An AI-based Ventilation KPI using embedded IoT devices

The air ventilation of enclosed premises has a direct impact on the occupants well-being. If not properly regulated, the air ventilation can originate a multitude of diseases and pathologies. The present study proposes a new KPI (ventilation KPI) adapted to Smart Cities. It is especially designed for academic environments (Smart Universities) in which community members spend a long time gathered in classrooms, seminars, laboratories, etc. The ventilation KPI (or KPIv) was designed to support decision-making and is based on the estimation of the number of occupants of an enclosed space and the accumulation of existing CO2. Two AI techniques are proposed to perform these estimations, specifically, two regressive neural networks. The resulting models, together with the KPI were implemented through the development of value-added services for the University of Alicantes Smart University platform. The network models were designed to be embedded within the built IoT device prototypes. These prototypes are small and inexpensive. They act as intelligent sensors and are connected via a low consumption and emission network (LoRa). The case study showed that it is possible to take advantage of the pre-existing services and resources of these platforms, and to validate the KPIv

IT Strategic Project Portfolio - Process Sheets

This document describes in detail the processes that make up the framework of the IT Strategic Project Portfolio (ITSPP). It has been developed within the GrupoM: Redes y Middleware research group at the University of Alicante

Strategic IT alignment Projects. Towards Good Governance

The senior management of organisations frequently perceive IT Projects as merely technological in nature. They fail to realise that in reality, the mission of IT is to provide technology-based support to business processes that can be key to the organisation. This lack of understanding means that these IT projects are not aligned with the business objectives and that investments in resources and personnel are not adequately prioritised. This can lead to an opportunity loss: a mere computerising of the business is sought, and processes that could turn out to be transformative, generating added value, driving a true digital transformation of the business are overlooked. This article proposes a model for implementing and operating a portfolio of strategic IT projects. Based on Good Governance principles, these latter projects move strategic decision-making up to an organisation's senior management, succeeding in gradually implicating these managers into the IT strategy. But above all, the model succeeds in achieving the targeted strategic alignment of IT projects with the organisation's business objectives and interests. The model has already been implemented in fourteen medium and large size public universities. The follow-up through interviews of the nine longest-standing experiences—some are nearly a decade old—revealed that the portfolio implementation strategy had helped to markedly improve the following elements: the institutions’ state of maturity of Good Governance; senior management's involvement in IT projects; and the identification of the most interesting IT projects for the business. To conclude, based on our experience, we can affirm that the strategic IT alignment projects is an effective IT Governance tool and, by extension, an example of Good Governance practice

Anomaly Detection System for Data Quality Assurance in IoT infrastructures based on Machine Learning

The inclusion of IoT in digital platforms is very common nowadays due to the ease of deployment, low power consumption and low cost. It is also common to use heterogeneous IoT devices of ad-hoc or commercial development, using private or third-party network infrastructures. This scenario makes it difficult to detect invalid packets from malfunctioning devices, from sensors to application servers. These invalid packets generate low quality or erroneous data, which negatively influence the services that use them. For this reason, we need to create procedures and mechanisms to ensure the quality of the data obtained from IoT infrastructures, regardless of the type of infrastructure and the control we have over them, so that the systems that use this data can be reliable. In this work we propose the development of an Anomaly Detection System for IoT infrastructures based on Machine Learning using unsupervised learning. We validate the proposal by implementing it on the IoT infrastructure of the University of Alicante, which has a multiple sensing system and uses third-party services, over a campus of one million square meters. The contribution of this work has been the generation of an anomaly detection system capable of revealing incidents in IoT infrastructures, without knowing details about the infrastructures or devices, through the analysis of data in real time. This proposal allows to discard from the IoT data flow all those packets that are suspected to be anomalous to ensure a high quality of information to the tools that consume IoT data.This project has been funded by the UAIND22-01B project "Adaptive control of urban supply systems" of the University of Alicante

Conceptual Modelling of Complex Network Management Systems

Society, as we know it today, is completely dependent on computer networks, Internet and distributed systems, which place at our disposal the necessary services to perform our daily tasks. Moreover, and unconsciously, all services and distributed systems require network management systems. These systems allow us to, in general, maintain, manage, configure, scale, adapt, modify, edit, protect or improve the main distributed systems. Their role is secondary and is unknown and transparent to the users. They provide the necessary support to maintain the distributed systems whose services we use every day. If we don’t consider network management systems during the development stage of main distributed systems, then there could be serious consequences or even total failures in the development of the distributed systems. It is necessary, therefore, to consider the management of the systems within the design of distributed systems and systematize their conception to minimize the impact of the management of networks within the project of distributed systems. In this paper, we present a formalization method of the conceptual modelling for design of a network management system through the use of formal modelling tools, thus allowing from the definition of processes to identify those responsible for these. Finally we will propose a use case to design a conceptual model intrusion detection system in network.This work was performed as part of the Smart University Project financed by the University of Alicante

