Álvaro Lozano Murciego

Monitoring and analysis of vital signs of a patient through a multi-agent application system

In the medical environment, the clinical study of the most basic vital signs of a patient represents the simplest and most effective way to detect and monitor health problems. There are many diseases that can be diagnosed and controlled through regular monitoring of these medical data. The purpose of this study is to develop a monitoring and tracking system for the various vital signs of a patient. In particular, this work focuses on the design of a multi-agent architecture composed of virtual organizations with capabilities to integrate different medical sensors on an open, low-cost hardware platform. This system integrates hardware and software elements needed for the routine measurement of vital signs, performed by the patient or caregiver without having to go to a medical center.

Non Intrusive Load Monitoring (NILM): A State of the Art

The recent increase in smart meters installations in households and small bussiness by electric companies has led to interest in monitoring load techniques in order to provide better quality service and get useful information about appliance usage and user consumption behavior. This works summarizes the current state of the art in Non Intrusive Load Monitoring from its beginning, describes the main process followed in the literature to perform this technique and shows current methods and techniques followed nowadays. The possible application of this techniques in the context of ambient intelligence, energy efficiency, occupancy detection are described. This work also points the current challenges in the field and the future lines of research in this broad topic.

Single Appliance Automatic Recognition: Comparison of Classifiers

Measuring and recording systems for the consumption of electrical energy which are connected to households, are essential in the optimization of energy use. Non-Intrusive Load Monitoring (NILM) is one of the most used techniques in the study of electrical consumption; these systems are based on the analysis of the load curve (the aggregated electrical consumption of the whole household). Thanks to a significant reduction in the price of sensors and sensor systems in recent years, it is possible to individually monitor each one of the devices connected to the grid. In this paper we compare different classifiers in order to find out which is the most appropriate for the identification of individual appliances attending to their consumption. In this way, we will know which electrical appliance is connected to a smart plug, helping to obtain more accurate and efficient load monitoring systems.

An Intelligent Agent-Based Journalism Platform

Internet upswing has entailed a structural change for journalism in general and the press in particular. The emergence of a new horizontal, low cost and accessible space for communication, has brought profound changes in journalism, both on the production and distribution. In this paper, we present a novel agent-based social platform which aims to improve the organization, management and distribution of the media contents through the application of artificial intelligence techniques.

Multi-agent System for the Recommendation of Electric Bicycle Routes

Nowadays, recommender systems are a key tool in sectors such as online sales, video playback and music on demand or book recommendation systems. This paper proposes a personalized route recommendation system for users of electric vehicles, specifically for e-bike users. Around the world e-bikes have become a real alternative to other motorized modes of transport and they are used for daily commuting. A multi-agent system is used to manage the information produced by the system, which generates route recommendations for users based on the routes they had travelled previously. Recommendations are provided to users through a smart-phone application, which is in charge of registering the data on the routes users travel.

Smart Waste Collection Platform Based on WSN and Route Optimization

In this paper, we present the design and implementation of a novel agent-based platform to collect waste on cities and villages. A low cost sensor prototype is developed to measure the fulfilling level of the containers, a route system is developed to optimize the routes of the trucks and a mobile application has been developed to help drivers in their work. In order to evaluate and validate the proposed platform, a practical case study in a real city environment is modeled using open data available and with the purpose of identifying limitations of the platform.