to how the events are quoted on one of the most famous bookmakers. Experimental results prove that the model is able to select with a certain accuracy winning teams. In particular, it reaches excellent results when we restrict the selection among underdogs (teams which probably will not win). Furthermore, we show that a significant sports prediction model cannot ignore bookmaker’s odds

Mechanism Design Approach for Energy Efficiency

In a real world, there exist different energy sources that provide the required energy (photovoltaic (PV), nuclear, hydroelectric, etc). Therefore, the trend of the amount of available energy is constantly changing by the day. At the other hand, the consumption of a community of users depends on users’ lifestyles, day of the week, season, ecc. In the literature, this kind of problem is called demand side management (DSM), that is the modification of consumer demand for energy through various methods such as financial incentives and behavioral change through education. During my research activities, I am developing a model that is able to manage the energy demand in order to reach an efficiency goal: consuming the whole produced energy. The model takes into account the social goal that is represented by the optimal use of the energy produced. This can be achieved by behavioural changes induced in the users modifying dynamically the energy cost per hour. In this work, I want to deploy a game-theoretic approach in order to tackle this DSM issue. The objective is to modify users’ behavior in order to avoid consumption peaks and to involve the users into a more careful energy consumption. The mechanism will be able to drive users in shifting energy consumptions, by selecting an appropriate energy pricing scheme considering the amount of available energy according to the energy consumption preference of every users. This result could be achieved through an incentive approach, for instance to give more expensive energy rate for specific peak hours. The aim is to develop a mechanism (in a game theoretic sense), that want to pursuit a global objective (the optimal energy use) through the independent maximization of single user’s utility, according to the definition of a social choice function and a payment scheme

A Fair Payment Scheme for Virtuous Community Energy Usage.

In this work, we face a payment estimation problem that involves a community of users and an energy distributor (or producer). Our aim is to compute payments for every user in the community according to the single user’s consumption, the community’s consumption and the available energy. The proposed scheme influences the community in consuming in a virtuous way. In order to reach this goal, our payment function distributes incentives if the consumption is lower than the produced energy and penalties when the consumption exceeds the resources threshold. Our model satisfies efficiency and fairness properties both from the community (efficiency as an economic equilibrium among sellers and buyers) and the single user (fairness as an economic measure of energy good-behaving) points of view. By computing community-dependent energy bills, our model stimulates a virtuous users’ behaviour so that it approaches the production threshold as close as possible. We also provide a simulation based on real data referring to a dataset of buildings in California State, thus, showing several possible shapes of our payment scheme

A mechanism design approach for allocation of commodities

We deploy a mechanism design approach for allocating a divisible commodity (electricity in our example) among consumers. We consider each consumer with an associated personal valuation function of the energy resource during a certain time interval. We aim to select the optimal consumption profile for every user avoiding consumption peaks when the total required energy could exceed the energy production. The mechanism will be able to drive users in shifting energy consumptions in different hours of the day. We start by presenting a very basic Vickrey-Clarke-Groves mechanism, we discuss its weakness and propose several more complex variants. This is an extended abstract, for additional details we provide a technical report [1]. Copyright © by the paper's authors. Copying permitted for private and academic purposes

Using Ontology and Complex Event Processing Engine for Human Activity Recognition in Ambient Assisted Living domain

As a result of the rising older people population, the Ambient Assisted Living (AAL) branch is growing up fast. Generally, the main goal of an AAL system is to help old people to live in their own houses longer and with an improved quality of life. In fact, its functionalities are based on the use of a set of different sensors interconnected by different types of communication systems to get information about the status of patients. The installed sensors network produce a set of data that shows a fine—grained nature, carrying generally their value, originating device, data type, timestamp and so on. For this reason, it is not always possible to have a clear overall view. Since it is often needed an analysis procedure which is able to take into account the semantic of records, ontologies are becoming widely used to describe the domain and to enrich the acquired data with its significance. In our research work, we propose a methodology arranged by two components integrated sequentially: an ontology [1] and a Complex Event Processing (CEP) [2] engine. The ontology has is built following a precise structure and it is able to describe the AAL domain, organize data according to their semantic meaning and select them (pre-processing phase). The main serious expressiveness limitation of OWL ontology is the lack of temporal reasoning, so in the framework it is introduced after ontology a CEP engine that is a technique concerned with timely detection of compound events within streams of simple events. Our challenge is to perform semantic queries on a data repository, whose records originate from a network of heterogeneous sources. The main goal of such queries is the pattern matching process, i.e. recognition of specific temporal sequences in fine—grained data. In our framework, benefits deriving from the implementation of a domain ontology are exploited i11 different levels of abstraction. Thereafter, reasoning techniques represent a pre—processing method that prepares data for the final temporal analysis. Our proposed approach will be applied to the ongoing AALISABETH [3], an Ambient Assisted Living project aimed to discover and manage the behavior of monitored users