Conceptual Modelling of Complex Network Management Systems

Society, as we know it today, is completely dependent on computer networks, Internet and distributed systems, which place at our disposal the necessary services to perform our daily tasks. Moreover, and unconsciously, all services and distributed systems require network management systems. These systems allow us to, in general, maintain, manage, configure, scale, adapt, modify, edit, protect or improve the main distributed systems. Their role is secondary and is unknown and transparent to the users. They provide the necessary support to maintain the distributed systems whose services we use every day. If we don’t consider network management systems during the development stage of main distributed systems, then there could be serious consequences or even total failures in the development of the distributed systems. It is necessary, therefore, to consider the management of the systems within the design of distributed systems and systematize their conception to minimize the impact of the management of networks within the project of distributed systems. In this paper, we present a formalization method of the conceptual modelling for design of a network management system through the use of formal modelling tools, thus allowing from the definition of processes to identify those responsible for these. Finally we will propose a use case to design a conceptual model intrusion detection system in network.This work was performed as part of the Smart University Project financed by the University of Alicante

A new paradigm: cloud agile manufacturing

Cloud Agile Manufacturing is a new paradigm proposed in this article. The main objective of Cloud Agile Manufacturing is to offer industrial production systems as a service. Thus users can access any functionality available in the cloud of manufacturing (process design, production, management, business integration, factories virtualization, etc.) without knowledge — or at least without having to be experts — in managing the required resources. The proposal takes advantage of many of the benefits that can offer technologies and models like: Business Process Management (BPM), Cloud Computing, Service Oriented Architectures (SOA) and Ontologies. To develop the proposal has been taken as a starting point the Semantic Industrial Machinery as a Service (SIMaaS) proposed in previous work. This proposal facilitates the effective integration of industrial machinery in a computing environment, offering it as a network service. The work also includes an analysis of the benefits and disadvantages of the proposal

Goal-oriented Email Stream Classifier with A Multi-agent System Approach

Now-a-days, email is often one of the most widely used means of communication despite the rise of other communication methods such as instant messaging or communication via social networks. The need to automate the email stream management increases for reasons such as multi-folder categorization, and spam email classification. There are solutions based on email content, capable of contemplating elements such as the text subjective nature, adverse effects of concept drift, among others. This paper presents an email stream classifier with a goal-oriented approach to client and server environment. The i* language was the basis for designing the proposed email stream classifier. The email environment was represented with the early requirements model and the proposed classifier with the late requirements model. The classifier was implemented following a multi-agent system approach supported by JADE agent platform and Implementation_JADE pattern. The behavior of agents was taking from an existing classifier. The multi-agent classifier was evaluated using functional, efficacy and performance tests, which compared the existing classifier with the multi-agent approach. The results obtained were satisfactory in all the tests. The performance of multi-agent approach was better than the existing classifier due to the use of multi-threads.This work was performed as part of the Smart University Project financed by the University of Alicante

Método para la detección de intrusos mediante redes neuronales basado en la reducción de características

La aplicación de técnicas basadas en Inteligencia Artificial para la detección de intrusos (IDS), fundamentalmente las redes neuronales artificiales (ANN), están demostrando ser un enfoque muy adecuado para paliar muchos de los problemas abiertos en esta área. Sin embargo, el gran volumen de información que se requiere cada día para entrenar estos sistemas, junto con la necesidad exponencial de tiempo que requieren para asimilarlos, dificulta enormemente su puesta en marcha en escenarios reales. En este trabajo se propone un método basado en la aplicación de una técnica para la reducción de características, denominada Análisis de Componentes Principales (PCA). El PCA permite obtener un modelo para la reducción del tamaño de los vectores de entrada a la ANN, asegurando que la pérdida de información sea mínima y, en consecuencia, disminuyendo la complejidad del clasificador neuronal y manteniendo estables los tiempos de entrenamiento. Para validar la propuesta se ha diseñado un escenario de prueba mediante un IDS basado en ANN. Los resultados obtenidos a partir de las pruebas realizadas demuestran la validez de la propuesta y acreditan las líneas futuras de trabajo.Este trabajo ha sido financiado por el Ministerio de Educación y Ciencia de España bajo el proyecto de investigación TIN2006-04081 y por la Generalitat Valenciana bajo el proyecto de investigación GV/2007175

Specifying Requirements for Modern Software Development: A Test-Oriented Methodology

Most modern computer systems operate in distributed environments. To develop and test such applications, services, and systems, it is necessary to consider the physical devices, architectures, communication, security and deployment mechanisms involved. However, the requirements’ specification process still replicates that of traditional applications: details remain implicit and are hidden in the description. As a result, specifications are difficult to identify and, ultimately, tests are designed in the traditional way: they overlook constraints and fail to achieve the desired effects. Our objective is to design a methodology for specifying requirements in both traditional software and applications deployed in distributed environments. We present an iterative and incremental requirements specification methodology. This methodology allows us to describe functional requirements and incorporate non-functional or quality constraints, which is the main contribution of this proposal. To ensure that quality requirements are specified during the design phase, the methodology proposes a series of phases, stages and artefacts that ensure the discovery and consideration of these requirements. In order to find out the strengths and weaknesses of our methodology, we have carried out a comparative study with other similar proposals in the literature. To this end, evaluation criteria were defined by considering standards and good practices in Requirements Engineering. The results of the comparative study show that our methodology constitutes a solid procedure for a detailed requirements specification from the beginning of the software development cycle. This represents an advance over the rest of the proposals studied. Our methodology contributes to the simplification of the design and execution phases of software testing, enabling traceability between the specified requirements and the designed test cases